How are you balancing the risk of innovation with oversight and control when piloting AI agents in your martech stack?

The key is understanding what the AI agent is actually doing, what information it uses, how it makes decisions, and if there is an integrated process that will pre-vet the outputs. Most AI agents are algorithms or ML, not actual generative AI creating outputs that are built on third-party data/information. Companies have been working with ML and algorithmic software for decades, often without much legal oversight because these are more of a closed environment developed with information that has already been risk-vetted. Calling something AI without understand what it actually does introduces friction into a process that may have been pretty smooth. But with AI being such a buzzword its a way for many companies to charge more by re-branding what their products have already been able to do. True innovation should have greater oversight and control, but incremental innovation of technical processes that are essentially the same underlying technology should be treated according to the actual risk it presents rather than immediately labeling AI risk as 'high'.

I am focused only AI agents that understand the entire business operations not just the martech stack. That way it doesn't feel disconnected from the rest of the organization. The important part here is to use Agentic AI plus an AI that understands business. The combo does wonders for the operation.

We're using controlled pilots with clear KPIs, ongoing monitoring, and regular reviews to balance innovation and oversight when integrating AI agents into our martech stack.