Blog

DAM Trends 2026: What the DAM Community to look forward to for 2026

Digital Asset Management is no longer just a place to store files. In 2026 the community is reporting a clear shift: organizations want DAM to act as an intelligent operating layer that powers content creation, distribution, rights management, and insights. But there is a capability gap. Ambition is high — AI, integrations, and automation top the opportunity list — and readiness is uneven. Teams face budget constraints, shrinking headcount, conflicting priorities, and pressure to adopt AI before the foundations are in place.

What the community said — quick facts

We asked DAM practitioners two open questions late in the year: what opportunities they see for digital asset management in 2026, and what their top risks and concerns are. The survey returned 105 complete responses spanning DAM practitioners, content and marketing operations, platform and product managers, IT, and executive leadership.

• Top opportunity themes: AI, integrations, workflow and automation, metadata and taxonomy, centralization and governance.
• Top risk themes: AI hype and misuse, funding and staffing cuts, lack of alignment and buy-in, complexity of integrations, surging volume and scale.
• Responses made it clear these priorities are tightly interrelated. People do not see AI as an independent goal — they see it as an accelerant that only works if metadata, integrations, workflows, and governance are solid.

Why 2026 feels different

Several forces are colliding. Formats are more varied. File sizes and asset volumes are growing. Teams are expected to achieve faster turnarounds and greater personalization. At the same time, many organizations are operating with fewer resources.

That dynamic creates two simultaneous pressures: do more with less, and adopt new technologies quickly. Generative AI and agentic capabilities intensify those pressures because leadership often expects rapid gains without understanding the necessary investments in data quality and controls.

Top opportunities — where DAM can add real value

Practitioners are optimistic about what DAM can deliver when it evolves beyond a repository:

• AI-driven efficiency: Use AI to automate repetitive tagging, transcription, image recognition, and routine workflows so teams can focus on higher-value creative work.
• End-to-end content orchestration: Move from a library model to a content creation and distribution platform that connects planning, creation, review, and publishing.
• Integrations that connect the stack: Better connectors to creative tools, CMS, PIM, marketing automation, analytics, and governance systems reduce friction and duplication.
• Metadata, taxonomy, and predictive tagging: Smarter metadata and taxonomies enable discovery, personalization, rights management, and effective AI inputs.
• Workflow and automation: Orchestrated approvals, templating, and automated transformation create repeatable, scalable processes.

Those opportunities are not separate checkbox items. Many respondents described them as stages in a maturity path: metadata and governance as the foundation, integrations as the enabler, automation and workflows as the value layer, and AI as the accelerant.

Top risks — why progress can stall or backfire

AI is being forced into everything whether it makes sense or not.

That direct observation from practitioners captures the primary fear: rushing to adopt AI without readiness risks amplifying existing weaknesses. The most common concerns are:

• AI hype and misuse: Executives are often sold on easy wins. Without clear use cases, mature data, and a governance framework, AI implementations deliver inconsistent, unreliable results.
• Funding and staffing shortages: Budget cuts and headcount reductions are squeezing teams already responsible for rising volumes.
• Lack of alignment and buy-in: Conflicting priorities between marketing, creative, IT, and legal make it hard to build a unified roadmap and get the resources to execute it.
• Integration complexity: Integrating a growing ecosystem of tools is technically possible but operationally expensive to maintain.
• Volume and scale: More assets and channels increase the demand for consistent metadata, permissions, and lifecycle controls.

The central insight: ambition without readiness creates a DAM AI gap

Organizations want DAM to be a system of action. They imagine a platform that automates repetitive work, surfaces the right assets, enforces rights, and enables AI-powered content generation. Yet many DAM programs lack the consistent metadata, stable integrations, and governance required to make that work reliably. When AI is layered on top of shaky foundations the result can be automation of mistakes — faster, louder, and more widespread.

That capability gap is both a risk and an opportunity. The push to adopt AI can be the catalyst for catching up on fundamentals — if leadership recognizes what is required and allocates the right funding and attention.

A practical roadmap for DAM teams in 2026

Moving from aspiration to execution requires a clear, staged plan. The following roadmap is designed for teams that need quick wins while building long-term capability.

First 90 days – stabilize and prove

• Conduct a rapid asset and metadata audit. Identify the highest-value asset classes and the most critical metadata fields for discovery, rights, and reuse.
• Run a small, tightly scoped AI pilot focused on a repeatable task — for example, automated transcription or image tagging for a single asset type.
• Create a governance working group with representatives from marketing, creative operations, IT, legal, and relevant business owners.
• Document short-term KPIs for the pilot: time saved, error rate, reduction in manual effort, or improvements in search relevance.

3 to 6 months – standardize and integrate

• Define and enforce metadata standards and taxonomy for the most valuable asset types.
• Map the integration landscape: prioritize connectors that remove the biggest manual handoffs (creative tools, CMS, PIM, analytics).
• Build modular automation for high-volume workflows: templating, derivatives, and publish pipelines.
• Expand governance into change control, permissions, and a basic AI policy that governs training data and allowed use cases.

6 to 12 months – scale and measure

• Roll out successful pilots with clear ROI measurements and case studies for leadership.
• Institutionalize metadata governance and data quality checks as part of onboarding and QA processes.
• Automate lifecycle management and rights enforcement across integrated systems.
• Invest in training and change management so people know how to use new workflows and understand limitations of AI.

Governance essentials for 2026

Good governance is the single most important control for reducing risk while unlocking AI and automation. The items below should be part of every DAM program roadmap.

• AI policy and use-case library: Define what AI will and will not be used for, who can approve models or tools, and how outputs will be validated.
• Metadata standards and ownership: Specify required fields, controlled vocabularies, and accountability for data quality.
• Permissions and access control: Apply least-privilege principles and review access periodically.
• Provenance and audit trails: Capture how assets were created, edited, and whether AI played a role in generation or transformation.
• Validation and human-in-the-loop: Require human sign-off for high-risk outputs and maintain a process for correcting model errors.
• Legal and compliance review: Align with IP, privacy, and upcoming transparency legislation related to AI and content authenticity.

Thinking about integrations – what belongs in DAM and what should be connected?

Deciding whether functionality should live natively in DAM or be integrated often comes down to three principles:

• Core competency: Keep capabilities in the system that provide the highest value per asset and are central to your content lifecycle — e.g., metadata, rights, versioning.
• Total cost of ownership: Integrations are not free. Consider ongoing maintenance, monitoring, and upgrades before committing.
• Experience and speed: If tight, seamless editing or template-based creation is required, native or deeply embedded tools may be preferable.

APIs, middleware, and integration platforms can bridge many gaps, but treat integrations like long-term investments. They require monitoring, governance, and periodic rework as downstream systems change.

How to make a business case for investment

Funding and staffing constraints are a primary blocker for progress. A practical business case speaks the language of leadership: risk reduction, revenue enablement, and cost avoidance.

• Start with a high-value pilot: Choose a use case that will clearly show time saved, cost reduction, or increased revenue (for example, faster campaign launches due to automated asset prep).
• Quantify the problem: Document how many hours are spent on manual tagging, approvals, or asset hunting and the impact on campaign velocity.
• Translate benefits into dollars: Use FTE hours, error avoidance, and time-to-market improvements to create a 12-month ROI projection.
• Document risk mitigation: Explain how governance, staging environments, and human validation reduce legal and brand risk from AI outputs.
• Present a staged investment plan: Leaders prefer phased spending tied to measurable outcomes rather than open-ended asks.

Recommendations for vendors and platform teams

Practitioners want vendors to meet them where they are. Key vendor responsibilities include:

• Robust integration capabilities: Provide well-documented APIs, pre-built connectors, and guidance for common enterprise ecosystems.
• Metadata-first designs: Tools should make metadata capture easy and useful by integrating it into workflows rather than as a separate admin task.
• Explainable AI features: Offer transparent models, confidence scores, and tools to validate and correct outputs.
• Governance tooling: Native support for permissions, audit logging, version control, and provenance tagging.
• Real-world case studies: Share practical examples with measurable outcomes so teams can understand applicability and limitations.

