This time last year, I released a Deeplearning.ai course with Andrew Ng on Governing AI agents with the goal of educating developers on the basics of data protection for effective and responsible agent deployment. The motivation for the course came from IBM's 2025 breach study, which found 97% of the organizations that suffered an AI-related breach lacked proper AI access controls, and 63% had no AI governance policy at all. A year is an eternity in AI development, and we have come a long way from agents with zero governance or grappling with governing a single agent. Teams are now confronting a new governance challenge: agent sprawl (the uncontrolled growth of autonomous AI agents across an organization without centralized tracking, ownership, or governance).
According to Gartner, by 2028 the average Fortune 500 enterprise will use over 150,000 AI agents. However, according to the firm, only 13% of organizations believe that they have the right AI agent governance in place. Since last year, the ability to deploy has gotten easier than ever. The onset of coding agents like claude code and codex, as well as a variety of low-code/no-code options have lowered the barrier to agent deployment substantially. One result is teams are now faced with the possibility of their agent fleet engaging in hugely wasteful token usage and incurring unforeseen costs.
Another serious challenge is the additional pathways for sensitive data to leak out. Unsurprisingly, governance challenges have evolved. Currently, I'm watching customers build agents faster than ever, and the shape of the problem has shifted. A year ago we focused on adding the four pillars of governance to a single agent: lifecycle management, risk management, security and observability. We knew even then that building an agent wasn't the hard part.
Now, this hasn't changed, but what's the shift? The difference is this is happening with dozens of agents/sub-agents at the same time. Agents are multiplying faster than a lot of teams are able to govern them. Teams now need to be equipped with a data platform that scales centralized tracking, permissions, and governance with the number of agents being built. Let's examine how the pillars of governance have evolved in 2026.
Source: Towards Data Science · Summarized by HeadlinesBriefing