Enterprise leaders met at Camunda’s NYC Roadshow to discuss the AI Process Gap—and why real transformation requires re-engineering processes from the ground up on open standards.
"In a broken process, people just try to use AI and throw it in, hoping it will work," observed Hemant Sharma, an engineering manager at Kaseya who attended Camunda's "The Great Process Re-Engineering" NYC Roadshow at Midtown Loft & Terrace on September 10, 2026. "Re-engineering means looking at the purpose of AI more holistically."
Sharma's team runs a merchant-onboarding process that takes 30 days, with a target of under 24 hours. He'd never used Camunda before, so his reaction was unprompted, and it captured the core problem facing enterprise operations today: AI can't fix a broken process. On accountability, Sharma said, "It's a process manager's job to put a human in the loop. When exception handling needs to happen, you're handing off to a human who can make the call for a special scenario the AI couldn't handle."
The Reality of the AI Process Gap
Sharma's comments echo Camunda's new AI Process Gap Report, a July-August 2026 survey of 1,000 process decision-makers and 5,000 employees at companies with 1,000+ employees, across the US, UK, Germany, and France.
The data shows a real tension in enterprise tech:
- 78% of decision-makers say they must redesign processes from the ground up to stay competitive, rather than just layering AI on top.
- 79% admit that bolting AI onto existing processes meets less internal resistance than a full redesign.
Shortcuts are expensive. 72% of leaders say process problems have caused AI initiatives to fail, at an average cost of $1.55M per organization. 40% had an AI-related compliance or governance issue in the past 12 months, and process gaps caused 84% of those. Without a shift to process design, 82% of leaders expect their AI investments will be a "bust."
Employees feel it too. 65% say they could use AI far more effectively if it were set up differently, and 44% have manually overridden AI outputs because the underlying process wasn't configured right.
Moving Beyond the 11% Production Barrier
In the keynote, Isaac Sacolick (Founder & President of StarCIO) laid out the gap between what technology can do and what counts as real business transformation. Peter Vaccarella (VP of Presales at Camunda) followed by introducing ProcessOS, an operating system for business processes built to cut re-engineering cycles from years to weeks.
In the customer panel, Murthy Ganti (Director, Software Development – Platforms & AI Accelerator, RBC Clear) and Jeremy Warren (VP, Enterprise Technology Solutions, Greylock Federal Credit Union) shared what it takes to scale production orchestration in financial services. Moderator Eric Clifford (Camunda) noted that only 11% of AI use cases ever reach production.
Asked where enterprises get stuck, the panelists said it's rarely a technical problem. It's change management, and the mindset shift from "injecting AI into existing workflows" to "re-engineering processes from the ground up."
Hands-On Workshop: Testing the Blockers
Attendees put these ideas into practice in a workshop, "Map your re-engineering opportunity." Tables of ten analyzed real-world baselines:
- Financial Services Loan Origination: 11-day baseline
- Insurance Claims (FNOL-to-Payment): 19-day baseline, 30% touched twice
- Quote to Cash: 62-day DSO baseline
Teams identified where a digital-native competitor with no legacy baggage would beat them, then tested their plans against a "the board gives you 90 days" constraint. Common blockers surfaced: deep system lock-in, fragmented ownership, and compliance acting as a gate instead of a built-in guardrail.
Making Re-Engineering Stick with Open Standards
A core takeaway: lasting process re-engineering needs an open foundation. Open standards mean an enterprise isn't locked into one vendor's roadmap.
When new technologies or AI models emerge, an open architecture lets organizations adopt them freely, without a vendor's commercial interests getting in the way. Closed platforms steer you toward their own ecosystem; open standards keep the focus on the best business outcome.
Next Steps
To dig into the research:
- Download the full AI Process Gap Report.
- Read the press release: "72% of organizations say process-related challenges have caused AI initiatives to fail."
- Explore the companion blog: "The Data Says It: AI Isn't Failing You. Your Processes Are."
Next Stop on the Roadshow: Join us in Dallas as "The Great Process Re-Engineering" tour continues. Find more Camunda events here.
