Celonis predicts context‑aware AI to reshape supply chains

Celonis executives expect companies to rethink artificial intelligence, automation and technology ecosystems by 2026, with a focus on operational context, autonomous processes and open platforms.

Senior leaders at the a global leader in process intelligence outlined their views on how AI and supply chains may develop over the next two years.

They expect competitive advantage to depend less on isolated automation projects. They expect more emphasis on how AI systems interact with real-world business operations.

AI and context

Dan Brown, Chief Product Officer at Celonis, said companies will move beyond early AI experiments.

He said many organisations will recognise that AI systems need a detailed view of operations.

Brown said that in 2026, competitive advantage will shift to organisations that provide AI with operational context through a "living digital twin" that reflects how the business runs.

He said this kind of model lets AI systems sense and reason about processes. He said it also underpins action and improvement in a responsible way.

Brown expects trust in AI to depend on clear visibility of how decisions happen rather than tight control.

"Your digital twin becomes the unbiased source of truth that makes every AI action traceable, explainable and continually improvable. When teams can see why AI made a decision, they can refine it - turning AI into a true partner," said Dan Brown, Chief Product Officer, Celonis.

He said context-aware AI will change supply chain decision-making.

Brown expects systems to look across entire flows rather than specific steps in a process.

He said AI will predict bottlenecks in advance. He said it will identify exceptions that matter and coordinate recovery plans based on financial and service-level impact.

He said this approach will narrow the gap between planning and execution in complex supply chains.

Brown said organisations need AI systems that understand how processes work in practice.

He expects real-time visibility of how work is done to become essential for AI-based decision-making.

"AI can't drive business value without understanding how your business flows. When you give it that context - the real-time visibility into how work gets done - the trust comes naturally. You see why it made a decision and how to make it better. That's when AI becomes enterprise ready," said Brown.

Autonomous operations

Peter Budweiser, General Manager of Supply Chain at Celonis, expects a shift from task automation towards outcome orchestration.

He said many enterprises have spent years automating individual activities.

He expects the next phase to focus on how well companies coordinate AI, people and systems across processes.

"In 2026, leaders will shift from fragmented automation to coordinating AI, people and systems across the entire workflow. This is the only way to transform business processes into truly autonomous operations," said Peter Budweiser, GM of Supply Chain, Celonis.

Budweiser said organisations should treat enterprise AI as a discipline for redesigning end-to-end processes.

He said they should avoid adding automation on top of inefficient workflows.

"Success should be measured by the continuous improvement of the whole process, not the speed of a single task," said Budweiser.

He expects supply chains to act as test beds for this more integrated approach.

Budweiser said AI systems will reroute shipments and rebalance inventory in response to changing conditions.

He said these systems will highlight capacity constraints and coordinate suppliers and planners within the same loop.

He said this will turn fragile supply networks into more adaptive ecosystems that can respond quickly to tariffs, disruptions and volatility.

Open ecosystems

Vanessa Candela, Chief Legal & Trust Officer at Celonis, expects more organisations to question closed technology platforms by 2026.

She said the era of walled systems and vendor lock-in is coming to an end.

"In 2026, enterprise value will shift to open, interoperable, system-agnostic ecosystems where processes are no longer constrained by the systems they run on. This is how organisations will improve continuously, adapt instantly, and innovate freely," said Vanessa Candela, Chief Legal & Trust Officer, Celonis.

Candela said companies should resist new forms of dependence on single vendors.

She said organisations should ask technology partners for interoperable solutions and data portability.

"Insist that your technology partners support interoperable solutions and data freedom so you can redesign your processes around business needs, not system constraints. Open architectures future-proof your operations and prevent new forms of vendor lock-in as AI becomes mission-critical," said Candela.

She expects more open ecosystems to support cross-company visibility of key operational data.

She said this will include capacity signals, supplier risk, emissions data, credit blocks and advance shipment notice quality.

She said companies will share a more consistent view of operations across networks.

"AI agents across companies will co-decide on allocations, routing, buffers, and lead-time risk, shifting the focus from internal efficiency to network-wide competitive advantage," said Candela.

Celonis executives said organisations that invest in operational context, integrated orchestration and open platforms over the next two years will be better placed for an AI-driven business environment in 2026.