Artificial intelligence (AI) and distributed ledger technology (DLT) are transforming industries. But the technologies can be even more powerful in combination, if industries and organisations can harness this synergy effectively.

Deutsche Bank and Clifford Chance’s combined expertise from both a financial services and legal perspective has come together to report on this trend in a new white paper, titled The convergence of AI and Distributed Ledger Technology – opportunities and risks.

The paper – which features a foreword authored by Diego Ballon Ossio, Partner at Clifford Chance, and Sabih Behzad, Head of Digital Assets & Currencies Transformation at Deutsche Bank – sheds light on the interaction between AI and DLT, highlighting practical steps for implementation and use cases for organisations, alongside possible barriers to adoption and legal considerations.

As the report notes, while AI brings intelligence, automation and analytical capabilities, DLT offers decentralisation, transparency and data provenance. When combined, the technologies can mutually reinforce each other’s capabilities.

The predictive and analytical capabilities of AI, combined with the decentralised and resilient infrastructure of DLT has the potential to accelerate the transformation of a range of products, services and industries by enabling smarter, automated systems that operate with improved transparency, efficiency and trust.

The paper highlights five practical insights for organisations developing or considering exploring implementation:

• Take a holistic and collaborative approach to use case exploration and implementation. Organisations must consider the impact of proposed projects and business models on their daily operations and understand cross-business implications across various departments, including legal, technology, risk, compliance, sales, HR, finance, and tax.
• Build internal capabilities and technology literacy to support the changes ahead. Building internal capabilities and literacy in AI and technology is essential to leverage these opportunities fully. Staff and stakeholders need to understand the capabilities and limitations of the technologies being used to ensure that use is appropriate.
• Consider wider impact and alignment with firm policies and culture. Organisations need to align new technologies with their policies and culture, considering factors such as customer care, transparency, accountability, energy consumption and sustainability goals.
• Strategically assess and navigate legal obligations and risk. Navigating the complex legal and regulatory landscape requires early due diligence, strategic risk management (including through the contractual framework) and collaboration with trusted advisers.
• