The asset management industry faces two challenges: clients demand greater personalization and efficiency, while profit margins are tightening. PwC’s Asset & Wealth Management Revolution study reports 89% of asset managers feel pressure to deliver profitability, with nearly half describing this pressure as high or very high.
At the same time, artificial intelligence (AI) has become the main technological lever in the sector. This is no coincidence: the global AI market surpassed USD 244 billion in 2025, an increase of almost USD 50 billion in just two years. Projections are even more compelling: the industry is set to surpass the trillion-dollar mark by 2031, consolidating itself as a transformative axis for multiple sectors, including financial services.
PwC notes that 80% of asset and wealth managers believe disruptive technologies, including AI, are driving revenue growth. McKinsey, on the other hand, estimates that a mid-sized asset manager can capture between 25% and 40% of their cost base through well-executed AI initiatives, provided that end-to-end workflows are reimagined, not just isolated tasks.
Meanwhile, the McKinsey Global Institute’s Agents, Robots, and Us report highlights that AI is redefining the way organizations operate: machines take on routine tasks, while people focus on interpretation, decision-making, and solution design.
In this context, securitization appears as the “structural bridge” that allows AI capabilities to be transformed into concrete, scalable, and globally distributable investment products.
Why are AI and securitization connected now?
1.- Pressure on margins + need for efficiency
AI reduces operational costs, and securitization allows this efficiency to be packaged into lighter and more cost-effective vehicles, helping managers survive and grow in an environment with increasingly tight margins.
2.- Increasing adoption of AI in front, middle, and back offices
PwC highlights that managers are integrating AI in portfolio personalization, task automation, and generating insights for clients.
However, many of these capabilities remain “locked” within the organization unless they are translated into investable products.
3.- Transformation of the investment leader’s role
McKinsey emphasizes that business leaders must become “tech-savvy leaders,” capable of linking AI strategy with financial outcomes and business models.
Securitization provides a framework for monetizing these technological capabilities in the form of structured series or notes.
How can portfolio managers combine AI + securitization?
a) Turning AI-driven strategies into securitized vehicles
AI models generate increasingly sophisticated investment signals, rebalancing, and portfolio construction. Rather than limiting these strategies to internal balance sheets or segregated mandates, managers can:
- Replicate the systematic strategy in a securitized vehicle (e.g., a series issued through an SPV).
- Offer it to institutional and professional investors as a product with an ISIN, international custody, and standardized operational flow.
In this way, AI becomes an alpha engine, and securitization is the vehicle that takes it to market.
b) Packaging infrastructures and AI-linked flows
Adopting AI involves investments in data, models, and technology infrastructure. McKinsey emphasizes that the true economic impact is achieved when AI is integrated into full processes and operational models, not just isolated pilots.
Through securitization, portfolio managers can structure:
- Thematic notes linked to AI-intensive company or sector strategies.
- Vehicles that expose the investor to flows generated by assets or contracts tied to AI (e.g., digital ecosystems, data, or technological services), when eligible as underlying assets.
c) Accelerating time-to-market and customization
PwC’s reports on the asset and wealth management revolution highlight that managers who combine technology and the redesign of operational models are more likely to capture growth in a highly competitive environment.
Securitization allows:
- Launching AI-based products in shorter timeframes than a conventional fund.
- Creating tailored solutions for specific customer segments (e.g., AI-driven strategies with specific ESG or liquidity restrictions).
Evidence from PwC and McKinsey shows that AI is already a critical factor for future profitability for managers, but its real impact depends on the ability to turn it into tangible investment solutions.
Securitization programs provide portfolio managers with a flexible infrastructure to transform AI capabilities into products ready for global distribution, aligning technological innovation, cost efficiency, and growth in assets under management. In this context, specialized companies like FlexFunds demonstrate how agile, global solutions can facilitate this transformation, turning advanced strategies into cost-efficient, scalable vehicles without the need for complex conventional structures.
To learn more about how FlexFunds uses advanced technologies for its asset securitization program, please contact our experts at contact@flexfunds.com
