Proven impact has prompted financial services firms to deepen their commitment to AI—and double down on their investment. In our conversations with industry executives, we’ve heard myriad stories about scaling AI, from ROI victories to how they’re tackling roadblocks.
Here are our six takeaways:
1. AI is rewriting the rules
AI is evolving at breakneck speed, transforming how value is created and delivered. Inaction is now a liability; it’s time to act boldly—and fast.
2. The ROI’s there—but that’s just the start
Though many cases are already delivering results, enduring impact requires structural change. To scale AI, start by refining processes, roles, and workflows.
3. Make AI core to the business
It’s time to rethink the business model, not just the tools. Unlocking full value means embedding AI into core operations and rebuilding capabilities with digital workers and AI agents in mind.
4. The “lab and the crowd” model gains traction
Momentum is building around a dual-track strategy for scaling AI, pairing centralized innovation focused on big bets (the lab) with decentralized, employee-led development (the crowd).
5. Address scale barriers now
A lack of governance, trust, and talent—not to mention the fear of change— are real obstacles to scaling AI. Tackle them with intentional investment and culture change.
6. Deeper tech and data questions remain
Key decisions around AI orchestration, memory, guardrails, cloud strategies, and legacy integration remain open—and critical.
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