Transforming investment management through AI: Our vision and use cases

Investment management is being reshaped by AI

AI is a transformative force with significant potential to change how investment managers work across their business, operating, and infrastructure models, e.g., how they communicate with clients and how they make their client and investment operations more efficient.

Clients are well advised to plan this change in a holistic manner, with some individual use cases for how AI can be used in an optimal way, considering risk, efficiency gains and priorities. Looking into some statistics, we see the following:

• 67% of investment managers are increasing their investment in AI after witnessing strong early value.¹
• More than 75% of investment managers anticipate utilising AI within their investment strategies in the next few years.²
• Early successful adoptions of AI have achieved improvements in operational workflows of about 50% (e.g., trade matching, settlement, document processing).³

Our vision for the future of investment management

Based on our client and market insights, we have formed a vision of how AI enablement may transform investment managers’ business and operating models:

• Portfolio management: From data interpretation to alpha generation
  Investment managers leverage data streams to generate alpha, better risk and return profiles, and predictive capabilities through human-AI collaboration. Portfolio managers work alongside AI agents to interpret and validate insights, enabling higher performance and cost savings through automation of trade execution, and research.
• Operations: Automation for efficiency and scalability
  AI transforms middle and back office workflows through agentification of manual processes (trade matching, settlement, document processing) while simultaneously strengthening regulatory compliance and risk management. AI-supported workflows/systems reduce errors, cut costs of manual activity, and enable rapid adaptation to market shifts, regulatory changes, and AuM growth, delivering both operational efficiency and regulatory excellence.
• Client relationship management: Tailored and proactive partnership
  AI enables tailored recommendations, marketing, to transform the client experience. This allows client relationship managers to focus on deepening client relationships while AI handles personalisation at scale.

Prerequisites for bridging vision and implementation

To fulfil AI's transformative potential, organisations must embark on the transformation with a holistic view, including laying the ground from a data and AI literacy perspective. A robust, clean, and accessible data infrastructure is often the starting point, and an organisational AI literacy is required to enable effective change management and human-AI collaboration.

AI use cases along the value chain

In the following paragraph, we outline selected use cases that we have worked on with clients, either already fully implemented or in development.

• The AI-powered Request-for-Proposal (RFP) generator supports sales activities by analysing incoming RFPs, matching client requests against asset and corporate data, and generating an automated response suggestion for the front office. This reduces manual effort, accelerates client proposals, and lowers costs.
  

• The Unify Compliance Workflow solution imports and reads investment contracts (via OCR) and fund documents, then uses AI to generate investment guidelines. It checks what rules are currently coded in the trading system and compares them against these AI-generated rules, identifying critical gaps and discrepancies. The delta, highlighting where coded rules diverge from the actual guidelines, is then shared for expert review and remediation. This solution unlocks better portfolio performance and reduces risk while eliminating manual work.

Conclusion: Growing with AI

We have observed different approaches to embark on an AI journey. Deloitte is uniquely positioned to provide you tailored advice about where to start and what to tackle. The transformation has started and there is no way back: AI will change how investment managers are working.

Authors

• Daniel Hirs, Partner, Investment Management
• Ueli Preisig, Director, Investment Management Lead Switzerland
• Diana Mayrhofer, CFA, Senior Manager, Investment Management
• Michiel Simonis, Manager, Investment Management