New research from Camunda, the enterprise platform for agentic orchestration, has revealed how broken business processes are causing AI initiatives to fail at a staggering rate. According to the report, The AI Process Gap, 65% of insurance organizations say that process-related challenges have caused AI initiatives to fail at an average cost of $1.40 million per business. Furthermore, another two thirds (65%) say that AI costs will spiral unless they gain better control over their business processes, with 79% believing that their AI investments will be a bust without more investment in process re-design.
The report highlights how many insurance organizations are attempting to bolt AI onto business processes, which weren’t built in the AI era, vs taking the outcome-centric approach and re-designing them from scratch. That’s because 79% of organizations state that adding AI onto existing processes creates less internal resistance, with 77% saying adapting all their most important processes for AI will take up to five years.
Growing Governance and Compliance Exposure
The report reveals that legacy or poorly designed processes are a leading contributor to the AI-related compliance and governance failures insurance firms already face.
- 26% of organizations have suffered an AI-related compliance or governance issue in the past 12 months. And process-related issues have contributed to the vast majority (89%) of them.
- One in five (18%) organizations fear AI agents going rogue if they make changes to a process.
- 79% of employees fear that their use of AI will lead to a compliance issue in their organization and almost all (99%) expect process challenges will contribute to future AI-related compliance issues.
The Leadership-Employee Gap
Employees are also feeling the impact of AI being introduced into processes that were never designed for it. Many are left to absorb the friction, quietly working around the AI tools that were supposed to make their jobs easier. So while 88% of insurance organizations say AI is making their teams more productive, only 57% of employees agree.
In fact, a quarter (26%) of organizations say they have rolled back on the use of AI because it’s had a negative impact on employees’ ability to do their job. And the consequences go further, with 40% of employees saying they would consider changing jobs due to poorly implemented AI.
The report also reveals the following:
- 73% of employees were not fully consulted about how AI would be used to support their day-to-day work.
- 63% of employees say they could use AI a lot more effectively if it was implemented differently.
- 43% of employees say they have had to manually override AI outputs because the underlying process wasn’t set up correctly.
- 35% of employees say they have used AI to artificially comply with their organization’s AI mandate when there was no need to do so.
For more information:
About the report
Camunda commissioned Sapio Research to conduct two surveys across the US, UK, Germany, and France. This edition reports the insurance responses: 34 process decision makers, comprising senior IT, operations, and transformation leaders involved in automation and AI strategy and execution at organizations with at least 1,000 employees, and 268 employees at organizations of the same size whose day-to-day work has had AI or automation introduced into it. Both surveys were conducted online in July and August, 2026.
65% of Insurance Organizations Say Process-Related Challenges Have Caused AI Initiatives to Fail and it is Costing Them Millions
Posted in Commentary with tags Camunda on September 16, 2026 by itnerdNew research from Camunda, the enterprise platform for agentic orchestration, has revealed how broken business processes are causing AI initiatives to fail at a staggering rate. According to the report, The AI Process Gap, 65% of insurance organizations say that process-related challenges have caused AI initiatives to fail at an average cost of $1.40 million per business. Furthermore, another two thirds (65%) say that AI costs will spiral unless they gain better control over their business processes, with 79% believing that their AI investments will be a bust without more investment in process re-design.
The report highlights how many insurance organizations are attempting to bolt AI onto business processes, which weren’t built in the AI era, vs taking the outcome-centric approach and re-designing them from scratch. That’s because 79% of organizations state that adding AI onto existing processes creates less internal resistance, with 77% saying adapting all their most important processes for AI will take up to five years.
Growing Governance and Compliance Exposure
The report reveals that legacy or poorly designed processes are a leading contributor to the AI-related compliance and governance failures insurance firms already face.
The Leadership-Employee Gap
Employees are also feeling the impact of AI being introduced into processes that were never designed for it. Many are left to absorb the friction, quietly working around the AI tools that were supposed to make their jobs easier. So while 88% of insurance organizations say AI is making their teams more productive, only 57% of employees agree.
In fact, a quarter (26%) of organizations say they have rolled back on the use of AI because it’s had a negative impact on employees’ ability to do their job. And the consequences go further, with 40% of employees saying they would consider changing jobs due to poorly implemented AI.
The report also reveals the following:
For more information:
About the report
Camunda commissioned Sapio Research to conduct two surveys across the US, UK, Germany, and France. This edition reports the insurance responses: 34 process decision makers, comprising senior IT, operations, and transformation leaders involved in automation and AI strategy and execution at organizations with at least 1,000 employees, and 268 employees at organizations of the same size whose day-to-day work has had AI or automation introduced into it. Both surveys were conducted online in July and August, 2026.
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