Most organizations are making decisions about AI faster than they can evaluate the results, while the processes the technology depends on have barely changed. Organizations are not failing to adopt AI. They are applying it to business processes which weren’t designed for the AI era, then wondering why the return on investment falls short.
According to our “The AI Process Gap” report, broken or legacy business processes are causing AI initiatives to fail at a staggering rate. Almost three-quarters (72%) of organizations say process-related challenges have contributed to AI initiatives failing at an average cost of $1.55 million per business. What’s more, 82% believe that their AI investments will be a bust without more investment in process re-design.
Bolting AI onto legacy processes isn’t the answer
Almost every process running in large organizations was designed for a world without AI. But with pressure to operationalize AI, many are opting for a quick fix rather than taking an outcome-centric approach and re-designing processes from scratch.
- 79% acknowledge that bolting AI onto existing processes creates less internal resistance than properly re-designing them.
- Almost two-thirds (61%) of respondents say business process re-design simply can't keep pace with how fast they need to move on AI.
- Over four-fifths (82%) say it will take up to five years to adapt their most important processes for AI.
Simply layering AI on top of legacy processes doesn’t unlock its full potential. Instead, organizations are adding complexity and creating new governance and regulatory exposure. In fact, 40% of organizations have experienced an AI-related compliance or governance issue in the past 12 months. And process-related issues have contributed to the vast majority (84%) of them.
Don’t forget about the employees
Employees are caught in the middle of poorly implemented AI rollouts. Many are feeling the impact of AI being introduced into processes that were never designed for it, quietly working around the tools that were supposed to help make their lives easier.
- 69% of employees were not fully consulted about how AI would be used to support their day-to-day work.
- 65% of employees say they could use AI a lot more effectively if it was implemented differently.
- 44% of employees say they have had to manually override AI outputs because the underlying process wasn't set up correctly.
In fact, almost half (48%) of organizations say they have rolled back on their use of AI because it’s had a negative impact on employees’ ability to do their job.
Closing the AI process gap
Closing this gap requires going further than most AI programs do today. Organizations need to re-engineer their processes so that AI agents operate seamlessly alongside people and systems within one governed, end-to-end process. That’s The Great Process Re-Engineering: re-designing how work gets done around what AI makes possible, rather than simply adding AI to the way work gets done today.
Processes built for a world before AI have to be rebuilt before AI can fully deliver on its promise. No amount of additional spending on AI agents and models can change that.
Fortunately, there is a path forward with ProcessOS, the AI intelligence layer of the Camunda platform. It’s built to reduce process re-engineering from months or years to weeks. Learn more about how ProcessOS works.
Download the report
Download Camunda’s “The AI Process Gap” report here.