Advice for organizations implementing their first DAM

For teams building DAM 1.0 in 2026, the environment can feel both exciting and overwhelming. A few practical rules-of-thumb:

• Focus on outcomes: Define two or three business problems the DAM must solve first. Avoid trying to solve every use case at launch.
• Keep metadata simple at first: Start with required fields for discovery and rights, then iterate.
• Design for change: Expect the ecosystem to evolve; choose flexible models and modular integrations.
• Resist premature automation: Do not hand over critical quality decisions to AI until you have stable metadata and validation processes.
• Invest in training: People matter. Plan for change management so users adopt workflows and standards.

Content authenticity and upcoming regulation

Practitioners should watch content authenticity trends closely. Transparency requirements and AI-related legislation are advancing in several markets. Organizations will increasingly need to track when content has been generated or altered by AI, who approved it, and what data or models were used.

Documenting provenance and maintaining audit trails will reduce legal and reputation risk and will soon be a core expectation rather than a nice-to-have.

Closing thoughts: design and discipline win

Success for DAM in 2026 will come down to two simple, underappreciated things: design and discipline. Design means thinking about content flows, audience needs, and how assets are used end-to-end. Discipline means governing metadata, enforcing standards, and committing to maintenance of integrations and automations.

If the pressure to adopt AI becomes the lever that finally funds metadata, governance, and integration work, then the hype will have served a useful role. But it will only happen if leadership is aligned, budgets are targeted, and teams follow a staged, measurable approach.

The immediate action for any DAM leader is to stop treating AI as a magic fix. Treat it as a capability that multiplies value when you have clean data, clear policies, and human oversight in place. Start small, document outcomes, and use evidence to build momentum for larger investments.

2026 is an inflection point. For teams that pair ambition with fundamentals, DAM can become the operating platform content organizations need. For those who rush ahead without the basics, the result will be more noise and risk. Design deliberately. Govern consistently. Measure everything.

The Interline Interview with Kara: How DAM Delivers on the Promises of DPC

3D and Digital Product Creation (DPC) have moved past the “should we?” phase, but many fashion and beauty companies are now asking a tougher question: how far should we really take these initiatives, and what do we need in place for them to pay off? In this excerpt from The Interline DPC Report 2026, AVP Partner & Managing Director Kara Van Malssen argues that the answer isn’t simply “more 3D.” It’s building the connective tissue that makes 3D usable at scale: digital asset management (DAM).

In this interview, Kara breaks down what DAM actually is (a practice, not just software), why it’s increasingly critical upstream in the product lifecycle, and how it unlocks real ROI by reducing rework, improving version confidence, and turning reusable components (materials, trims, meshes, renders) into a trustworthy library teams can actually find and use. If you’re navigating tool sprawl across design, PLM/PIM, and 3D platforms or feeling the drag of duplicated files, scattered storage, and “where is the latest version?” chaos, this is a practical framework for what to fix first, and why.

Download the full article to get the complete perspective, the DAM operational model, and the clearest decision matrix for where DAM (and 3D) belong in your DPC ecosystem.

The DAM AI Gap Is Real. Here’s How to Close It.

The fastest way to tell if your DAM is (un)healthy is to turn on AI.

Because AI does not just make DAM smarter. It makes your DAM’s foundations visible. When the fundamentals are strong, AI accelerates what is already working. When the fundamentals are weak, AI amplifies inconsistency, risk, and cleanup work.

That matters because organizations are being asked to do more with less, and AI has become the default answer. DAM is no longer expected to be a repository. It’s expected to orchestrate content operations, reduce friction, and scale output. But without consistent metadata, clear governance, and operational control, AI can’t deliver that promise. It amplifies whatever is already true in your DAM, including gaps.

AI is proliferating across the DAM ecosystem. Vendors and DAM-adjacent platforms are shipping automated metadata creation, natural language search, and agentic AI at an unprecedented pace. Leaders within organizations are being told to expect dramatic gains in efficiency, automation, and discoverability, often framed as the fastest path to doing more with less.

But a consistent reality is showing up across organizations: many do not yet have the foundations, funding, or control required to leverage AI safely and effectively.

This is what I’m calling the DAM AI Gap: the disconnect between what AI promises and what most DAM programs are actually ready to operationalize.

If you are not seeing results from your DAM or early AI initiatives, it is likely not a technology problem. It is a foundation problem.

The good news is that this gap is solvable and often faster to address than leaders expect when the work is approached with the right experience and a clear path.

The Gap

The pattern is straightforward. Market innovation is moving faster than organizational readiness. Advanced AI capabilities assume a level of maturity that many DAM programs have not yet achieved. Most organizations are still constrained by fundamentals:

• Inconsistent or missing metadata
• Weak or unclear governance and ownership
• No taxonomy or competing taxonomies
• Fragile workflows and uneven adoption
• Half-baked integrations that keep content scattered across systems and shared drives
• Disorganized ecosystem

The ambition is DAM as a system of action, not storage. The reality is uneven data quality, under-resourced teams, and unclear control points. The risk is that AI and automation amplify weakness rather than resolve it.

AI does not replace DAM fundamentals, it depends on them. When the underlying structures are not in place, AI-driven features often create new failure modes. Improved discoverability without strong permissions and rights management can expose content to the wrong audiences.

Automation without oversight can scale mistakes faster than teams can catch them. AI layered onto fragile governance can create noise and unpredictability, which erodes trust and adoption.

In our 2026 DAM Trends survey, the tension was clear: the vision is compelling, but the fear is being pushed to move faster than governance, data quality, and operational control can support.

Most organizations are operating under sustained efficiency pressure. DAM, marketing operations, and content operations teams are being asked to deliver more impact with constrained capacity while also adopting new AI-driven capabilities.

In that environment, the foundational work AI requires is often the first work deferred. Metadata models, taxonomy decisions, governance structures, rights and permission frameworks, workflow integrity, integration design, enablement and operational ownership are hard to prioritize when teams are stretched.

The result is predictable: the organization invests in AI and automation expecting speed and savings, but experiences more cleanup work, higher risk exposure, and slower adoption. Not because the technology failed, but because the operating foundation was never built to support it and accordingly there were unreal expectations of what AI could do.

This is not a story about resistance to change. It is a story about organizations knowing what DAM needs to become and being acutely aware of what can go wrong if they try to get there without fixing the fundamentals.

Closing the Gap and Delivering on the Promise of AI

At AVP, we embrace the potential of AI, but our stance is grounded in truth and readiness.

AI can amplify DAM value, but only when the foundations are sound. If you want to unlock the power of AI, you have to get the foundation in place first. Much of that foundation is what we define as the DAM Operational Model: the operating system that makes DAM sustainable and scalable across people, process, governance, and technology (Learn more about that here.)

Without it, AI becomes another layer of activity on top of instability, rather than a multiplier of value.

This includes things like:

• A metadata model and taxonomy aligned to how the business finds, governs, and uses content
• Clear governance, ownership, and operating mechanisms that sustain quality over time
• Permissions, rights management, and policy controls that protect the organization as discoverability improves
• Workflows and practices that scale across teams and regions
• Integrations that support end-to-end operations, not isolated repositories
  

When these fundamentals are in place, the outcomes leaders are looking for become achievable:

• AI works as intended
• Automation becomes reliable
• Rights and intellectual property are protected
• Workflows scale and cycle times drop
• Adoption increases because teams trust the system
• ROI becomes visible and defensible

If your organization is under pressure to move faster with AI, the highest-leverage move is to treat DAM fundamentals as an executive-level capability, not an operational nice-to-have.

That framing also gives DAM practitioners the language they need internally: the work is not “cleanup.” It is risk mitigation, preparedness, efficiency enablement, and value realization. The goal is not to slow down AI. The goal is to make AI safe and effective.

AVP helps organizations close the DAM AI Gap by building the foundation required to make AI safe, scalable, and ROI-driving. We provide the expertise and capacity to:

• Build or rebuild taxonomy and metadata structures
• Establish governance, permissions, and rights management
• Fix workflow and operational bottlenecks
• Stabilize underperforming DAM environments
• Support lean or capacity-constrained teams
• Integrate AI safely and effectively

If you are not seeing the results you expected from DAM or early AI initiatives, start with readiness. Close the foundational gaps that determine whether AI becomes a multiplier or a liability.

