Are Financial Services Firms Right to Bet on Tokenisation After AI Adoption?

The financial services industry has seen a rapid shift in technology adoption over the past few years. After moving from experimenting with artificial intelligence (AI) to deploying it at scale, many firms are now turning their attention to tokenisation. New research from Broadridge highlights this trend, showing that tokenisation is poised to become the next major infrastructure change in finance. But is this bet on tokenisation justified? This post explores the findings of Broadridge's 2026 Digital Transformation and Next-Gen Technology Study and explains why tokenisation could be the next big step after AI.

Tokenisation transforming financial infrastructure

The Shift from AI Experimentation to Deployment

Broadridge's study surveyed 950 participants across the financial services sector and revealed a striking acceleration in AI adoption. Just a year ago, only 31% of firms had operational AI systems. Today, that number has jumped to 80%. This is not a small step forward; it represents a wholesale move from pilot projects to full-scale deployment.

This rapid adoption shows that financial firms have learned how to integrate complex technologies quickly and effectively. AI, particularly generative and predictive models, is now embedded in many core processes, from risk assessment to customer service automation. The success of AI adoption has built confidence in the industry’s ability to modernise rapidly.

Why Tokenisation Is the Next Focus

With AI firmly in place, 54% of firms are now investing moderately to heavily in tokenisation and digital asset infrastructure. Tokenisation involves converting rights to an asset into a digital token on a blockchain or distributed ledger. This technology promises to change how financial assets are issued, traded, and settled.

Blockchain technology, which underpins tokenisation, is also gaining traction as a source of new growth opportunities. The study found that 55% of respondents see blockchain as a key growth driver, up from 42% the previous year. This growing interest reflects a broader industry trend: firms are applying the lessons learned from AI to accelerate adoption of tokenisation.

What Makes Tokenisation a Structural Evolution?

Germán Soto Sanchez, Broadridge’s chief product and strategy officer, explains the connection between AI and tokenisation clearly. AI has shown that the financial industry can modernise quickly. Tokenisation represents the next structural change that builds on this foundation.

One of the main benefits of tokenisation is its potential to transform settlement processes. Currently, many markets operate on a T+1 or T+2 settlement cycle, meaning trades settle one or two business days after execution. Tokenisation combined with AI-driven automation offers a path to T+0 settlement, where trades settle almost instantly and continuously.

This shift could reduce counterparty risk, free up capital, and improve liquidity. It also aligns with the increasing demand for real-time financial services in a global, digital economy.

Practical Examples of Tokenisation in Action

Several financial institutions and platforms have begun implementing tokenisation to improve efficiency and open new markets:

• Real Estate Tokenisation: Some firms are tokenising real estate assets, allowing investors to buy and sell fractions of properties digitally. This lowers barriers to entry and increases market liquidity.

• Securities Tokenisation: Tokenised securities enable faster settlement and easier transfer of ownership. For example, a tokenised bond can be traded 24/7 on blockchain platforms, unlike traditional bonds limited by market hours.

• Trade Finance: Tokenisation can digitise trade finance instruments like letters of credit, speeding up processing times and reducing fraud risk.

  
  

These examples show how tokenisation can create new opportunities while improving existing processes.

Challenges to Overcome

Despite its promise, tokenisation faces several hurdles before it becomes mainstream:

• Regulatory Uncertainty: Financial regulators are still developing frameworks for digital assets and tokenised securities. Firms must navigate complex and evolving rules.

• Interoperability: Different blockchain platforms and legacy systems need to work together seamlessly for tokenisation to scale.

• Technology Maturity: While blockchain technology has advanced, issues like scalability, energy consumption, and security remain concerns.

• Market Adoption: Broad acceptance by investors, custodians, and clearinghouses is essential for tokenisation to reach its full potential.

  
  

Firms investing in tokenisation must address these challenges carefully to realise the benefits.

What This Means for Financial Services Firms

The Broadridge study suggests that firms that mastered AI deployment are now applying those skills to tokenisation. This sequence matters because it shows a pattern of building on proven capabilities rather than chasing every new trend.

Financial services firms should consider:

• Investing in Talent and Skills: Building teams that understand both AI and blockchain technologies.

• Piloting Tokenisation Use Cases: Starting with specific asset classes or processes to test benefits and challenges.

• Engaging Regulators Early: Working with policymakers to shape clear, supportive frameworks.

• Collaborating Across the Ecosystem: Partnering with technology providers, exchanges, and other firms to build interoperable solutions.

  
  

By taking these steps, firms can position themselves to benefit from the next wave of digital transformation.

Disclaimer: This article is provided for general information only and does not constitute legal, financial, or investment advice. The regulatory treatment of tokenised assets and digital securities varies by jurisdiction and continues to evolve. Readers should seek independent professional advice before making any financial, legal, or regulatory decisions.