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85% of companies want to become an agency within three years; however, 76% admit their operations cannot support it. According to the Celonis Process Optimization Report 2026According to a survey of more than 1,600 global business leaders, organizations are aggressively pursuing AI-driven transformation. However, most recognize that the critical work—modernizing workflows, reducing process friction, and building operational resilience—remains unfinished. The ambition is clear. The infrastructure to run it is not.
To act autonomously and effectively, AI agents need optimized, AI-ready processes, as well as the process data and operational context that only comes from process intelligence. Without that, they’re guessing. And 82% of decision makers believe that AI will fail to generate return on investment (ROI) if it does not understand how the business works.
"The magnitude of the opportunity is truly remarkable: 89% of leaders see AI as their biggest competitive opportunity." says Patrick Thompson, global senior vice president of customer transformation. "That is not a marginal finding. What is interesting is the change in the framing. Leaders are confident that AI will transform operations. The question now is how to fuel your ambitions with the right AI enablers."
Explaining the gap between ambition and reality
Right now, 85% of teams use AI generation tools for everyday tasks, so the question “will it work?” The issue is largely resolved. The real question now is: “Why isn’t it working the way we need it to?” And that is a much more difficult problem, because it is structural. They are isolated teams. Systems that do not communicate with each other. AI that looks impressive in a demonstration but fails once it is introduced into a real business environment. That is the wall that companies are hitting.
So, despite the overwhelming ambition, today only 19% of organizations use multi-agent systems. It all comes down to an issue of operational readiness, Thompson says.
"Nine out of ten leaders are already using or exploring multi-agent systems, so the will is there, but ambition without infrastructure doesn’t get you very far." explains.
Until now, process has largely been a “good enough” problem, because processes that are messy and disconnected can still produce results, just inefficient and opaque. As the business continues to grow, there hasn’t been a compelling need to fix them. AI changed the calculus. If 82% of leaders believe that AI can only deliver ROI with the right business context, then suboptimal processes are not just an operational drawback, they are actively blocking an AI strategy. Suddenly, process optimization is no longer a background IT project, but a prerequisite to compete.
"This is where structural modernization becomes critical," he says. "Organizations that have invested in modernizing their data, systems and processes are in a much stronger position to enable AI at scale."
The other obstacle for AI: lack of business context
AI will not be able to provide the highest possible return on investment until it understands the operational context of the business. That includes how KPIs are defined and calculated, unique internal policies and procedures, how the organization is structured, and where the true decision-making authority lies.
This knowledge is often trapped in different departments that have developed their own languages and systems over time. Naturally, they do not share a common understanding. Bringing AI into that environment is kind of like engaging someone in a conversation that’s been going on for years, without any backstory.
Process intelligence becomes the connective layer: a shared operational language that grounds AI decisions in how the business really works.
Why AI adoption is also a change management issue
The AI adoption challenge is less of a technology problem and more of a change management and operating model problem than many leaders want to admit, because technology problems seem easier to solve. Data shows that only 6% of leaders cite resistance to change as an obstacle. The real obstacles are isolated teams (54%) and lack of coordination between departments (44%). And 93% of process and operations leaders explicitly state that process optimization is as much about people and culture as it is about tools and technology.
"When companies come to us looking for a technology solution, part of our job is to help them see that the operating model has to evolve along with the tools." Thomson says. "You can’t throw AI into a broken process and expect it to work. True business modernization means redesigning the way teams, systems, and decisions connect, and AI only works when that modernization happens first."
Make process optimization a strategic advantage
How can process optimization be made a strategic advantage, rather than just another operational project? Connect it directly to the results that executives care about. When processes work, they go beyond IT metrics and directly impact board-level concerns. 63% of leaders use process optimization to proactively manage risk, while 58% see faster decision making.
Additionally, the current economic and geopolitical environment makes agility a survival skill. Look at the supply chain industry, where 66% already consider process optimization a critical business-wide initiative.
"That is the mindset change we are trying to catalyze in the rest of the organization." Thomson says. "They are not maintenance jobs. It’s what allows you to move quickly when the world changes, and right now the world is constantly moving."
Closing the readiness gap in enterprise agent AI
To succeed, and even triumph, organizations must be prepared to close the readiness gap and be honest about where they are starting from, Thompson says.
"The biggest risk I see is that companies continue to layer AI on opaque and fragmented processes and then wonder why they aren’t getting results." he says. "Moving from static, traditional tools to real process intelligence, where you have live visibility into how your operations are actually executed, that is the fundamental change that makes agent AI viable."
Without it, agents are deployed in the wrong places, can’t integrate with existing systems, and organizations end up with expensive pilots that don’t scale. The call to action is clear: stop starting with tools and start with operational visibility.
"The leaders who will win in the agent era are not necessarily the ones with the most sophisticated AI," he says. "They are the ones who have done the hard work of creating a shared and accurate picture of your operations. Process intelligence is the starting point. It’s what enables business modernization in practice, creating the operational clarity AI needs to deliver real ROI. Master your processes, give AI the context it needs, and then you can deploy it somewhere it works."
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