Work with AVP to build the DAM foundation that enables safe deployment, scalable operations, and defensible ROI.

DAM delivers on the promise of AI. AVP delivers on the promise of DAM.

Let us know how we can help you.

Trust, Authenticity & Governance for the AI Age

Trust is hard to come by.

Eminem

Technology succeeds when it is leveraged to transform data into information and then information into insight that can then generate action and meaning. Collective actions build mutual trust among community members, establishing knowledge-sharing opportunities, lowering transaction costs, resolving conflicts, and creating greater coherence. Trust sets expectations for positive future interactions and encourages participation with technology. Communicating the meaning and purpose of why a technology tool is being used will build trust with its audience and impact positive experiences. Trust in technology and the data flowing through all connected systems will lead to greater participation that will increase information’s value and utility. But is artificial intelligence (AI) in our content, our documentation, and our marketing information is making this all the messier and more complicated? The question is, do we trust what we see and read? 

AI as an energetic force for change in our modern business content systems such as a DAM, PIM, CMS, and e-Commerce will accelerate the conversation between business and consumer. All the integration and interconnectivity between business applications strengthens the argument for strong and authoritative metadata, and for effective workflow management. Businesses creating and disseminating brand and marketing messages and products will engage with the consumer community who will respond with shopping behavior, internet searches, assets, and data such as reviews, comments, images, check-ins and other online actions. Data serving content as a connection between people, process, and technology.

Furthermore, understanding the needs of users and showing transparency in the technology, the people and the process will improve the experience and start the path to building trust. And yet, trust is hard to come by because there is not enough of it in our data. It’s no surprise that some of the biggest and most vocal critics of AI are artists themselves, the creators, those who create from an original and inspired source. 

“I hate AI … AI is the world’s most expensive and energy-intensive plagiarism machine. I think they’re selling a bag of vapor.” – Vince Gilligan

“People ask if I’m worried about artificial intelligence, I say I’m worried about natural stupidity?” – Guillermo del Toro

And we are beginning to see more criticism from the creative community of AI being used in marketing the most recent of which is the negative feedback on Coca-Cola’s 2025 Christmas ad which follows criticism of their 2024 efforts. This in tandem with the persistence of “AI hallucinations” gives us all reason to pause and query where the trust and authenticity is in our content. Should consumers be skeptical … yes, but if we start to “distrust” what we see, then uncertainty creeps into the relationship. A 2024 study by Bynder found that when posts sound AI-written, 25% of people think the brand feels impersonal, and others flat-out call it lazy. Trust is getting harder to come by in a world filled more with hyperbole than facts, precision and nuance.

Let’s get some definitions out of the way to help both ground and illuminate this discussion:

Authenticity – The trustworthiness of a record as a record, i.e., the quality of a record that is what it purports to be and that is free from tampering or corruption.

Provenance – The origin or source of something. Information regarding the origins, custody, and ownership of an item or collection.

Integrity – The quality of being honest and having strong moral principles; of being whole and complete.

Data Integrity – The property that data has not been altered in an unauthorized manner; in storage, during processing, and while in transit.

What’s your data-driven AI strategy? We want the data and the machines managing it to learn and do more, but we must provide them with good, quality data for them to do that. Good data = smart data = good learning = happy customers. But if the data delivered does not match the user expectations, then the efficiencies of a personalized, and meaningful consumer experience are lost. Do we trust what we see and read? Data is the foundation for all that organizations do in business and how they interact with their customers. Data is proliferating, and that growth is only going to continue exponentially. As it multiplies, organizations need refreshed, enterprise-level approaches to systematically create, distribute, and manage data for your brand and your customers. Is authentic, accurate, and authoritative data the foundation to help us navigate the digital age? 

Information Integrity

“Transparency builds trust.”

Denise Morrison

Data provides the link allowing processes and technology to be optimized. But if the data delivered does not match the user expectations of accuracy and authenticity, trust may be lost. Trust may not always be built with consistency if the facts are not always there. Be mindful of the current situation and the challenges faced. More importantly, be mindful of the people, processes, and technologies that may influence transformation. Information, IP and content are critical to business operations; they need to be managed at all points of a digital life cycle. Trust and certainty that data is accurate and usable is critical. Leveraging meaningful metadata in contextualizing, categorizing and accounting for data provides the best chance for its return on investment. The digital experience for users will be defined by their ability to identify, discover, and experience an organization’s brand just as the organization has intended. 

Integrity of information means it can be trusted as authentic and current. When content is allowed to move freely, the chain of custody can be lost, undermining trust that the information is original. By establishing rules around originality and custodianship, or document ownership, content can be relied on as the “single source of truth,” and there may well be more than one source of truth, for it is authenticity we seek. As an example, if we define content as something that has value to the organization, then controls should be placed on access to that content. If controls are not in place, or they are insufficient, then the consequences can be embarrassing and costly. Possible dangers might include having the company sustain damage to its reputation, or it could result in the loss of trust of clients or consumers.

History teaches us that the study of “Diplomatics” in Archival Studies, posits that a document is authentic when it is what it claims to be. The Society of American Archivists (SAA) definition reads, “The study of the creation, form, and transmission of records, and their relationship to the facts represented in them and to their creator, in order to identify, evaluate, and communicate their nature and authenticity.” And, with that definition comes arguably its greatest modern proponent of Diplomatics, Luciana Duranti, reminds us to be mindful of, “the persons, the concepts of function, competence, and responsibility” must all be considered when considering digital assets and trust, from creation to distribution. Trust in content created with authority, authenticity, and responsibility. 

Governance is No Longer an Option

Governance is the process that holds your organization’s data operations together as you seek to become truly data-driven, realize the full value of your data and content, and avoid costly missteps. To be effective, governance must be considered as a holistic corporate objective establishing policies, procedures, and training for the management of data across the organization and at all levels. Without governance, opportunities to leverage enterprise data and ultimately your content to respond to new opportunities may be lost. By developing a project charter, working committee, and timelines, governance becomes an ongoing practice to deliver ROI, innovation, and sustained success. While technology is important, culture will prevail, for Governance is more than just “change management”. Governance demands a cultural presence and footprint. The best way to plan for change is to apply an effective layer of governance to your program. 

In his autobiography, Permanent Record, Edward Snowden argues that “Technology doesn’t have a Hippocratic oath. So many decisions that have been made by technologists in academia, industry, the military, and government since at least the Industrial Revolution have been made based on ‘can we,’ not ‘should we.” Another example of governance is needed is reflected in the advice of moving away from the brash work ethic of “move fast and break things,” from millennial technobrat and Cambridge Analytica whistleblower Christopher Wylie, who argues for a “building code for the internet” and a “code of ethics”—in essence, regulations to prevent the technological atrocities of the past. Governance is about the ability to enable strategic alignment, to facilitate change, and maintain structure amidst the perceived chaos. 

Good governance delivers innovation and sustained success by building collaborative opportunities and participation from all levels of the organization. The more success you have in getting executives involved in the big decisions, keeping them talking about AI making this a regular, operational discussion (not just for project approval or yearly budget reviews), the greater the benefits your organization will have. Participation from all levels of the organization is key. Engaging the leadership by involving them in the big decisions, holding regular reviews and keeping them talking about DAM or any content management system, will yield the greatest benefits. 

Opportunities to Provide Authenticity

From a legal point of view, there is some hope for the future as new legislation regarding AI creation and usage does take into account issues of “transparency” and “provenance,” most notably in the new California Transparency Act (AB 853) (SB 942), and the Transparency in Frontier Artificial Intelligence Act (TFAIA) all coming into effect in 2026, with the EU Artificial Intelligence Act been in place since 2024. 

