Contents

Foreword 3

Executive summary 4

Introduction 5

1 The landscape today 7

1.1 Context and industry outlook 8

1.2 AI spending trends and prioritization 10

2 Investment and maturity of the industry 12

2.1 Business-driven adoption models 13

2.2 Aligning AI to strategy 13

2.3 Measuring AI value 15

2.4 Pilots versus scaled programmes 16

3 Successful AI starts with a strong foundation 17

3.1 The foundation and platform architecture 18

3.2 Skills, hiring and culture change 19

3.3 Governance, risk and compliance management 20

3.4 Security, model risk and threat landscape 23

4 The role of agentic systems in unlocking value at scale 24

4.1 Why agentic AI is key 25

4.2 Human–AI partnership 25

4.3 Examples of agentic AI in financial services 27

5 Planning for the industry’s future 32

5.1 Emerging technologies and cross-industry innovation 33

5.2 Framework for scaled and sustained AI adoption 33

5.3 Leadership, sponsorship and accountability 35

Conclusion 36

Appendices 37

A1 Overview of risk framework adoption by region (non-exhaustive) 37

A2 Overview of AI-driven risks and corresponding 39

risk management approaches

A3 Additional reading 40

Contributors 41

Endnotes 47