Mastering AI: Consent, Compliance, and Customer Trust
â–Ľ Summary
– AI’s value for marketers depends on quality data collected responsibly, as discussed at The MarTech Conference by experts including Anthony Coppedge, Alex Cash, and Adam Eisler.
– The data landscape is shifting, with AI expanding beyond browsers and apps into voice and wearables, while transparency in data use boosts consumer trust and engagement.
– Governance must be agile and proactive, using existing privacy laws without waiting for new regulations, and distinguishing between deploying AI tools versus training models.
– Ownership of governance should be cross-functional, involving marketing, privacy, and risk teams in a dynamic, layered approach rather than being siloed in one business unit.
– Key near-term disruptions include legal and IP issues, new hybrid marketer skill sets, and agent-to-agent ecosystems, requiring marketers to act now with transparency and adaptability.
Harnessing the power of artificial intelligence offers marketers unprecedented opportunities, but only when built on a foundation of ethically sourced and well-managed data. A recent panel at The MarTech Conference emphasized that responsible data practices are not just a legal requirement, they are central to maintaining consumer confidence and achieving meaningful engagement.
During the session, experts including Anthony Coppedge, Alex Cash of OneTrust, and Adam Eisler of the IAB explored how the rapid evolution of AI is reshaping marketing’s relationship with data, governance, and public trust.
Cash highlighted a significant shift on the horizon, noting that AI will soon operate beyond traditional digital environments like browsers and mobile apps, integrating deeply with voice assistants and wearable technology. This expansion demands new thinking around data collection and user permissions.
Eisler added a crucial perspective: the relationship between companies and AI is bidirectional. It’s not only about how organizations deploy AI, it’s also about how AI systems influence organizational behavior and decision-making.
Transparency emerged as a recurring theme. Coppedge stressed that customers increasingly expect to understand how their data is being used. Showing users how their information fuels AI systems can actually deepen engagement and strengthen brand loyalty. Meanwhile, moderator Melissa Reeve pointed out that AI is democratizing data analysis, empowering marketers who once depended heavily on specialized technical teams.
The panel agreed that traditional governance models are too rigid for the AI age. Organizations need agile, adaptive frameworks, such as live dashboards that offer real-time insight into data usage. Eisler warned against waiting for legislation to catch up. Companies that act now, embedding privacy into their AI strategies, will gain a competitive edge.
He also clarified that existing privacy regulations already apply to AI. No special exemptions exist, consumer rights like opting out of targeted ads or consenting to sensitive data processing remain firmly in place.
Cash drew attention to a critical distinction in AI implementation: using pre-built AI tools is fundamentally different from training custom models in-house. Each approach carries unique compliance considerations and risks. He illustrated the challenge with what he called the “unbaked cake” problem: if a user withdraws consent after their data has been used to train a model, can that influence be undone? In most cases, it cannot.
Ownership of AI governance sparked lively debate. Cash argued that marketing teams must collaborate closely with privacy, risk, and governance units. Coppedge believes effective oversight requires a cross-functional effort rather than isolation within one department. Reeve proposed a layered approach, combining high-level strategic oversight with empowered AI champions embedded in frontline teams.
Looking ahead, the panel identified several areas ripe for disruption over the next 18 months. Eisler anticipates legal battles around copyright and fair use that will directly affect marketing tools. He urged teams to clearly identify use cases and measure real ROI, separating substance from hype.
Coppedge foresees the rise of a new type of marketing professional: one who blends data science, ethical reasoning, and storytelling. Tomorrow’s most effective marketers will need to orchestrate personalized experiences within trusted ecosystems.
Cash predicted the emergence of AI agents that could revolutionize how marketers acquire and utilize data, creating new channels and complexities in data sourcing.
The consensus among experts is clear: marketing leaders cannot afford to delay AI adoption until regulations are perfected. Success hinges on proactive, transparent, and adaptable governance built on trust.
Key recommendations include acting now under current privacy frameworks, using clear dashboards and explanations to demonstrate transparency, differentiating between AI deployment and model training, fostering cross-functional governance, and investing in new skill sets for marketing teams. As Reeve summarized, governance must become dynamic, evolving as rapidly as the technology itself. For marketers, that means embracing both new tools and new responsibilities in the ongoing effort to earn and keep customer trust.
(Source: MarTech)