From a practical point of view, there are some things we as digital creators and managers of content may do: 

1. C2PA, Coalition for Content Provenance and Authenticity, provides an open technical standard for publishers, creators and consumers to establish the origin and edits of digital content at the metadata level. This also includes Content Credentials to leave a metadata audit trail for your digital assets (e.g. date, time, and location of creation, along with a digital signature to prove authenticity)

2. Employ embedded digital signatures and watermarking. 

3. Implement AI detection to identify if an image, video, or audio file has been altered or generated by AI.

4. Quality control and data verification on a regular basis throughout the digital asset life cycle to ensure content came from trusted and authorized sources.

5. Governance as an organizational process to mitigate risk and to achieve your goals. 

Amidst the clash and clatter of AI it is good to know there are real tangible things you can start doing to use people, process, technology and data to navigate this complex environment. 

Conclusion

Good, trusted, authentic data is critical to AI; trust and certainty that the data is accurate and usable is critical for success. And be mindful of the people, processes, and technologies that may influence data and learning within business. Data will only continue to grow. There has never been a more important time to make data a priority and to have a road map for delivering value   from it. AI provides great opportunities for communication, engagement, and risk management. Data sharing and collaboration will play an important part in growth, as business rules and policies will govern the ability to collect and analyze internal and external data. More importantly, business rules will govern an organization’s ability to generate knowledge—and ultimately value. To deliver on its promise, data must be delivered consistently, with standard definitions, and organizations must have the ability to reconcile data models from different systems.

A call to action … may we all just slow down. Simple, and effective. Yes, AI is incredible and powerful and advancing at a fast pace, which is exactly why we need to slow down as best as we can. Remember to evaluate your trusted sources of information and evaluate what you are reading. Trust may not always be built with consistency if the facts are not always there. Be mindful of the current situation and the challenges faced. More importantly, be mindful of the people, processes, and technologies that may influence transformation. Information, IP and content are critical to business operations; they need to be managed at all points of a digital life cycle. Trust and certainty that data is accurate and usable is critical. Leveraging meaningful metadata in contextualizing, categorizing and accounting for data provides the best chance for its return on investment. The digital experience for users will be defined by their ability to identify, discover, and experience an organization’s brand just as the organization has intended.

While metadata may help us find the facts needed for that truth, governance is the structure around how organizations manage content creation, use, and distribution and a critical part to developing trust. Ultimately, governance is the structure enabling content stewardship, beginning with metadata and workflow strategy, policy development, and more, and technology solutions to serve the creation, use, and distribution of content. Content does not emerge fully formed into the world. It is products of people working with technology in the execution of a process… the transparency needed for content to be authoritative, authentic, and all willing, responsible. Trust may be built through transparency and quality data, and trust may be earned through good governance; your brand depends upon it.

Citations

1. https://variety.com/2025/tv/news/pluribus-explained-vince-gilligan-rhea-seehorn-1236571666
2.  https://www.hollywoodreporter.com/movies/movie-news/guillermo-del-toro-not-worried-artificial-intelligence-1235585785/
3.  https://www.creativebloq.com/design/advertising/what-brands-can-learn-from-coca-colas-terrible-ai-christmas-ad
4.  https://www.bynder.com/en/press-media/ai-vs-human-made-content-study/
5.  https://interparestrustai.org/terminology/term/authenticity
6.  https://dictionary.archivists.org/entry/provenance.html
7.  https://dictionary.cambridge.org/us/dictionary/english/integrity
8.  https://csrc.nist.gov/glossary/term/data_integrity
9.  https://calmatters.digitaldemocracy.org/bills/ca_202520260ab853
10.  https://calmatters.digitaldemocracy.org/bills/ca_202320240sb942
11. https://www.gov.ca.gov/2025/09/29/governor-newsom-signs-sb-53-advancing-californias-world-leading-artificial-intelligence-industry/
12.  https://artificialintelligenceact.eu/
    
    
    
    
    
    
    
    
    

Choosing a DAM System: A 10-Point Framework for the Final Decision

After months of evaluating platforms, the moment has arrived: it’s time to make a decision on your digital asset management (DAM) system. Your choice will shape how your teams access, manage, and use content for years. Our goal is to help you move forward with confidence.

We assume you’ve already done the necessary legwork: aligning stakeholders, identifying requirements, evaluating right-fit vendors, and running demos and a POC tailored to your assets and workflows. If not, consider revisiting those steps—take a look at our previous posts in this series.

Reconnect with Your Digital Asset Management System Goals

Before comparing feature lists or pricing tables, revisit why you began this process. What problems are you trying to solve? What does success look like a year from now? Make sure your final decision is rooted in those goals. Your task is to choose the digital asset management system that best supports your organization, not just the one with the flashiest interface.

Evaluate DAM Vendors Using a Structured Framework

A decision of this magnitude benefits from objectivity. Using a structured scoring model or decision matrix can help your team make a transparent, evidence-based selection. This approach allows you to evaluate each platform against consistent criteria, assign weights based on your priorities, and compare options side by side. It also creates documentation that supports internal alignment and future reference.

Ten Dimensions to Evaluate Each Digital Asset Management System Vendor Finalist:

1. Value

Does the platform deliver the functionality you need? Does it offer capabilities that significantly improve how your organization produces, manages, and shares content? Focus on alignment with your current and future needs, not the total number of features.

2. Feasibility

Can you implement and maintain the platform with your available resources? Consider implementation effort, integration complexity, and ongoing management. A great-looking system may require infrastructure or capacity you don’t currently have.

3. Usability

How easy is the system for different user groups—admins, content creators, and end users? If these groups weren’t included in demos, or didn’t participate in a proof of concept, go back a step. Be sure to get input from the people who will be affected most. Don’t forget to test admin functionality too.

4. Affordability

Is the pricing model sustainable? In addition to license fees, consider implementation (including integration and migration), training, support, storage, and feature add-ons. Don’t forget to look at the cost of utilizing AI services, too. We recommend projecting costs over at least three years to get a clear picture of the price.

5. Scalability

Will the platform grow with you? Think about asset volume, metadata complexity, user numbers, and geographic spread. If you have a particularly large collection or number of users, ask the vendors what their largest deployments are. Review whether the vendor’s roadmap aligns with your growth trajectory.

6. Security & Compliance

Does the platform meet your organization’s security and compliance requirements? Evaluate encryption, access controls, audit trails, and alignment with standards like GDPR or SOC 2. Consider both technical and policy aspects.

7. Ecosystem Fit

How well does the platform integrate with your current systems? Assess APIs, connectors, plugin availability, and the vendor’s experience with relevant third-party tools. Custom integration can quickly become a significant area of cost and complexity, so look for vendors that plug-in to your ecosystem easily.

8. Social Proof

Have similar organizations (in industry, size, scale, complexity) adopted this platform successfully? Are they growing with it over time? Review case studies, references, and testimonials. Speak directly with current customers to learn about the vendor’s strengths and limitations.

9. Trust

Does the vendor seem like a reliable long-term partner? Look at financial stability, delivery track record, and support reputation. Review SLAs, support channels, and upgrade policies. You’ll get great insights when you speak to other customers.

10. Exit Path

If your needs change, can you move on easily? Ask vendors how they support full export of assets, metadata, vocabularies, and user data in open formats. Understand the terms and costs of a potential exit.

Assign Weights and Score Objectively

Not all criteria carry the same weight. A nonprofit with limited IT support may prioritize feasibility and security, while a global brand may focus on integration and scalability. Assign weights to reflect your priorities, then score each option accordingly.

Final DAM evaluation using weighted scoring

Include a cross-functional team in the process to reflect diverse perspectives and build alignment. Document your evaluation so you can refer back to it as needed.

Avoid Common Final-Decision Pitfalls

Even with a strong evaluation process, watch out for these missteps:

• Letting brand recognition or peer adoption sway your decision
• Letting cost outweigh actual needs
• Underestimating implementation, integration, and migration effort
• Failing to thoroughly vet vendor support and services

Get Internal Buy-In and Document the Decision

Before finalizing, make sure all key stakeholders are aligned. Review the decision rationale with leadership, legal, procurement, and IT to surface any final concerns. And as a reminder, don’t forget to talk to your chosen vendor’s current customers (and not just the ones they suggest you talk to!)

