My latest interactions with customers and prospects on their AI deployment efforts have signaled a few things: 1. There is growing recognition that AI agents cannot be deployed successfully without foundational work to build and maintain a digital twin of the organization. This digital twin can provide the context layer needed to design and run autonomous agents. Unfortunately, some companies recognize this only after spending millions of dollars on agentic deployment efforts. 2. Companies that have historically been disciplined in documenting and managing their processes through a proper process-intelligence platform have a visible competitive advantage in deploying AI compared with their peers. The concept of “process debt” is emerging as an analogue to technical debt. 3. Some companies have understood the urgency of paying down their process debt, with mandates from the C-suite to build a complete digital twin of the company as a matter of priority.

Could not agree more with this. No executive would agree to sign off (and in some cases be personally liable) on deploying agentic AI in production at scale without having confidence that deterministic guardrails, audit trails and containment options are in place - This is part of what we're focused on enabling at ARIS

Seven months ago I became CEO of @ARIS_Process. Before that, I spent years trying to get AI to do real work at scale, and mostly failing. Here's the mistake I made, more than once. I treated AI deployment as a model problem. Pick the right model, write the right prompt, ship it. The real issue sat somewhere else entirely: documentation. We never had an accurate picture of how our processes actually ran, exceptions and workarounds included, not just the tidy version in the slide deck. So every agent we deployed was guessing. Guessing agents get narrow scope, heavy guardrails, and results that don't hold up. I didn't fully understand this until I got inside ARIS and saw what a properly built digital twin of an organization looks like. Every week I ask an AI to find me real examples of companies that have given agents genuine autonomy at scale. The list is still short, a pattern across the whole industry rather than any single team's failure. Give an agent the same clarity about how your business works that you'd give a sharp new hire, and it stops guessing. That's the bet I'm making with ARIS. Where is your team hitting that same wall?

"We're deploying AI agents" almost always means "on something small, with a human checking every step." The real blocker is context. Most companies don't know their own processes well enough to trust an agent inside them. What's stopping your team?

Another win for ARIS: we've been named a Leader in the inaugural Gartner® Magic Quadrant™ for Digital Twin of an Organization Platforms 🎉 As enterprises scale agentic AI, the real challenge isn't deployment, it's governance and trust. Our unified digital twin platform gives…