Threat or opportunity? How asset managers are making AI work

When it comes to asset managers’ top concerns, technology disruption has jumped to the front of the queue. Front of mind for 37% of responders last year, it’s now the number one concern for 53% of senior asset managers we surveyed.  

It’s not just in their heads. In the same time frame, artificial intelligence has quietly moved from boardroom speculation to operational reality. 

Only 26% of UK asset managers see AI stuck in pilot phases, whilst 69% are actively using it in some form across their operations. The question is no longer whether AI works in asset management, but how firms can implement it most effectively.  

The proof-of-concept era is over 

The numbers tell a story of rapid maturation: 

• 31% actively using AI in specific functional areas 
• 22% deployed broadly across operations 
• 16% fully integrated into core business processes 

The firms that spent the last year experimenting are implementing whilst the quarter of firms still in exploration now face an uphill battle to close the adoption gap. 

Why technology became urgent 

Asset managers are watching competitors automate regulatory workflows whilst they still manually process compliance requirements. They're seeing peers launch products in weeks whilst their own time-to-market stretches across months. 

Data disruption and tech segmentation is a nightmare for operational efficiency. Clients expect real-time portfolio insights and immediate responses to market volatility. Regulators demand transparent, auditable processes that adapt to changing requirements instantly. Distribution partners require seamless integration and rapid product deployment. 

Firms relying on legacy systems and manual processes run the risk of becoming inefficient in an era when efficiency begets relevance.  

The data foundation reality 

Here's the challenge most firms underestimate: 90% of asset managers recognise data as critical to decision-making, yet 67% regularly experience delays due to data availability or accuracy issues. 

Since AI systems are only as effective as the data that feeds them, firms with fragmented systems and inconsistent data flows find their AI initiatives delivering disappointing results. Meanwhile, those with unified data architectures discover AI and machine learning amplify their operational advantages. 

This explains why 53% of senior asset managers are prioritising investment in data management and governance, up from 48% in 2024. It's not just about better reporting; they are building the foundation that makes all future AI implementation successful. 

Real applications that work 

Leading asset managers are deploying AI across practical use cases that deliver measurable results: 

• Investment research is being transformed as AI accelerates the processing of vast data quantities, enabling professionals to generate unique insights faster than ever. Machine learning algorithms are optimising portfolio allocation based on specific investor profiles, moving beyond one-size-fits-all approaches. 
• Regulatory compliance sees dramatic efficiency gains as AI systems intelligently map disclosure requirements and automatically update documentation across jurisdictions. Manual compliance reviews that once took weeks now happen in real-time. 
• Client engagement becomes personalised at scale, with AI directing clients to appropriate product recommendations whilst customising communication based on individual preferences and behaviours. 

The result goes beyond efficiency to better client outcomes with reduced operational risk. 

The equalising effect of artificial intelligence  

AI adoption doesn’t seem to be following traditional technology patterns. The firms furthest along aren't necessarily the largest or best-funded, but they are the ones that built proper data foundations first. 

Overwhelmingly, we’re seeing that AI maturity is built rather than bought. The 16% of firms with fully integrated AI achieved this by getting fundamentals right: unified data systems, streamlined workflows and clear operational processes. This creates opportunities for mid-sized asset managers to leapfrog larger competitors who may still be wrestling with legacy system complexity. The window for action 

The surge in technology disruption concerns reflects a basic feat for asset managers: that competitors are moving faster whilst they're still wrestling with basic operational challenges. 

The opportunity here is about systematic improvement. With 64% of asset managers prioritising investment in automation and digitisation, the focus has shifted from whether to adopt AI to how to implement it most effectively for your firms’ use case. 

For most firms, success comes down to addressing data infrastructure challenges first, then gradually expanding AI applications where they deliver clear operational benefits.  

Our 2025 Asset Managers Report examines the specific data architecture requirements and AI implementation priorities that enable successful digital transformation. Access detailed analysis of investment strategies, operational challenges and the practical approaches that leading firms are using to make AI work effectively. Download the report below.