Trust, Authenticity & Governance for the AI Age

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

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/