Generative AI in risk and compliance 2025

Why risk management is the key to unlocking AI value

This report examines the role of risk and compliance in the AI revolution, supported by a comprehensive program of primary research: 

  • A survey of 224 senior risk and compliance professionals across the UK and US.
  • Evaluations of 620 applications of GenAI across risk and compliance.
  • Interview insights from eight named industry experts.

Download this new research report to learn why risk management is the key to unlocking AI value!

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98% of compliance leaders say that GenAI is creating new or intensified risks.

Download the full report to learn:
  • Which risk domains are most challenged by GenAI — and why.
  • Which risk workflows are most enhanced by GenAI — and how.
  • Why governance, risk, and compliance are key to achieving ROI on GenAI.
"AI is moving at a pace that outstrips formal policymaking. Most companies are attentive to the risks, but governance mechanisms need to keep evolving in parallel with model releases."
Su Cizem
AI Policy Fellow, Institute for AI Policy and Strategy​
"Most companies are pursuing efficiency gains with GenAI, but leader believe the real value... will accrue from applications that transform the effectiveness of the business functions."
McKinsey
GenAI in corporate functions: Looking beyond efficiency gains

Meet the experts...

Chapters

01

The ROI paradox and the path forward

GenAI promises efficiency in risk and compliance, yet short-term ROI remains elusive due to integration and regulatory hurdles. This chapter unpacks the paradox, showing initial gains in decision-making precede measurable returns. It proposes phased adoption, cross-functional teams, and long-term metrics to guide leaders toward sustainable, value-driven GenAI transformation.

02

Current state of GenAI in risk and compliance: survey results

Drawing from a comprehensive survey of 224 risk and compliance professionals across finance, healthcare, and tech sectors, this chapter reveals the nascent yet accelerating adoption of GenAI. Key findings include 62% of respondents piloting AI for fraud detection and regulatory reporting, but only 28% achieving measurable ROI, citing data silos and skill gaps as barriers. Adoption varies by industry, with finance leading at 45% full integration. The results underscore optimism—78% anticipate 30% efficiency boosts within two years—while flagging ethical concerns like bias amplification, providing a benchmark for benchmarking progress.

03

Building ROI with elite risk management: analyst view

Analysts from Deloitte and PwC highlight elite teams using GenAI to cut audit times 40% via scenario modeling and predictive risk tools. Success stems from strong governance, domain-trained models, and human-AI synergy. They provide ROI frameworks blending cost savings and reduced exposure for scalable impact.

04

Key challenges for the industry to overcome: expert perspectives

Industry luminaries from Gartner, McKinsey, and regulatory bodies converge in this chapter to candidly address GenAI's thorniest challenges in risk and compliance. Foremost are explainability deficits, where "black-box" models hinder auditability, and escalating cyber threats from AI-generated deepfakes. Experts decry fragmented regulations, with 70% advocating global standards akin to GDPR for AI. Perspectives also tackle talent shortages and ethical dilemmas, like algorithmic bias perpetuating inequities. Solutions proposed include interdisciplinary upskilling, federated learning for privacy, and collaborative sandboxes for testing. Overcoming these is pivotal for GenAI's trustworthy proliferation.
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Authors
Parker & Lawrence Research
Type
Industry Report
Layout
PDF