Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Artificial intelligence is moving rapidly from experimentation into everyday use across financial services. From client servicing and research to operations and risk analysis, AI is increasingly embedded in core workflows. This shift is widely recognised within the industry. Recent research indicates that 67% of financial services organisations report rapid AI adoption, with 93% ranking AI as a top security priority heading into 2026. At the same time, governance structures are being established.

RSA Conference 2026 made one thing clear very quickly. Security leaders are done with generic AI pitches. After two years of relentless “AI everything,” the market is now pushing back. There is a growing fatigue with vague promises, surface-level features, and what many are calling outright AI washing. The result is a trust gap. What cut through this year was not another AI-powered detection claim. It was a much more grounded question.

For channel partners, AI has quickly moved from a future conversation to a current customer problem. Clients are already using AI across their organisations, often faster than governance can keep up. What’s emerging is not just another technology trend, but a new class of risk that customers cannot fully see or control. Our latest research, based on insights from senior security leaders in highly regulated industries, highlights the scale of the issue.

There is a structural shift happening in enterprise environments that most security leaders recognise, but few have fully adapted to. AI is now embedded, decentralised, and operating across core workflows. At the same time, governance models are still largely built on assumptions that no longer hold: that tools are known, data flows are observable, and behaviour follows policy. The result is a widening gap between perceived control and operational reality.