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The conversation around AI in financial services is evolving. Until recently, much of the industry’s focus has been on testing standalone AI tools, typically “bolted on” to existing platforms. But as portfolios become increasingly complex and the investment management landscape continues to develop, firms are moving towards broader AI implementation to help streamline workflows, automate manual processes and enhance efficiency.
So where is AI headed in the next five years?
Today, 72% of financial services CEOs identify generative AI as a top investment priority¹, yet the firms that successfully scale will be those that use intelligence to deepen their connection to data and their clients. The need to shift from AI adoption to integration is becoming clear, and strategic value in this next phase won’t come from replacing human expertise — it will come from amplifying it.
The need to shift from AI adoption to integration is becoming clear, and strategic value in this next phase won’t come from replacing human expertise — it will come from amplifying it.
Five AI trends for executives
Intelligence becomes integrated
Until recently, AI has typically been accessed as a separate tool or sidebar — an external assistant that often requires users to move data out of their native technology platform to use the tool. This can cause a security-risk, become time-consuming and cause data fragmentation.
Over the next five years, we expect a continued shift towards embedded intelligence, where AI-native capabilities live directly within the workflows investment teams already use. Whether it’s a portfolio review or a complex approval chain, clarity should be a native feature of firms’ portfolio management platforms.Trust and explainability as a non-negotiable
As AI-generated insights begin to inform significant investment decisions, firms are shifting focus from the power of the model to how trustworthy the data is. Considering the importance of security in the investment management industry, alongside the compliance and regulatory environment firms are operating in, there is likely to be a trend towards transparency and traceability in AI-generated insights.
Research shows that inadequate data quality and availability remain the largest obstacles to AI adoption in finance², suggesting the future will bring systems that ground every insight in a firm’s own verified data.Permission-awareness grows more important
The importance of AI permission-awareness is set to grow. Firms cannot integrate intelligence that is blind to permissions and roles, to ensure data and information security is maintained across organisations and with external clients. This means AI will become increasingly permission-aware by understanding not just the query, but who is asking and what they are authorized to see.
A shift from passive to active
AI is evolving to provide value by surfacing what requires attention before being asked and before a problem arises. More traditional AI tools are reactive meaning firms must prompt or search for solutions.
By contrast, a platform that identifies emerging portfolio risks or unusual trends in private market valuations allows professionals to act faster. This can act as a second set of eyes, helping investment teams stay ahead of market shifts so they can support clients to make smarter investment decisions.Vertical intelligence built for specificity
General-purpose AI tools may struggle with the nuances of private market data and complex ownership structures. The next wave of AI technology belongs to "vertical AI"— intelligence trained specifically for the investment industry’s workflows.
Investment in this area is accelerating; Deloitte reports that 74% of organizations invested in AI capabilities over the past year³, a 20-percentage-point lead over any other technology. As AI adoption accelerates, firms are recognizing that impact comes from how intelligence is applied. When it is grounded in industry-specific data and embedded in real-world workflows, it delivers more meaningful outcomes than standalone generalized tools.
Conclusion
While these AI trends are on the horizon, the most effective AI strategies are likely those built to amplify human expertise. People play a crucial role in investment management, nurturing client relationships, performing high-level analysis and understanding the specific needs of a client or the long-term goals of a firm.
By streamlining workflows, enhancing data management and automating time-consuming manual processes, AI gives professionals the time to focus higher-value work. As the industry and technology continues to evolve, the importance of human expertise is a trend that looks set to stay.
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