Roundtable Event: AI in Investment Management
AI in Investment Management
Milan, May 2025 – In recent years, artificial intelligence has made significant strides, establishing itself as a strategic lever capable of profoundly transforming the way financial data is gathered, analysed, and used in decision-making processes. The integration of AI promises to boost efficiency, enhance accuracy, and open up new operational opportunities. However, alongside these opportunities come complex challenges, ranging from cultural and regulatory aspects to issues concerning the evolution of professional skills.
During the event organised by Axyon AI in Milan last week, which brought together leading experts from the worlds of asset management and technology, these dynamics were discussed in depth. The starting point for the debate was clear and provocative: does artificial intelligence represent a paradigm shift for the financial sector, or is it, rather, a natural evolution of existing models?
The roundtable offered concrete insights and complementary perspectives on how AI is redefining the entire investment ecosystem.
Featured speakers:
Key Topics of Discussion
Beyond the Myth: Evolution, Not Replacement
The discussion swings between those who view AI as a revolution and those who see it as an incremental evolution. According to PwC AI Predictions 2025, 73% of financial leaders believe AI will radically transform asset management over the next three years. At the same time, the rise of AI raises important questions about the future of work in the financial sector: McKinsey estimates that 44% of tasks in wealth management could be automated by 2030.
During the panel, a powerful image emerged: the shift from the typewriter to the first personal computer. The adoption of AI, much like that of the computer in the 1980s, is not an immediate revolution, but a gradual process.
"The real transformation will depend on companies’ ability to move beyond the ‘pilot paradox’ and scale AI projects at a strategic level”.
In Italy, in fact, AI adoption is still growing and remains heavily reliant on visionary leadership and the commitment of individual business functions.
Immediate Impact of AI: Efficiency and Performance
- AI can enhance speed and operational capacity across the entire financial services sector.
- Visionary leadership plays a crucial role in shaping the strategy and driving AI implementation.
The Competitive Advantage of Scalability
During the discussion, it was noted that in the financial context, one of the most significant aspects of artificial intelligence is scalability – the ability to operate with the same level of effectiveness as data volumes and processes grow exponentially.
“When it comes to developing and adopting AI, scalability becomes a crucial factor: it is what enables expansion and exponentially accelerates the pace of implementation.”
This feature not only enables the management of complexity that would otherwise require unmanageable human and infrastructure resources, but also acts as a key enabler of innovation. In particular, the scalability of AI allows financial institutions to automate and refine analysis across increasingly broad investment universes, to personalise offerings at scale, and to respond more swiftly to change. It is precisely this combination of scalability and adaptability that makes AI a genuine competitive advantage.
Scalability as a Competitive Advantage
- Scalability is a strategic lever for the effective adoption of AI, as it enables the efficient and rapid handling of growing volumes of data.
- This capability drives large-scale innovation, facilitating automation, personalised offerings, and responsiveness to change.
The Portfolio Manager at the Heart of an Augmented Evolution
One recurring theme was the impact of AI on the role of the portfolio manager. While in some quantitative areas AI represents a natural evolution (“Quant 2.0”), in others—especially in traditional asset management—it marks a potential paradigm shift. The growing demand for personalisation from younger generations calls for a significant step forward:
“Without advanced tools for data analysis and dynamic portfolio construction, traditional managers risk becoming uncompetitive.”
In any case, the idea of total replacement does not appear realistic:
“We cannot replace human brilliance. But we can—and must—augment it.”
Human–Machine Collaboration Is Essential
- La conoscenza del settore e le competenze tecnologiche devono lavorare in sinergia.Industry knowledge and technological expertise must work in synergy.
- The “quantamental” approach represents the new hybrid model enhanced by AI.
- To remain competitive, it is essential to have a robust technical infrastructure — including computing power and data processing capabilities — aligned with a high level of technological proficiency.
Explainability & Accountability
How Can We Improve “Explainability” to Make It Acceptable to Investors?
In a context where artificial intelligence is playing an increasingly pervasive role in investment management, the ability to explain how it works and on what basis it makes decisions becomes crucial. Investor trust depends on the clarity and transparency of automated decision-making processes.
Moreover, the responsible adoption of AI requires a balance between innovation and accountability, where explainability serves as a vital bridge between technology and people.
Explainability and Trust: Essential Requirements
- Finance demands models that are both verifiable and justifiable.
- Explainability fosters trust — a particularly crucial factor when it comes to clarifying the rationale behind models and addressing any periods of underperformance.
Technological Disruption and the Redefinition of Industry Players
The introduction of AI, blockchain, and quantum computing could usher in a profound transformation. The combination of extremely high computational power and new tools for process automation may lead to the creation of hyper-optimised, low-cost, dynamically managed portfolios — potentially reshaping the role of the traditional intermediary.
Data Analysis and Infrastructure
- Fundamental managers can now expand their analysis across vast investment universes thanks to AI.
- Predictive AI is driving a convergence of strategies, enhancing both agility and analytical capabilities.
New Generations, New Expectations
New generations — particularly high-net-worth clients under the age of 45 — are demanding a radically different relationship with finance: digital, personalised, and transparent. It is no coincidence that many emerging solutions are coming from Asia, where integrated platforms are already combining banking, wealth management, and AI.
“There is a strong demand for agency in decision-making. The investment fund, with its more than 100-year history, is no longer seen as a suitable instrument.”
Immediate Impact of AI: Performance & Efficiency
- AI can enhance speed and efficiency across financial services.
- Even non-technical users can now access advanced technologies, contributing to a more level playing field.
- Implementation speed is critical. Choosing qualified partners with the right domain expertise and a proven track record can make all the difference in ensuring effective adoption and delivering tangible results.