Key Takeaways
- • Deloitte's 2027 Investment Management Outlook argues that the traditional advantages of investment managers, namely strong performance, broad distribution, and steady margins, are being reshaped toward a "balanced firm" model combining insight- and speed-driven investing, partnership-minded product teams, human- and machine-led distribution, and high-quality data.
- • Deloitte expects M&A activity among investment managers to increase over the next 18 months as firms pursue scale, new geographies, product capabilities, and distribution.
- • Deloitte's State of AI Survey found 68% of financial services firms cited improved efficiency and productivity from AI, 40% reported cost reductions, and only 18% reported increased revenue from AI, while 75% hoped AI would lift future revenue.
- • Deloitte projects the average AI budget at financial services firms could more than triple by the end of 2028, and warns that token consumption could rise sharply, with 70% of firms expecting to exceed 10 billion tokens per month in 2028 versus 36% expecting that level in 2026.
- • Deloitte contends that as AI commoditizes analytics through reliance on a few leading large language models, differentiation will shift toward proprietary information, human judgment, and institutional memory.
Summary
Deloitte's 2027 Investment Management Outlook argues that investment managers must rebuild their operating models for a faster industry. The traditional advantages of strong performance, broad distribution, and steady margins are increasingly insufficient on their own. Deloitte describes a "balanced firm" that brings together insight- and speed-driven investing, nimble product teams, joint human- and machine-led distribution, and high-quality data that drives continuous transformation.
Consolidation is a central theme. According to Deloitte, investment managers are pursuing mergers and acquisitions globally to increase scale, enter new geographies, add product capabilities, and improve distribution, and deal activity could increase over the next 18 months. Greater scale may also give firms more capacity to invest in technology and data for investment analysis, client service, and risk management. Deloitte says firms face competing priorities, including growing revenue while protecting margins and personalizing at scale without losing control. Sustaining this progress, the report argues, depends on treating data as a competitive asset, simplifying ways of working, sharing change leadership across functions, and embedding governance, incentives, and talent into decision-making.
On AI, Deloitte expects enterprise-scale adoption to become a business imperative as firms move beyond experimentation. Citing its State of AI Survey, Deloitte reports that 68% of financial services firms cited improved efficiency and productivity, 48% noted better decision-making, 46% cited stronger client relationships, and 40% reported cost reductions. However, only 18% reported increased revenue from AI, although 75% hoped AI would increase future revenue. Deloitte projects the average AI budget at financial services firms could more than triple by the end of 2028.
Deloitte also warns that AI costs could rise quickly over the next 12 to 18 months if not managed well, as AI moves into critical workflows such as investment research, valuation, and due diligence. While cost per token is expected to decline, total consumption is likely to rise sharply: 70% of financial services firms expect to exceed 10 billion tokens per month in 2028, compared with 36% expecting that level in 2026. Citing a separate Deloitte publication, the report states that roughly 7 billion tokens per month is the point at which on-premises hosting becomes more cost-effective than API access, packaged products, or neocloud providers.
Finally, Deloitte argues that as firms rely on the same few leading large language models, analytics may become commoditized, reducing differentiation in investment thinking. Differentiation may shift toward proprietary information and human judgment, including industry conversations, fieldwork, proprietary research, and institutional memory.
Consolidation is a central theme. According to Deloitte, investment managers are pursuing mergers and acquisitions globally to increase scale, enter new geographies, add product capabilities, and improve distribution, and deal activity could increase over the next 18 months. Greater scale may also give firms more capacity to invest in technology and data for investment analysis, client service, and risk management. Deloitte says firms face competing priorities, including growing revenue while protecting margins and personalizing at scale without losing control. Sustaining this progress, the report argues, depends on treating data as a competitive asset, simplifying ways of working, sharing change leadership across functions, and embedding governance, incentives, and talent into decision-making.
On AI, Deloitte expects enterprise-scale adoption to become a business imperative as firms move beyond experimentation. Citing its State of AI Survey, Deloitte reports that 68% of financial services firms cited improved efficiency and productivity, 48% noted better decision-making, 46% cited stronger client relationships, and 40% reported cost reductions. However, only 18% reported increased revenue from AI, although 75% hoped AI would increase future revenue. Deloitte projects the average AI budget at financial services firms could more than triple by the end of 2028.
Deloitte also warns that AI costs could rise quickly over the next 12 to 18 months if not managed well, as AI moves into critical workflows such as investment research, valuation, and due diligence. While cost per token is expected to decline, total consumption is likely to rise sharply: 70% of financial services firms expect to exceed 10 billion tokens per month in 2028, compared with 36% expecting that level in 2026. Citing a separate Deloitte publication, the report states that roughly 7 billion tokens per month is the point at which on-premises hosting becomes more cost-effective than API access, packaged products, or neocloud providers.
Finally, Deloitte argues that as firms rely on the same few leading large language models, analytics may become commoditized, reducing differentiation in investment thinking. Differentiation may shift toward proprietary information and human judgment, including industry conversations, fieldwork, proprietary research, and institutional memory.
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