In recent years, Artificial Intelligence has moved from being a technological promise to an operational reality for the world of asset management. Far from the image of machines taking control, AI is now seen as a strategic ally—one that broadens perspectives, reads markets in depth, and frees professionals to focus on high-impact decisions. Its strength lies not only in processing vast amounts of data quickly, but above all in integrating those analyses into decision-making processes, cutting through noise and highlighting the signals that really matter. This is where the combination of human intuition and advanced computation becomes a competitive edge.
From context to market signals
One of the most relevant contributions of AI in professional asset management is its ability to capture the “big picture” without losing sight of the details. Quickly identifying whether the market is in a risk-on or defensive phase, estimating how long it may last, and understanding how different asset classes are moving enables more informed decision-making. The goal is not to replace the manager’s expert eye, but to complement it with tools able to detect patterns and correlations invisible to the naked eye, turning intuition into choices backed by concrete evidence. According to BCG’s Global Asset Management Report 2025, the industry reached USD 128 trillion in assets under management (AuM) in 2024—up 12% from the previous year. At this scale, solutions that filter useful signals and reduce complexity are indispensable.
From strategy to execution at scale
If analysis is the first step, implementation is the true test of efficiency. Building portfolios aligned with objectives, constraints, and risk profiles is already complex; doing it simultaneously for dozens or hundreds of portfolios can be overwhelming. AI makes it possible to manage this complexity with consistency and precision, automatically applying personalized constraints and rebalancing allocations in line with defined targets. This ensures coherence and control even as operational volumes grow, minimizing unwanted deviations and freeing up time for more strategic tasks.
Recent studies estimate that AI adoption could impact asset managers’ cost structures by 25–40%, cutting manual and repetitive tasks and reallocating resources to technology, governance, and high-value skills. At the same time, Deloitte highlights that more than two-thirds of managers are increasing AI investments after seeing its tangible value in daily operations.
Personalization and scalability
While efficiency is key, the ability to deliver personalized solutions has become essential. AI enables the construction of tailor-made portfolios, modeled on specific risk profiles and preferences, and updated in real time as markets evolve. Digital platforms offering such capabilities are rapidly expanding: by 2027 they could manage nearly USD 6 trillion in AuM, almost double compared to 2022. AI thus becomes not only an analytical tool, but also a driver of scalability, bringing true personalization within reach at large scale.
Explaining decisions, not just numbers
In a sector where trust and transparency are fundamental, explaining investment choices is as important as making them. Generative AI is emerging as a valuable tool here: it can transform complex data into clear, personalized analyses that explain not only what was done, but also why. Reports that link portfolio positioning to the market context, highlight risk factors, and outline the rationale behind decisions help strengthen client relationships and ensure consistency of communication, even under time pressure. Several firms are already adopting this technology, and solutions such as MDOTM Ltd’s StoryFolio module demonstrate how generative AI can produce automated commentary and reporting at the single-portfolio level, making communication more transparent and timely.
The impact on skills and teams
AI adoption is reshaping not only processes and costs but also the skills required. Managers are evolving toward “human+AI” models, where analysts and portfolio managers use AI copilots to enhance research, scenario building, and documentation. This shifts time away from repetitive tasks and creates demand for new capabilities: interpreting AI-generated output, validating quality, and embedding it into decision-making. Increasingly, teams bring together data scientists and portfolio managers, creating a shared language between technology and investment. The result is more agile organizations, where AI augments human capabilities rather than replacing them.
Toward a new normal
The transition from pilots to broad adoption is now clear. AI is no longer a technological novelty, but a foundational infrastructure for asset management business models. Those who integrate it carefully can transform not only internal productivity but also the investor experience.
Recent studies show that 67% of industry organizations increased AI investments in 2025, aiming to consolidate lessons from early pilots and embed AI at the core of operations. The message is clear: AI has become part of the new normal.
The next chapter in asset management
The data already trace a clear path: from analysis to communication, from operational efficiency to extreme personalization, AI is set to become an essential component of asset management. According to Global Market Insights, the AI in asset management market will grow from about USD 3.4 billion in 2024 to over USD 20 billion by the mid-2030s, with a CAGR of nearly 25%.
The future of asset management will increasingly be a dialogue between people and technology. Human intuition, enriched by AI computation, will guide toward more agile, targeted, and resilient solutions in a constantly evolving financial world.
Sources
- BCG – Global Asset Management Report 2025
- McKinsey – How AI could reshape the economics of the asset management industry, 2025
- Deloitte – Role of AI in Investment Management, 2025
- PwC – Asset and Wealth Management Report, 2025
- Business Insider / McKinsey – AI adoption cases at AllianceBernstein, BlackRock, and JPMorgan, 2025
- Global Market Insights – AI in Asset Management Market Forecast 2025–2034
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