Our findings predict AI agents could add up to $1.3 trillion of incremental value globally across banking, insurance, and capital markets by 2027. Already, 36% of banking organizations and 33% of insurers are experimenting or deploying AI agents in the next 6–12 months, reflecting the sector’s urgency to innovate.

The public sector is also moving quickly: Among the global public sector organizations surveyed, 91% have initiated partial implementation of agentic AI, and 67% are looking to partner with solution providers to tailor and scale AI adoption. In the next three years, 50% of public sector organizations expect AI agents to be deployed in customer service and field operations, underscoring how governments are reimagining citizen services.

But the path ahead isn’t straightforward. While visible benefits like efficiency and faster speed to market are evident, the real differentiator will be scaling responsibly. More than half of the value creation in financial services and the public sector will accrue to organizations that embed AI agents into core operations with trust and oversight at the center.

The challenge is clear: trust in AI agents is underdeveloped and, in some regions, declining.

  • In Australia, trust fell from 31% in June 2024 to 25% in April 2025.
  • In Japan, from 44% to 37%.
  • In Singapore, from 30% to 28%.

Yet, 62% of Japanese financial services organizations believe AI agents will augment human teams in the next 12 months, and nearly 78% expect them to become autonomous members within 3 years. In Singapore, 60% of public sector organizations report above-average trust during implementation, showing cautious confidence.

Human oversight remains a critical lever: 83% of Japanese, 69% of Australian, and 78% of Singaporean financial services firms plan to ensure oversight at critical points of action. In fact, across both financial services and the public sector, the top drivers of trust are accuracy, transparency, and governance, combined with the ability of human supervisors to overrule AI decisions.

Still, ethical concerns like data privacy, algorithmic bias, and the “AI black box” remain prevalent. Only half of organizations claim sufficient knowledge of AI agent capabilities, and fewer can pinpoint where agents outperform traditional AI or automation. Worryingly, fewer than one in five report high levels of data readiness, while over 80% lack mature AI infrastructure, a structural weakness that limits scaling.

The way forward for financial services and the public sector requires moving beyond pilots to large-scale transformation that empowers both the enterprise and its workforce. This means:

  • Reimagining business models by deploying AI agents effectively and ethically.
  • Fully onboarding the existing workforce to operate AI agents and future-proof their talent pools.
  • Striking the right balance across aspects of AI autonomy and human oversight.
  • Strengthening data and technological foundations to scale AI impact.
  • Setting AI agents to operate within defined societal boundaries and ethical frameworks.

The pace of adoption of AI demands clarity, speed, and accountability. Scaling responsibly requires more than enthusiasm. It requires leadership vision anchored in ethics, data, and trust. As senior leaders, we must be the architects of trust, ensuring AI agents drive sustainable growth while upholding societal and regulatory expectations. For a deeper view of opportunities, risks, and leadership actions in financial services and public sector, download the full report.

* As per Statista