Enterprise agentic AI requires a process layer most companies haven’t built
Source: VentureBeat
Presented by Celonis
The Ambition–Readiness Gap
85 % of enterprises want to become agentic within three years — yet 76 % admit their operations can’t support it.
According to the Celonis 2026 Process Optimization Report (survey of > 1,600 global business leaders), organizations are aggressively pursuing AI‑driven transformation. Yet most acknowledge that the foundational work — modernising workflows, reducing process friction, and building operational resilience — remains unfinished.
The ambition is clear. The infrastructure to execute on it is not.
To act autonomously and effectively, AI agents need:
- Optimised, AI‑ready processes
- Process data and operational context – the only output of process intelligence
Without these, AI is “guessing.” 82 % of decision‑makers believe AI will fail to deliver ROI if it doesn’t understand how the business runs.
“The scale of the opportunity is truly remarkable: 89 % of leaders see AI as their biggest competitive opportunity,” says Patrick Thompson, Global SVP of Customer Transformation. “That’s not a marginal finding. What’s interesting is the shift in the framing. Leaders are confident that AI will transform operations. The question now is how to fuel their ambitions with the right AI enablers.”
Explaining the Gap Between Ambition and Reality
- 85 % of teams are already using generative AI tools for everyday tasks – the “will this work?” question is largely settled.
- The new question is: “Why isn’t it working the way we need it to?”
- Structural issues: siloed teams, non‑communicating systems, AI that looks impressive in demos but falters in real‑world enterprise environments.
Consequently, only 19 % of organisations use multi‑agent systems today. The problem is operational readiness.
“Nine in ten leaders are already using or exploring multi‑agent systems, so the will is absolutely there, but ambition without infrastructure doesn’t get you very far,” Thompson explains.
Until now, process has been treated as a “good enough” problem: messy, disconnected processes can still produce results—just inefficiently and opaquely. As long as the business grows, there’s been little urgency to fix them. AI changed the calculus.
- 82 % of leaders believe AI can deliver ROI only with proper business context.
- Sub‑optimal processes are no longer a convenience issue; they actively block an AI strategy.
“This is where structural modernisation becomes critical,” Thompson says. “Organisations that have invested in modernising their data, systems, and processes are in a far stronger position to enable AI at scale.”
The Other AI Stopper: Lack of Business Context
AI cannot achieve its full ROI until it understands the operational context of the business, including:
- How KPIs are defined and calculated
- Unique internal policies and procedures
- organisational structure and decision‑authority hierarchy
This knowledge is often trapped in disparate departments that speak different “languages.” Dropping AI into such an environment is like inserting someone into a long‑running conversation without any back‑story.
Process intelligence becomes the connective layer—a shared operational language that grounds AI decisions in how the business actually runs.
Why AI Adoption Is Also a Change‑Management Problem
The challenge is less about technology and more about change‑management and operating‑model evolution.
- Only 6 % of leaders cite resistance to change as a hurdle.
- Real blockers:
- Siloed teams – 54 %
- Lack of coordination between departments – 44 %
93 % of process and operations leaders state that process optimisation is as much about people and culture as it is about tools and technology.
“When companies come to us looking for a technology fix, part of our job is helping them see that the operating model has to evolve alongside the tooling,” Thompson says. “You can’t bolt AI onto a broken process and expect it to work. True enterprise modernisation means redesigning how teams, systems, and decisions connect, and AI only works when that modernisation happens first.”
Making Process Optimisation a Strategic Advantage
Connect optimisation directly to outcomes that executives care about:
| Outcome | % of Leaders Reporting Use |
|---|---|
| Proactively manage risks | 63 % |
| Faster decision‑making | 58 % |
| Critical business‑wide initiative (supply‑chain) | 66 % |
In today’s economic and geopolitical climate, agility is a survival skill. Process optimisation moves beyond IT metrics to board‑level concerns.
“That’s the mindset shift we’re trying to catalyse across the rest of the organisation,” Thompson says. “It’s not maintenance work. It’s what lets you move fast when the world changes, and right now the world is moving constantly.”
Closing the Readiness Gap in Enterprise Agentic AI
To succeed—and even triumph—organisations must:
- Honestly assess where they are today.
- Close the readiness gap by moving from static, traditional tools to real process intelligence.
“The biggest risk I see is companies continuing to layer AI on top of fragmented, opaque processes and then wondering why they’re not getting results,” Thompson warns. “Moving from static, traditional tools to real process intelligence, where you have …”
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“We need visibility into how your operations actually run; that’s the foundational shift that makes agentic AI viable.”
Without it, agents get deployed in the wrong places, can’t be integrated 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 agentic era aren’t necessarily the ones with the most sophisticated AI,” he says. “They’re the ones who’ve done the hard work of building a shared, accurate picture of their operations. Process intelligence is the starting point. It’s what enables enterprise 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 actually deploy it somewhere it will deliver.”
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