The AI paradox in BFSI: The tech is moving fast, but the workforce isn’t
By Asmita Dube, Director – BFSI, Great Place To Work India
BFSI is not short on ambition right now. We do see AI adoption picking up, digital investments getting more serious, and leadership conversations centring on transformation. But underneath this momentum, there is a quieter problem that is starting to shape what execution looks like on the ground. The technology is moving faster than the workforce is being enabled to keep up.
Illusion of readiness:
As organisations move past experimentation and begin talking seriously about scale, our research highlights an illusion of readiness. While 83% of organisations say digital transformation is a priority, only 31% believe their workforce is ready to deliver on it.
There is a clear mismatch between how fast organisations are investing in technology and how slowly their people systems are evolving around it: strong intent, visible activity, and patchy execution.
The biggest barriers to AI in BFSI are no longer just about technology, regulatory restrictions, infrastructure, or even budget. Our research shows that these challenges definitely exist (1 in 3 organisations still see implementation complexity and cost as a challenge), but many organisations are already starting to work through them.
The real friction now sits somewhere else. Our research shows that:
One in three organisations say they do not yet have enough AI-ready talent internally. At the same time, intent is soaring, with 1 in 3 CHROs saying they are highly likely to scale AI adoption in their daily workflows over the next three years .
What is even more interesting is that employees themselves are not pushing back.
– 83% of employees feel positive about AI
– 87% see automation as a clear productivity win
– 67% want more training, experimentation, and guidance
That is what makes the paradox so sharp. Employees are open to AI. Leaders are investing in AI. But the system around them is still not enabling either at the pace required.
Where the real bottleneck lies: Enablement
That is why the real constraint in BFSI today is not whether AI can be implemented. It is whether people can work with it well.
And that comes down to two very real gaps.
– Roles are changing quickly
Across BFSI, AI is already changing the nature of work. Risk and credit roles are moving from manual judgment to real-time, AI-supported decision-making. Lending workflows are becoming more automated. Claims and underwriting are increasingly AI-assisted.
But many organisations are still running on legacy job structures.
So, what teams experience in practice is simple: new expectations layered on top of old roles. And when roles are not redesigned, AI does not really simplify work. It often creates more complexity, more rework, and more hidden stress.
– Learning is still reactive in many areas
The second bottleneck is capability building.
Nearly 50% of the BFSI workforce is expected to need reskilling in the coming years, but learning systems are still not moving at the speed of the shift. Nearly 70% of employees learn only what their current role requires, while only 7% are learning proactively for what is coming next.
That creates a constant capability lag. Teams keep catching up instead of building ahead. In an AI-led environment, that is not a small inefficiency. It becomes a direct limit on execution speed.
In conclusion
If enablement is the real constraint, then the answer is not simply more technology. It is about rethinking how work is designed and supported.
That means three shifts matter most.
- Redesign work, not just workflows: AI adoption must come with role clarity, better decision rights, and success metrics that reflect AI-augmented work.
- Shift from learning programs to learning speed: Capability building must happen in the flow of work, not as a side initiative. The real metric is no longer course completion. It is time to role readiness.
- Treat leadership as the engine of execution: Leaders need to enable teams to execute change sustainably, while balancing speed, compliance, and care.
The future of BFSI will not be decided only by how quickly organisations deploy AI. It will be decided by how well they prepare their people to work with it.
So as the sector moves into its next phase of growth, the real question is no longer:
“Are we adopting AI fast enough?” Rather, it is: “Are our people, roles, and leaders actually ready to perform in an AI-enabled system?”
Until organisations answer that honestly, the paradox may not go away.