TLDR: A MarTech Conference panel discussed the critical need for marketers to proactively manage consent, ensure compliance, and build customer trust in an increasingly AI-driven world. Key takeaways include leveraging existing privacy frameworks, fostering transparency, differentiating AI use cases, and developing new skill sets that blend data, ethics, and storytelling.
The rapid integration of artificial intelligence into marketing operations presents both immense opportunities and significant challenges, particularly concerning data privacy, regulatory compliance, and maintaining customer trust. This was the central theme of a recent session at the September installment of The MarTech Conference, featuring a panel of industry experts.
Moderated by MarTech contributor Melissa Reeve, the discussion included enterprise AI consultant Anthony Coppedge, Alex Cash, director of strategy for consent-based solutions at OneTrust, and Adam Eisler, legal counsel at the Interactive Advertising Bureau (IAB). The consensus was clear: AI’s value is contingent on responsible data collection and ethical deployment.
Alex Cash highlighted a coming paradigm shift, noting, “The way that these AI products operate today and their ability to interact with voice wearable devices… There is a very real possibility that in the future we talk about AI outside of the context of the browser and the mobile app.” Adam Eisler added a crucial perspective, stating, “It’s not just how companies use AI, it’s also how AI uses those companies.” Anthony Coppedge underscored the growing importance of transparency, asserting, “Customers want to know what AI is doing and what AI is doing with the customer’s data… Show them the way their data is used… that would actually, I think, boost engagement.” Melissa Reeve pointed out that AI is democratizing data use for marketers, who previously relied heavily on specialized teams for data collection, processing, and analysis.
The panel emphasized the necessity for agile governance frameworks, as traditional, slower approaches are ill-suited for the dynamic AI landscape. Coppedge advocated for “adaptive approaches like transparency through dashboards that show users how data is being used.” Eisler cautioned against a ‘wait-and-see’ approach to regulation, stating, “Definitely don’t wait. Waiting, in the end, put a lot of companies that chose to wait at a disadvantage because the companies that took a more privacy-proactive approach were in a position to hit the ground running.” He also reminded the audience that existing state comprehensive privacy laws already encompass AI activities, with no specific ‘AI carve out.’
A significant challenge discussed was the ‘unbaked cake’ problem related to consent for AI model training. Alex Cash explained the distinction between deploying embedded AI tools and training models in-house. He noted, “One of the key concepts of consent is that you need to be able to withdraw it. If you train a model on someone’s data and then they withdraw… Do I roll back the model? You can’t un-bake a cake.”
Regarding the ownership of AI governance, opinions varied but converged on a collaborative approach. Cash argued that “Marketing teams must be at the same table with privacy and with our governance and risk teams… ‘govern well, move fast.'” Coppedge, however, believed it shouldn’t be confined to a single business unit, advocating for a “group effort” due to AI’s dynamic nature. Reeve synthesized these views, suggesting a move “from static to dynamic, a cross-functional group at the top, another layer and AI leads or champions on the front line.”
Looking ahead 18 months, the panel predicted three key areas of disruption: evolving legal and intellectual property questions, the emergence of new hybrid marketer skill sets (part data scientist, part ethicist, part storyteller), and the rise of agent-to-agent ecosystems that will fundamentally alter how marketers acquire data.
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In conclusion, the panel’s overarching message was that successful AI adoption requires proactive, transparent, and agile governance, with marketers playing a pivotal role in shaping how customer trust is earned and maintained in this new era. Key actions for marketers include utilizing existing privacy frameworks, making transparency tangible through clear explanations and dashboards, distinguishing between different AI use cases, sharing governance responsibilities across functions, and continuously upskilling in data fluency, ethics, and storytelling.