Document your decision, including priorities and tradeoffs. This record will be valuable during implementation and future reviews.

Final Thoughts

Selecting a DAM system is more than a software purchase. It’s a strategic decision that will shape how your organization manages content for years. Use comprehensive evaluation criteria and a collaborative process to choose with confidence.

When implementation begins, you’ll be glad you did.

Digital Asset Management Demos and Proof of Concepts

Digital asset management demos and POCs are where things get real. A demo is a live, guided walkthrough of your specific usage scenarios—ideally using your actual assets. A proof of concept (POC) goes further, giving your team hands-on access to test how the system performs with real workflows. Together, they offer a grounded, honest look at whether a system fits, not just how it looks in a sales deck.

A structured, goal-driven approach to managing these activities is the best way to move from feature lists to informed decisions.

Before the Demo: Set Your Foundation

Start by defining what matters most to your organization. Common areas to evaluate in a DAM system include:

• Workflow automation
• Metadata structure and taxonomy
• Permissions and user roles
• Search and discovery
• Upload and download processes
• User interface and experience (UI/UX)
• Integrations with other systems (e.g., CMS, PIM, MAM)

Also consider what makes your organization unique. Do you manage large volumes of high-resolution images, video, or audio (rich media)? Do you need to preserve or migrate older, inconsistent, or incomplete metadata (often referred to as legacy metadata)? These factors should inform the usage scenarios you ask vendors to demonstrate or support during a proof of concept (POC).

If you haven’t created usage scenarios yet, now’s the time. A usage scenario is a short, structured description of a key task a user needs to perform in the system. Each should include:

• A clear title
• The goal or objective
• The user role
• A brief narrative of the scenario
• Success criteria

Aim for 6 to 8 scenarios that reflect your core needs across different user types. A focused set like this keeps digital asset management demos and POCs grounded in what really matters to your team and ensures a more meaningful evaluation.

Preparing for the Demo

Give vendors a chance to show how their system handles your real-world needs. Ask them to walk through 4–5 key tasks your users need to perform in a two-hour demo session.

About two weeks before the demo, send each vendor a small sample of your actual content—around 25 assets in a mix of file types and sizes—along with a simple spreadsheet describing those files (titles, descriptions, dates, etc.). If you work with items made up of multiple files (like a book with individual page scans), include one or two of those as well.

The goal is to see how the system performs with your materials—not polished demo content—so you can better understand how it might work for your team.

Digital Asset Management Demo Participation and Structure

Invite a diverse group:

• Core users
• Edge users with atypical needs
• Technical staff
• Decision-makers

Suggested agenda:

• 30 minutes – Slide-based intro and vendor context
• 60 minutes – Live walkthrough of your usage scenarios
• 30 minutes – Open Q&A

Distribute a feedback form before the demo so your teams can rate the system and each usage scenario in real time. Collect quantitative scores (e.g., “On a scale of 1–5, how well did the system support this scenario?”) to make it easier to compare vendors side by side. Include a few qualitative prompts as well, such as “What surprised you?” or “What did you like or find confusing?” Keep the form short and focused—if it’s too long, people won’t fill it out.

Running the POC

Once you’ve identified a finalist, it’s time for hands-on testing. A two-week POC is ideal—short enough to keep momentum, long enough to explore.

Set expectations upfront. Testers must dedicate focused time. The POC isn’t a background task. If people delay or casually click around, you won’t get meaningful results.

Check with the vendor about potential POC costs. Some vendors charge if their team invests heavily and you don’t purchase. Ask early.

Prepare for a successful POC:

• Give vendors ~3 weeks to configure the system with your content and workflows. Share usage scenarios and access needs early.
• Assign clear roles, for example:
  • End Users – Test search, discovery, and downloads
  • Creators – Test uploads, tagging, and editing metadata
  • Admins – Test permissions, structure, workflows, and configuration
• Create a task-based script aligned with your usage scenarios. Ask testers to log their experience, pain points, and surprises.
• Schedule three vendor touchpoints:
  • Kickoff (60 min):  Introduce the vendor, ensure everyone has access, clarify roles, and walk through the POC goals and script.
  • Midpoint Check-in (30 min):  Surface blockers or confusion while there’s still time to fix them. Encourage open questions: “How do I…?” or “Why isn’t this working?”
  • Wrap-up (30 min): Review what worked and what didn’t. Ask the vendor to walk through anything missed. Preview post-purchase support and onboarding to help gauge confidence in next steps.

Reminder: This is not a sandbox. Stick to the script, test with intention, and focus on how the system performs in a real working scenario.

Decision Making

Pull your team together while the experience is still fresh.

Start with the structured feedback:

• Compare rubric scores across categories like usability, metadata, permissions, and admin tools.
• Look for patterns or outliers: did some roles struggle more than others?
• Discuss gaps, friction points, and what’s non-negotiable.

If your group is large, collect final thoughts via a form and summarize for review.

Document your decision—not just which system you chose, but why. Connect it to your business goals, priorities, and user needs. This not only strengthens your recommendation, but also provides valuable context for onboarding new users and teams. When people understand the reasons behind the choice, they’re more likely to engage with the system and use it effectively. It also gives you a foundation for measuring success after launch.

Final Thoughts

Digital asset management demos and POCs don’t just validate vendor claims, they clarify your priorities, surface assumptions, and test how ready your team is for change. They help you figure out not just if a system works, but how it works for you.

A well-run process builds alignment, fosters engagement, and reduces risk by exposing critical gaps early. Most importantly, it sets the stage for a smoother implementation.

When you choose a system based on real tasks, real users, and real feedback, you’re not just buying software. You’re investing with confidence.

Next Article:

Making the Final Decision on a Digital Asset Management System

Go to the article

Conducting Market Research and Shortlisting Digital Asset Management Vendors

Choosing a Digital Asset Management (DAM) system is one of the most critical decisions an organization can make for managing digital content. But diving into the DAM market without guidance can be overwhelming. Dozens of vendors offer similar feature sets, and without a clear plan, it’s easy to get lost in marketing jargon or swayed by a sleek demo that doesn’t reflect your real-world needs.

This process isn’t just about picking a product. It’s about starting a long-term relationship with a vendor who will support your team, evolve with your workflows, and play a role in your digital strategy. That’s why thoughtful market research and intentional shortlisting are essential.

Begin with Requirements, Not Features

Effective vendor research starts with clarity about your needs. Before browsing solutions, define what your organization actually requires from a DAM platform. Consider:

• Who your primary users are and what they need to do with assets
• What types of assets you manage (images, video, audio, documents)
• Metadata standards and requirements
• Integration needs (CMS, PLM, PIM, creative tools, cloud storage, preservation)
• Permission models and access control
• Reporting, analytics, and training needs

List “must-have” and “nice-to-have” features, then use that as your rubric. This helps you stay focused on what matters and avoid shiny features that don’t advance your goals.

Navigating the Digital Asset Management Marketplace

A web search is a fine place to start, but it’s not enough. Vendor websites offer a polished view, but few provide meaningful detail about true differentiators, limitations, or ideal usage scenarios.

Sites like G2, Trustpilot, and Capterra offer user-generated reviews and side-by-side comparisons, which can be helpful for spotting trends or potential red flags. That said, be aware that many listings are paid placements, and reviews often lean toward the extremes—either very positive or very negative. Also, many of the tools listed on these sites aren’t actually full-featured DAM systems. Some, like Canva or Airtable, offer DAM-like features but may not meet the broader needs of your organization. This can make it tricky to distinguish between tools that support part of the workflow and those that can truly serve as a centralized DAM solution.

For deeper and more balanced insight, explore:

• DAM News – Offers industry-specific news, vendor updates, and interviews with practitioners.
• CMSWire – Covers a range of digital workplace topics, including strong, up-to-date content on DAM.
• LinkedIn – A powerful resource where DAM professionals share real-world insights, lessons learned, and vendor experiences. Connect with industry peers who have already implemented a DAM and ask for honest feedback and recommendations.

Research Firms & Case Studies

• Reports from Gartner, Forrester, and Real Story Group provide in-depth vendor evaluations and market analysis. (You can typically find these linked from vendor websites.)
• Seek out case studies from vendor websites to understand how specific solutions perform in real-world contexts.

Industry Events

Consider attending a Henry Stewart DAM Conference, which gathers DAM professionals and vendors for learning and networking. These take place annually in:

• London (June)
• New York City (October)
• Sydney (November)
• Los Angeles (March)

These events offer an opportunity to demo different systems and meet digital asset management vendors in person, expert panels, and the opportunity to hear directly from other organizations about their selection and implementation journeys.

Learn from Peers, with Context

Colleagues can be a great source of insight. Ask what systems they use, what worked well or poorly, and what they’d do differently. These conversations reveal how vendors behave during implementation and long-term support.

But keep in mind: a DAM that works well for your pal over at their organization may not be right for you. Your users, workflows, and digital strategy are unique. A negative experience elsewhere might reflect poor alignment rather than a flawed system. Treat peer feedback as helpful context, not universal truth.

Consult the Experts

If you lack time or in-house expertise, consider hiring a DAM consultant. Specialists know the landscape, can translate your needs into actionable requirements, and can help you run a disciplined selection process. They can also facilitate internal conversations neutrally to surface user needs and pain points, ensuring decisions are informed by real requirements and aligned with strategic goals.

Digging into DAM Differentiators

Most DAMs claim to offer robust features—AI, metadata support, flexible permissions, and more. These terms sound impressive, but they rarely reveal how the system actually works in practice. Real differentiators are found in the details across all functionality areas.

For example:

• “AI” alone isn’t helpful. One platform might offer basic auto-tagging, another facial recognition, or full generative AI descriptions and AI-driven workflows tied to metadata.
• “Controlled vocabularies” are standard. A system with the ability to support complex taxonomies, multilingual thesauri, or ontology integration might stand out if this is what your organization need.
• “Permissions” are expected. Granular controls, field-level restrictions, and automated rights management are worth noting.

Ask vendors for documentation that shows actual configuration options, not just marketing overviews. In demos, go beyond checklists. Ask how it performs at scale, supports your asset types, and adapts to real-world workflows. If you don’t push, vendors may not volunteer specifics.

Engage Digital Asset Management Vendors with Purpose

Once you reach out to digital asset management vendors, you’re signaling interest. Sales reps will follow up. That’s expected. Many will work hard to win your business, and that can be a good thing. But this isn’t just a sales transaction. If you choose their system, you’ll likely be working closely with that company for years.

Pay attention to how vendors engage with you. Do they ask thoughtful questions about your needs? Offer strategic guidance? Or are they focused only on closing the deal? You want a partner, not just a product.

Ask tough, specific questions. Request use-case examples. Involve your users early so they can determine if the system fits their actual workflows.

Early demos can help you understand layout and navigation. But once you’re seriously considering a system, ask for tailored demonstrations using your scenarios and assets. This helps you evaluate both product fit and vendor fit—their responsiveness, flexibility, and support philosophy. And if you really want to get under the hood, consider doing a proof of concept with your top 1-2 finalist vendors.

Building the Shortlist

A shortlist should include only those digital asset management vendors who align with your requirements, fall within your budget, and seem like a cultural fit. Aim for five to six vendors for your Request for Information (RFI) or Request for Proposal (RFP).

After reviewing the vendors’ responses, narrow the list to two or three finalists. Invite them for detailed demos, reference calls, and technical Q&A. Note that at this point, you’re evaluating the partnership as much as the platform.

What Makes Digital Asset Management Vendors Shortlist-Worthy

A vendor becomes shortlist-worthy not just by meeting your technical and functional requirements, but by demonstrating alignment with your organization’s broader context and strategic direction. Beyond feature fit, consider factors like company size and funding stability—these can indicate whether a vendor is likely to support and evolve their platform over the long term. Geographic location may matter for support hours, data residency, or language requirements. Longevity and client retention can signal maturity and reliability, but don’t discount newer vendors if they show strong responsiveness and innovation. Experience within your industry or with similar organizations can also be a valuable indicator of how well the vendor understands your needs and challenges. Most importantly, assess cultural and strategic fit: does the vendor listen actively, offer thoughtful insights, and seem invested in your success? A good partner should feel like an extension of your team, not just a service provider.

Final Thoughts

DAM market research is both a filtering and discovery process. It takes effort, but the payoff is a well-aligned solution that fits your organization and your future.

Stay focused on your goals. Be curious, but critical. Ask hard questions. A solid selection process sets you up for long-term success—not just with the tool, but with the vendor team that supports it and the users who rely on it every day.

Next Article:

Issuing and Evaluating RFPs for DAM Solutions

Go to next article

Assessing Your Organization’s Digital Asset Management Needs

Choosing a Digital Asset Management (DAM) system is a high-stakes process, but it can also be energizing and collaborative when done right. Whether you’re replacing a legacy system or starting from scratch, the first step is understanding what people need. This means listening carefully, mapping what’s working and what’s not, and building shared enthusiasm for what a DAM can unlock.

Start with People

The foundation of this work is people. Find them, talk with them, and the rest will start to fall into place. Before you dive into features or vendors, start with people. A DAM system’s success depends on the constituency that uses and supports it, so identifying and engaging the right voices is essential.

Who makes or uses the digital assets?

Think broadly about anyone who creates, manages, approves, uses, or delivers digital assets. That might include:

• Content creators, designers, and editors
• Marketing and communications teams
• Archivists and records managers
• Product or project managers
• IT and security staff
• Legal, compliance, and risk officers
• Executive sponsors and decision-makers
• Funders or departments responsible for system costs

To identify the right stakeholders, ask:

• Who touches assets from creation through to delivery and preservation?
• Who makes decisions about DAM staffing, training, and long-term support?
• How is the DAM currently funded—or how will it be funded in the future?

Start broad. As you engage people across roles and departments, a smaller group will naturally emerge with deeper involvement, insight, and decision-making responsibility. These are your core stakeholders—the people who will help shape the system and carry it forward.

Listen for Insights

Stakeholder input isn’t just helpful—it’s essential. These conversations shape your goals, expose pain points, and clarify what your DAM needs to support. Engaging the right people early gives you a clearer view of how assets are really managed—and where the friction lives.

As you talk with them, don’t just focus on workflows. Ask about long-term support: Who will own the DAM? Is IT prepared to manage integrations, infrastructure, and security? Is there funding or staffing available to maintain governance, training, and standards? These questions are just as important as functional needs and should guide your assessment from the start.

Start with short, focused interviews. Skip surveys, which often yield surface-level feedback. Instead, speak one-on-one or in small groups. Record conversations (with permission) so you can revisit the details. Ask open-ended, practical questions like:

• What tools do you use to create, manage, or find digital assets?
• What do you wish were easier?
• What already works well?
• How do you handle rights or metadata?
• What slows you down or creates confusion?
• If you had a magic wand, what functionality would you ask for?

Pay attention to the language people use. It’s invaluable when you begin writing requirements or explaining priorities to vendors.

Organize and Prioritize What You’ve Learned

Once you’ve gathered enough feedback, use a simple rubric to organize and prioritize what you’ve learned. This helps you spot patterns, identify gaps, and guide planning. Assessment isn’t just a step toward a decision. It’s how you learn what success will require. It helps you see not only what’s broken but what’s working, what people hope for, and what you’ll need to prioritize.

Your assessment should help you answer:

• Where are the friction points in your asset lifecycle?
• What are the root causes of confusion, delays, or errors?
• What already works well and could be scaled?
• What would help your teams collaborate better or move faster?

A useful way to organize this thinking is with a simple rubric:

This high-level rubric helps turn qualitative insights into a shared understanding of your current landscape. It can surface high-impact gaps, clarify priorities, and serve as a foundation for your implementation roadmap or RFP.

Keep Listening, Keep Refining

At the heart of a successful DAM assessment are people—the users, decision-makers, and behind-the-scenes teams who rely on digital assets every day. Their insights are the source of your best ideas.

Information gathering isn’t a one-time process. Keep asking questions. Keep listening. As your understanding deepens, your priorities will evolve, and your system requirements will sharpen. The more inclusive and user-driven your approach, the more likely you are to select a DAM that meets your real needs and earns long-term support.

