The agentic AI edge: How financial asset managers can manage change in a shifting industry
The asset management industry holds immense influence, with global assets under management reaching approximately $128 trillion in 2024 and expected to hit $145 trillion by 2025. Yet, its size doesn't guarantee ease of operation. Changes in technology, investor expectations, and new market entrants are pushing asset managers to rethink traditional approaches.
Who’s disrupting whom?
For years, a handful of major players controlled nearly half of the global assets under management. Today, the field is more crowded:
- Alternative asset managers such as private equity and hedge funds are attracting new interest through diverse offerings.
- ETFs (Exchange-Traded Funds) offer passive strategies linked to indexes at lower fees, challenging conventional models.
- Quant funds use algorithms and mathematics rather than relying on human judgment.
- Fintech companies have made wealth services more accessible and streamlined onboarding.
- Investment platforms provide utility-style access and distribution models.
These players combine technology, cost efficiency, and ease of access to chip away at the traditional market share.
Mounting pressures and industry gaps
Despite the market's size, challenges are growing:
- Margin pressure: Costs rose 4.3% in 2023, while revenues increased only 0.2%. Fee compression, competition, and inefficiencies squeeze profits.
- Regulatory burden: New rules like MiCA, DORA, and ISO 20022 increase compliance complexity and costs. The SEC alone proposed or passed 42 rules in 2023, reshaping operations and reporting.
- Legacy technology: About 70% of firms still rely on decades-old systems. Most spend 60–80% of IT budgets maintaining existing infrastructure rather than innovating.
- Diversifying asset classes: Emerging assets such as cryptocurrencies, tokenised assets, and structured notes are changing investor expectations.
Agentic AI—a smarter kind of intelligence
Agentic AI goes beyond generating content or analyzing data—it acts independently. It sets goals, adapts on the fly, and interacts with different systems without constant human input. This marks a shift comparable to how the internet transformed industries in the early 2000s.
Adopting agentic AI should be intentional and focused. One practical framework to guide this is the CARE Framework:
- Complex: Address multifaceted business challenges that need more than quick fixes.
- Alarming: Focus on areas vulnerable to fraud or high-risk failures.
- Repetitive: Automate routine but essential tasks.
- Ethical: Ensure AI decisions align with social and environmental values.
Where agentic AI can make a real impact
Leading asset managers are deploying micro-agents that integrate with legacy systems through APIs and orchestration layers. This allows gradual, modular adoption without overhauling existing infrastructure.
Agentic AI won't replace core asset management platforms entirely anytime soon. These platforms remain key for trade execution, portfolio management, customer engagement, and compliance. However, agentic AI can reduce dependence on external platforms by enabling firms to build their own agents, cutting license fees and upgrade costs.
Meanwhile, vendors are embedding agentic AI into their offerings, creating a competitive dynamic that will shape the future of asset management technology.
Final thoughts
Managing assets is only part of the challenge—managing change is equally crucial. Agentic AI offers asset managers a way to take control of ongoing shifts, reduce costs, and deliver smarter, faster, and more personalized financial services.
For UK-based firms, now is a good time to assess how this technology can address persistent challenges and improve operations. Starting small with micro-agents can set the foundation for broader transformation.
For those interested in practical AI training that supports smarter adoption of technologies like agentic AI, explore relevant courses at Complete AI Training.
Your membership also unlocks:
