AI Leadership Forum: AI Maturity & emerging regulatory issues

The rapid evolution of artificial intelligence (AI) is reshaping financial services, from investment management to compliance and AI-driven automation. Our recent AI Leadership Breakfast Forum brought together industry leaders to explore the intersection of AI, regulation, Agentic AI, and strategic implementation. Below are some of the key discussion points and findings we observed about AI in Investment Banks and Wealth Management firms.

AI and Regulation – A Balancing Act

The evolving regulatory landscape is both a challenge and an opportunity for financial services firms looking to adopt AI. While regulations aim to enhance consumer protection—ensuring every customer receives the same level of service—compliance requirements can slow adoption.

Key discussion points:

• Consumer Duty: AI presents an opportunity to help firms comply with regulatory requirements, but it requires support from regulators like the FCA.
• RegTech and AI: Can regulatory technology (RegTech) help solve the compliance challenges that AI presents? Many participants saw co-creation between fintech startups and banks as the key to managing liquidity and mitigating risk.
• Big vs. Small AI Firms: Larger investment management firms are cautious, favouring established fintechs over newer startups. In contrast, smaller firms are actively engaging with AI-driven fintechs to reduce risk and optimise business operations.
• Fintech Funding Gap: Despite the UK's advanced fintech ecosystem and the great work coming out of universities, funding remains a challenge. Compared to the US, UK startups struggle to secure investment, limiting innovation and competition.

While AI presents a path to improving regulatory compliance, firms must also navigate internal challenges such as data security, risk stacking, and evolving compliance frameworks.

Agentic AI – The Next Competitive Advantage

One of the most compelling discussions centred on Agentic AI—the concept of AI agents collaborating autonomously to enhance decision-making and efficiency. Unlike traditional AI, which automates workflows, agentic AI creates an entirely new workforce of synthetic workers.

Use cases explored:

1. Insurance Transformation: A major insurance firm deployed AI agents to handle compliance and GDPR processes. These agents collaborated with humans via Slack and Teams, interacting with IT systems and providing feedback. The result? A 2% revenue increase and dramatically improved loss ratios.
2. Regulatory Insourcing: AI agents replaced expensive consultants, completing complex procurement tasks in hours rather than weeks—delivering faster, cheaper, and higher-quality results.

Key takeaways:

• AI agents can significantly reduce operational costs, automate regulatory compliance, and improve efficiency.
• However, AI adoption should augment human intelligence rather than replace it—firms that integrate AI into decision-making rather than replacing humans altogether see the greatest benefits.
• Agentic AI is still widely misunderstood—most IT teams have little knowledge of its full potential, highlighting the need for education and awareness.

Analysts predict that agentic AI could be 10 times bigger than the SaaS market, making it one of the hottest topics in 2025, alongside AI return on investment (ROI).

AI Strategy and Roadmaps – Where Should AI Sit?

Firms are increasingly focused on AI’s return on investment (ROI) and how to measure success. The discussion identified several key challenges in AI adoption:

• Proof-of-Concept (POC) Fatigue: Many firms experiment with AI without scaling it, leading to stagnation. A balanced scorecard approach—using KPIs aligned with business objectives—can help overcome this hurdle.
• AI in Investment Banking vs. Asset Management: Some asset managers are moving ahead in AI adoption now.  Banks remain cautious, largely due to regulatory and risk concerns, though MS co-pilot adoption now appears to be widespread across the sector.
• Data Access & Ethics: AI adoption requires structured, repeatable, and well-documented processes. However, access to quality data remains a significant barrier. Ethical concerns around AI decision-making and ESG considerations were also raised.
• Legal & Compliance Challenges: AI adoption is being driven at the VP level and below, with AI-powered tools like CoPilot gaining traction. However, AI’s integration into legal frameworks and document processing needs further development.

Looking Ahead: The Role of NextWave

As AI adoption accelerates, organisations will need strategic guidance to navigate regulatory, operational, and technological challenges. NextWave has deep expertise in AI-driven financial services solutions, having built regulated onboarding platforms and workflow automation for global financial institutions.

Key areas where NextWave can support:

• Regulatory Compliance & AI Governance: Helping firms deploy AI solutions that meet evolving regulatory requirements.
• AI Strategy & Implementation: Driving AI adoption with measurable ROI and scalable use cases.
• AI Enablement: Assisting firms in leveraging AI agents to transform operations.

Future Round Tables: What’s Next?

The discussion raised several key themes for future round tables, including:

• Governance & AI Ethics: Best practices for managing AI-driven decision-making.
• AI’s Role in Workforce Transformation: Balancing automation with human expertise.
• The Future of Fintech & RegTech: How startups can collaborate with incumbents to drive innovation.

As AI continues to disrupt financial services, the firms that embrace AI strategically—while aligning with regulatory and ethical considerations—will emerge as industry leaders.