What may feel like a jumble of tools, frustrations, and hopes now will eventually turn into clear priorities, confident decisions, and, most importantly, a system that fits the way your organization actually works.

Focus the Vision for Your Digital Assets

With input from your stakeholders in hand, it’s time to define a shared vision for what the DAM is meant to accomplish. That vision comes to life through clear, outcome-driven business objectives. These objectives articulate the why behind the DAM: why it matters, what it will change, and how you’ll know it’s working.

Business objectives help you prioritize features, align teams, and communicate the system’s value to leadership. They keep the project focused, especially when you’re evaluating trade-offs or making decisions down the line.

Before diving into detailed requirements, ask: What does success look like with a digital asset management system in place? Are you aiming to reduce legal risk? Speed up campaign delivery? Preserve institutional knowledge? These goals shape every step of your selection and implementation process and are communicated through business objectives.

A strong business objective answers:

 “What are we trying to improve, fix, or enable with this system?”

Sample Business Objectives:

• Reduce time spent searching for assets by 50% to support faster content delivery Teams currently spend significant time locating approved visuals and files. Reducing this friction will help meet tight publishing timelines and improve responsiveness.
• Ensure only licensed assets are used in public materials Inconsistent tracking of usage rights increases legal and reputational risk. A DAM should help enforce compliance and make rights information visible and actionable.
• Consolidate digital assets created by different users and stored in disparate systems Assets are currently spread across local drives, cloud folders, and legacy tools. Centralizing them will support discoverability, collaboration, and long-term access.

Whenever possible, tie business objectives to measurable outcomes. For example: “Reduce asset search time by 50%” or “Ensure 100% of publicly used assets have visible rights metadata.” These goals can help you evaluate vendors—and later, your DAM’s performance.

Is a New Digital Asset Management System Actually Needed?

One of the goals of a good assessment is clarity. Sometimes that clarity reveals that a new DAM isn’t the right next step. You might discover that your existing system could work with better training, governance, or configuration. Or you may find that the real issue isn’t the technology, but the lack of shared standards or ownership. That’s still progress. A thoughtful assessment can help you solve the right problems, whether or not that includes replacing your DAM.

Next Steps: From Insight to Action

Whether your assessment points to the need for a new DAM or uncovers ways to improve the one you already have, the outcome is the same: you now know what you didn’t know before. It’s time to turn that insight into a plan.

Start by organizing what you’ve learned into something clear and shareable. A spreadsheet, a shared doc, or whatever helps your team keep track of it all. Consolidate data and priorities in one place to prepare for internal planning, vendor conversations, or decision-making.

As you move toward system selection or renewal, take a beat to assess your organizational readiness:

• Who will own the DAM long-term?
• Is IT prepared to support infrastructure, integrations, and identity management?
• Do you have staff or governance in place to manage the operation of the system?

A successful digital asset management system depends on more than just features. It also needs committed people, long-term support, and a structure that can grow with your organization. As you talk with stakeholders and gather input, make sure to document what you’re learning—key themes, priorities, pain points, and goals. Documenting these early insights will help shape shared understanding and keep things grounded as you move into planning and decision-making.

Next Article:

Documenting your DAM Selection Criteria

Go to next article

Documenting Your Digital Asset Management Criteria

Choosing a Digital Asset Management (DAM) system isn’t just about comparing feature lists from vendor websites. It starts with understanding your organization’s specific digital asset management criteria: what assets you manage, how your teams work, what’s not working, and where you’re headed. To make good decisions, you need clear documentation that captures those needs in a reusable, structured format.

This article offers practical guidance to help you build that foundation, with examples and templates you can reuse throughout your planning process, including RFP development, vendor evaluations, and internal alignment.

1. Start with a Centralized, Collaborative Document

Use a collaborative tool like Google Sheets, SharePoint, Excel, or AirTable to keep your documentation organized and visible to stakeholders. Create tabs that reflect the key areas in this article (e.g., Stakeholders, Usage Scenarios, Assets, Metadata), and structure your notes in a clear, sortable format. This makes it easier to spot patterns, prioritize shared needs, and track where each requirement came from. Your spreadsheet becomes a central source of truth for drafting your RFP, comparing vendors, and aligning internally.

2. Interview Stakeholders and Track Themes

Record short interviews (with permission) with stakeholders in marketing, creative, archives, IT, legal, and other teams that work with digital assets. Focus on what tools they use, where processes break down, and what they wish were easier.

Skip surveys. Interviews offer deeper insight into workflows, pain points, and expectations, and help you capture the language people actually use. These conversations will ground your future steps, ensuring the DAM supports real-world needs.

Tip: “Role” refers to the type of user experiencing the need (e.g., Designer, Archivist), while “Source” refers to the specific person or department who shared that insight during interviews (e.g., Design Lead, Archives Manager). This helps you see how broadly a need applies and trace it back to the original stakeholder if you need more context later.

3. Inventory Your Digital Assets (Rough Counts Are Fine)

You don’t need a full audit, just a rough idea of what you have, where it is, and who uses it. Include file types, volume estimates, and storage sizes:

This information is essential for planning migration and estimating storage needs, and vendors will need a summarized version to provide accurate costs in their proposals.

4. Look for Metadata (Even If You Don’t Call It That)

Even if you’re not using a formal metadata system yet, your team is probably tracking important information about your assets, like who created them, what they’re about, or how they can be used. That’s metadata.

Start by identifying what kind of information you already track and where it lives. It could be:

• In filenames or folder names
• In a spreadsheet
• Stored inside the file itself (like photo properties and technical information about the file)

You might also hear terms like:

• Metadata schema: This just means a consistent set of fields used to describe your assets, for example, “Photographer,” “Date Taken,” or “Usage Rights.” If you’re not using one yet, that’s okay. Start by listing what you are tracking.
• Embedded metadata: This is metadata that’s saved inside the file itself. For example, a photo might include the date it was taken, the camera model, or GPS location.

You might be tracking more metadata than you realize. Look around, especially in shared drives, naming patterns, or that old spreadsheet someone still updates manually. This will help you decide what metadata to keep as-is, what to standardize, and what metadata to capture automatically (with AI) once your DAM is in place.

5. Document Integration Needs Across Systems

Most DAM systems won’t stand alone. They often need to connect to tools your team already uses. These could include your website CMS, creative tools from Adobe, or archives and records systems.

Think about what other tools or systems it should work with.

Start by making a list of all the software your team already uses—like design programs, content management systems, cloud storage, or social media tools. Then, for each one, ask:

 “What do we need the DAM to do with this system?”

For example:

• Your designers might want to pull images straight from the DAM while working in Adobe Creative Cloud, without switching between tools.
• Your marketing team might need the DAM to automatically send approved images to your website or social media platform.

Making this list now will help you choose a digital asset management (DAM) system that plays nicely with the rest of your tech setup—and saves your team time down the line.

Even if you’re not sure how the integration will work yet, noting your needs now gives vendors and IT something concrete to work with later.

6. Capture Technical Requirements Up Front

Before you choose a digital asset management system, it’s important to document any technical expectations your IT team or organization has. These might include how users will log in, where the system is hosted, or what kind of security and accessibility standards it needs to meet.

Start with questions like:

• Does your organization require Single Sign-On (SSO)?
• Do you prefer a cloud-based system or one hosted internally?
• Are there file size limits you need to support?
• Do you have accessibility or compliance requirements?

No need for a technical spec. Just capture the basics to share with vendors.

Final Thoughts

Take your time with documenting your digital asset management needs. It can be tempting to jump straight into vendor conversations, but a clear, well-documented foundation will save time, reduce confusion, and support better decisions later on.

And don’t try to do it alone. Involve the people who will use the DAM every day. Their input will save you from surprises later, and probably make the system better for everyone.

