“How hard can it be?”
That’s what one technology leader at a global asset manager thought when their firm launched a data integration project to support a new AI initiative. What followed was the discovery of 12 different Microsoft tenants, nine CRM systems, and 12 HR management systems spread across the organization. A project initially expected to take six months stretched to more than 18.
“You simply cannot overestimate how challenging it can be to synchronize data globally,” the executive explained.
That story captures the reality confronting many financial services firms today.
For years, digital transformation has largely centered on incremental modernization. Firms migrated workflows to the cloud, automated individual processes, layered in new applications, and modernized around the edges of existing infrastructure.
According to Broadridge’s 2026 Digital Transformation & Next-Gen Technology Study, that era is rapidly giving way to something much larger. Based on a survey of more than 900 financial services leaders across wealth management, capital markets, and asset management, the study suggests firms are entering a broader architectural reset driven by tokenization, AI, and the growing pressure to simplify fragmented operating environments., and the growing pressure to simplify fragmented operating environments.
Tokenization emerges as the next infrastructure disruptor
Alongside AI, tokenization is quickly emerging as a major driver of infrastructure transformation.
The study found that 54% of firms are making moderate to large investments in tokenization and digital asset infrastructure, while 53% believe blockchain and distributed ledger technology will dramatically affect the way assets are settled.
Importantly, the conversation around tokenization has evolved.
Rather than viewing tokenization purely through the lens of cryptocurrency adoption, firms are increasingly focused on its broader implications for market infrastructure, including settlement, liquidity, interoperability, governance, and operational resilience.
“Tokenization has become mandatory in the last year,” said one technology leader at a U.S.-based wealth management firm. “Now, whenever we think about transactional modes—whether it’s trading or anything to do with clearing or movement of money or stocks—we’re thinking about the role that tokenization is going to play in streamlining that process.”
As firms prepare for tokenized versions of equities, mutual funds, and alternative assets, many are recognizing they will need to support parallel traditional and digital workflows for years to come. That increases the importance of interoperability, ecosystem collaboration, and integrated infrastructure capable of operating across both environments.
AI moves from experimentation to operations
The acceleration of AI adoption over the past year has been dramatic.
Eighty percent of firms now report using generative or predictive AI in operations, up from 31% last year. AI is also viewed as delivering the greatest business impact among next-generation technologies, surpassing cloud. GenAI ranks among the industry’s top technology investment priorities, while 27% of firms report already realizing measurable business benefits from those investments.
The shift reflects how quickly AI has moved from experimentation into day-to-day operations.
“AI is changing absolutely everything we do, from human capital—how we conduct our year-end reviews—to how we collate data internally, ingest data from external sources, and analyze that data,” said one chief operating officer at a Europe-based global asset manager.
As firms scale AI initiatives across the enterprise, however, many are running into a difficult reality: existing architectures were never designed to support the speed, interoperability, and data accessibility required to operationalize these technologies effectively.
Chief Operating Officer, Global Asset Management Firm
Infrastructure complexity moves to the forefront
The study found that 84% of firms believe front-, middle-, and back-office systems must be integrated into a unified platform to support innovation. More notably, 43% of firms believe they will need to build an entirely new technology stack to thrive in the age of AI.
Many firms are attempting to modernize while operating across fragmented systems, disconnected workflows, inconsistent data structures, and layers of technology built over years of expansion and acquisition. As organizations push deeper into AI integration, those operational gaps are becoming harder to ignore.
“When firms talk about modernization, what they’re really saying is they want to simplify,” said Swatika Rajaram, Broadridge President, Bank Broker-Dealer. “Over many years of innovation, acquisitions, and consolidation, they’ve built multiple layers on top of their tech stacks, and as they begin the process of trying to simplify those systems, they start uncovering lots of complexity.”
That focus on simplification is shaping investment priorities across the industry. Firms are increasingly prioritizing scalable cloud-native infrastructure, a unified data architecture, embedded AI and analytics, standardized APIs, and integrated operating environments that support future innovation.
Execution becomes the differentiator
The firms moving fastest are not necessarily those pursuing every emerging technology trend. Increasingly, the leaders are focused on foundational readiness: modern infrastructure, integrated data environments, operational agility, and the ability to execute transformation initiatives across multiple functions.
Talent remains a major challenge. Thirty-eight percent of firms cite lack of skilled talent as the biggest barrier to GenAI adoption, up from 28% last year. At the same time, 65% of firms say they have no formal mandates or incentives in place to encourage AI adoption internally.
“Success in this environment is not about doing one thing better than everyone else; it’s about executing across multiple departments and functions, working with the right partners, and constantly testing the limits to extract value from new innovations,” said Germán Soto Sanchez, Broadridge Chief Product and Strategy Officer.
The study points to an industry entering a more demanding phase of transformation. AI is producing measurable operational impact today. Tokenization is pushing firms to rethink the future of market infrastructure. Underneath both trends sits a growing recognition that legacy architectures, fragmented data environments, and disconnected workflows may no longer be sustainable.
For a deeper look at the trends, challenges, and priorities shaping this next phase of transformation, download the full 2026 Digital Transformation & Next-Gen Technology Study.