科技的未来：生成式AI在资产管理中的应用——2030年AI原生资产管理公司

Future of Tech: Gen AI in Asset Management...The AI-NativeAsset Manager of 2030 In our last Future of Tech report, we presented 5 key trends for next 5yrs ie. multi-foldincrease in AI adoption in back/middle office functions, more AI-led product launches, AI toaugment (not replace) investors, discretionary funds to benefit more than quants, and, ‘AI as aservice’ (AIaaS) to become a key enabler. As AI adoption continues to increase (c.50%-60%now within LOs), we share 5 more trends on the impact of AI in asset management: Rupal Agarwal+65 6326 7641 AI-Native Investment Process:By 2030, we expect AI-first framework to emerge,consisting of: 1) AI-powered idea generation, 2) Automated research synthesis, 3) AIstress tested thesis that gets endorsed or challenged by analyst, 4) AI-optimized portfolioconstruction, and, 5) Continuous portfolio monitoring with AI flagging risk breaches andpreparing exception reports for human review. Workforce transformation: AI-Analyst & AI-PM of 2030:IMF estimates that 40% ofglobal employment is exposed to AI. We expect a hybrid AI/human workforce to speed-upthe flattening of hierarchies as the analyst’s role transforms into that of research directorand AI supervisor (formulating investment hypothesis, directing multi-agent system,evaluating and challenging AI-generated outputs and providing qualitative synthesis)while the PM's role evolves into an allocator & AI orchestrator (spending less time on ideageneration, research, portfolio management and monitoring and more time on convictionbuilding, governance of AI agents and bringing differentiated insights). Impact on market-structure:We expect 5 key impacts-1) Information asymmetrydecreases as AI democratizes access, 2) Buy-side/sell-side shift towards fewer butdeeper relationships with increased attention on ‘super forecasters’, proprietary researchand interpersonal skills, 3) Institutional investors retain structural advantage (ultra-lowlatency trading/access to dark pools) but retail investors gain more power, 4) The linebetween quants and fundamentals blur as AI brings both breadth and depth, 5) Systemicvulnerabilities increase through higher crowding and concentration risk. The profitability paradox. Large & small asset managers likely to benefit:AUM forthe top 50 global asset managers grew at 7% CAGR in the last 10yrs vs. revenue growthof 4%pa and margin growth at 2% CAGR; while fees compressed (c.34bps in US) led bymigration to passives, rising tech spend and regulatory burden. With AI, we believe, the pieof true alpha would further squeeze, making cost the most credible survival lever (McKinseyestimates 25-40% of AI led cost savings). We believe, large (tech leverage) and small(agile/sharper AI-led insights) asset managers are at an advantage while mid-sized firms($300bn-$500bn) could find it hard to compete as shown in BCG's 2025 analysis. AI-Native Alpha:In an AI era, while investors would have to work harder to generate alpha,there are 4 broad opportunities that can be tapped into: coverage and speed alpha, insightalpha, system alpha and human alpha. This comes from AI helping to expand coverage,accelerating time to market and unlocking unique insights alongside the agility of anenterprise to find/build AI solutions while creating structured governance frameworks andbringing differentiated orchestration of AI agents. DETAILS In our last year’s Future of Tech : Gen AI in Asset Management report, we presented 5 key trends that we expect to emerge: 1)Multi-fold increase in AI adoption in the back and middle office functions, 2) Increased number of pure AI led strategies comingto market, though burden of proof remaining quite high on AI vs. human out performance, 3) AI to augment (not replace) humaninvestors as a bigger man+machine world emerges, 4) Increased opportunities for quant investors but a much lower bar fordiscretionary investors to incorporate AI in their investment processes, 5) AI as a service to become a core product throughmore sophisticate and agentic vertical AI for finance products. As Gen AI adoption in asset management continues to increase (from 35% back in 2024 to c.50%-60% now), we build onto ourlast year’s report to share 5 more trends on the future of AI in asset management: 1. Emergence of AI-Native Investment Process:By 2030, we expect, leading asset managers to operate under afundamentally restructured investment workflow — not AI layered onto the old process, but AI-first by design which wouldinclude: 1) AI-powered idea generation with AI agents scanning filings, earnings transcripts, alternative data, news flow etc. tosurface signals while the analyst reviewing the ideas. 2) Automated research synthesis with AI querying internal and externalknowledge base, producing a structured research document. 3) AI stress tested thesis where PM/senior analyst appliescontextual judgment to either endorse or challenge it. 4) AI-optimized portfolio construction where AI run scenario analysis,optimi