Next Article:

Conducting Market Research and Shortlisting Vendors

Go to next article

Appendix A. DAM Selection Planning Checklist

Once you’ve done some of this early prework, like interviewing stakeholders and identifying your assets, you can move on to this checklist. It’s comprehensive and may feel overwhelming at first, but you don’t have to tackle it all at once. Take it step by step. Collaborate with your main stakeholders. Check in with IT. Use this list to structure your planning, shape your RFP, and guide vendor conversations.

The good news is, if you’ve done the work above, this list will feel much more manageable and actionable.

Strategic Foundation

• What purpose will your DAM system serve, and what problems is it meant to solve?
• What does success look like, and how will you measure it?
• What does Phase 1 (Minimum Viable Product) look like?

Users & Stakeholders

• Who are your key users and stakeholders?
• Have you conducted recorded interviews with them?
• What pain points and needs did they share?
• Have you tracked themes across roles and prioritized them?
• Who will administer the DAM system?

Usage Scenarios & Requirements

• Have you written future-focused usage scenarios for core roles?
• Have you written user stories that describe desired functionality?
• Are your requirements categorized as Mandatory / Preferred / Nice to Have?
• Are sources (departments, individuals) attributed to each requirement?

Assets & Storage

• What types of digital assets do you manage? (e.g., images, videos, audio, 3D)
• Where are they stored now? (shared drives, cloud storage, hard drives)
• What’s the estimated volume (e.g., number of files) and storage size (e.g., in TB)?
• Who uses or owns each asset type?
• Are any assets at risk (e.g., no backups, fragile storage media)?

Metadata & Organization

• What metadata do you track, even informally (e.g., in file names or spreadsheets)?
• Where does that metadata live (e.g., embedded, folder structures, Excel)?
• Do you have consistent file naming conventions?
• Do you use any controlled vocabularies or taxonomies?

Workflow & Lifecycle

• Who creates, reviews, approves, and publishes digital assets?
• What do your current workflows look like, and where are the pain points?
• Do you distinguish between Work in Progress (WIP) and Final assets?
• How are assets currently tagged and ingested?
• Who will manage migration and tagging into the new DAM?

Digital Preservation

• Do any assets need long-term preservation beyond active use?
• Are there embargoing, archiving, or retention policy requirements?
• Will the DAM integrate with a preservation system or strategy?

Licensing & Rights

• Are you currently tracking usage rights and license information?
• Do you know which channels, regions, and formats assets are approved for?
• Are any licenses expired, missing, or uncertain?
• How will user roles, permissions, and security be defined in the DAM?

UX / UI

• What should the user experience be like for search, upload, and browsing?
• Do you need features like thumbnails, preview players, or 3D viewers?
• Do you need multilingual interface support?
• How will different user types (e.g., casual vs. power users) interact with the system?

Integration Requirements

• What systems should the DAM integrate with (e.g., CMS, PIM, Adobe CC)?
• What kind of integrations do you need (e.g., push/pull assets, metadata sync)?
• Are any integrations vendor-supported or likely to require customization?
• Which integrations are Mandatory, Preferred, or Nice to Have?

Technical Requirements

• Do you require SaaS (cloud-based) or on-premise deployment?
• Is SSO (Single Sign-On) required (e.g., via SAML or OAuth2)?
• Are there preferred storage providers or data residency requirements?
• What is the max file size or upload threshold?
• Do you need accessibility compliance (e.g., WCAG 2.1 AA)?
• Will the DAM need to support public delivery of assets with secure access?

Timeline & Budget

• What is your ideal timeline for selection, contracting, and go-live?
• What is your estimated first-year cost?
• What is your projected ongoing cost (e.g., storage, licensing, support)?
• Will implementation be phased or rolled out all at once?

A DAMn Good Investment 

When the going gets tough, the tough get investing.  

With economic instability, the pressure is on leaders to tighten belts yet remain top of mind for target markets. In 2025, the global economy has been wildly unpredictable with tariffs, layoffs, and consumer confidence unstable. And, one of the biggest mistakes I see business leaders make during times of uncertainty is cutting their marketing and advertising budgets altogether.  To unlock the full potential of a company’s data for informed decision-making, it is essential that data be accurately recorded, securely stored, and properly analyzed. This becomes especially critical during economic downturns, when financial scrutiny intensifies and every margin matters. Data presented to prospects and existing customers must be precise to ensure that services and differentiators are clearly and correctly communicated. Internally, the accuracy of data shared with executives and analysts can directly influence client retention, strategic direction, and budget planning.

This is also a matter of operational efficiency. Even with effective employee training, the benefits can only be realized if teams are working from a consistent and reliable source of truth … DAM. Establishing this foundation is an investment that relies more on strategic time allocation than significant capital expenditure. To position itself for future growth, a company cannot afford to be complacent when evaluating potential technology investments. In a fast-moving digital landscape, organizations that delay improvements during slow periods risk falling behind. In contrast, companies that make deliberate investments—whether through new systems or by dedicating employee time to development and training—will be better prepared to seize emerging opportunities and showcase their competitive advantages as conditions improve.

This is a good time to invest in DAM.

Change is a Good Investment

Change is as present as it is pervasive. It is good to recognize, acknowledge and accept that change is happening in business, and to learn not only what that means for you and your team, but to be ready for those new opportunities. So, why do we change?

• We change to advance forward.
• We change to make ourselves stronger.
• We change to adapt to new situations.

Without change, there would be no improvements. If business is about growing, expanding and making things better for your customers, then what changes are you making? As many of us begin to see future recovery, I too look to the horizon and know that better days are ahead for us all. Whether you’re undertaking an improvement, an upgrade or modernization, whatever you call it, any such effort is holistic by design, encompassing all aspects of business. Many businesses have taken this time to focus on improving all aspects of their business that affect people, process, and technology. This is about good and positive access to information from many systems to not hinder but enable our work. Watch for signs and respond well. Improvement for all is a good thing. In business, we always aspire for stability but need to be prepared for the opposite. This is about both insurance, and investment. 

Invest in DAM

The demand to deliver successful and sustainable business outcomes with our DAM systems often collides with transitioning business models within marketing operations, creative services, IT, or the enterprise. You need to take a hard look at the marketing and business operations and technology consumption with an eye toward optimizing processes, reducing time to market for marketing materials, and improving consumer engagement and personalization with better data capture and analysis.

Time to Transform

To respond quickly to these expectations, we need DAM to work within an effective transformational business strategy that involves the enterprise. Whether you view digital transformation as technology, customer engagement, or marketing and sales, intelligent operations coordinate these efforts towards a unified goal. DAM is strengthened when working as part of an enterprise digital transformation strategy, which considers content management from multiple perspectives, including knowledge, rights and data. Using DAM effectively can deliver knowledge and measurable cost savings, deliver time to market gains, and deliver greater brand voice consistency — valuable and meaningful effects for your digital strategy foundation.

Future-Proof your Content

Consider the opportunity in effective metadata governance: do you have documented workflows for metadata maintenance? Are you future-proofing your evergreen content and data? Remember to listen to your users, to keep up to date and aware of your digital assets, and leverage good documentation, reporting, and analytics to help you learn, grow and be prepared. If you are not learning, you are not growing. If you are not measuring, then you are not questioning, and then you are truly not learning.

Conclusion

Keep the lights on. Now is the time to get smart and strategic with your money to ensure you can weather the current unpredictability and even come out ahead. Tariffs, recession fears, rising prices, and potential layoffs dominate headlines right now. As you look to the second half of the year, this might be causing you to take a close look at budget forecasts and reevaluate spending.

Play the long game. Marketing is a long-term strategy, and DAM is a cornerstone of Marketing efforts and operations. More than ever, there is a direct need for DAM to serve as a core application within the enterprise to manage these assets. The need for DAM remains strong and continues to support strategic organizational initiatives at all levels. DAM provides, more than ever, value in:

• Reducing Costs
• Generating new revenue opportunities
• Improving market or brand perception and competitiveness
• Reducing the cost of initiatives that consume DAM services

The decision to implement a DAM isn’t one to take lightly. It is a step in the right direction to gain operational and intellectual control of your digital assets. DAM is essential to growth as it is responsible for how the organization’s assets will be efficiently and effectively managed in its daily operations.

A DAMn good investment to me. 

Next Page »