AI Alone Will Not Win. Workforce Transformation Will.
Workforce transformation
QUICK TAKE: In insurance, AI investment alone doesn't drive results — organizations that pair AI with workforce redesign, upskilling, and change management are the ones seeing real gains. Farmers Insurance freed up 16.4 million hours annually not by cutting roles, but by using AI to eliminate low-value tasks and redirect people toward higher-value work.
Across the insurance industry, AI is still too often framed as a technology play or a cost-cutting opportunity. But the firms that come out on top are more likely to be the ones that use AI to redesign work, strengthen human capability, and lead change intentionally.
Why AI Investment Alone Isn't Enough
Recent industry signals make that clear. LIMRA/LOMA argues that AI implementation is fundamentally a workforce transformation, not just a technology challenge — and notes that while insurers are increasing AI investment, far fewer have redesigned roles or prepared employees for new ways of working. Deloitte has found similar gaps: most insurers have already deployed generative AI in at least one function, yet many still struggle to turn use cases into enterprise value.
What Better Looks Like: The Farmers Insurance Example
Farmers Insurance offers a practical example. By asking agents which tasks weren't adding value, the company used AI to reduce routine servicing work by 35%, freeing up roughly 16.4 million hours annually for sales and customer relationships. Importantly, this wasn't achieved by cutting roles — it was achieved by shifting people toward higher-value work.
Where Change Leadership Comes In
AI is reshaping tasks, roles, and expectations faster than many organizations are redesigning workflows, upskilling talent, and preparing managers to lead through the shift. That gap is where change leadership matters most.
FlexPaths is actively supporting insurance organizations through this kind of transformation. In one current engagement, a core people process is being redesigned, requiring leaders and employees to adopt new workflows, responsibilities, decision points, and system-supported ways of working.
The process redesign itself is only part of the challenge. The equally important work is:
Helping people understand what is changing and why
Preparing leaders to communicate and lead differently
Building role-based training and tools
Establishing clear support pathways
Continually assessing readiness and reinforcing adoption
The Real Lesson: Implementation Is Not Adoption
That experience reinforces an important lesson for AI transformation: implementation is not adoption. New technology creates value only when people understand how their work is changing, feel capable of operating differently, and have the leadership, support, and reinforcement to make new behaviors stick.
As Jill Semegran, one of our lead strategists, puts it:
"The winners will be those who pair AI with workforce planning, capability building, and strong change management — creating efficiencies, improving performance, and better positioning both their people and their business for the future of work."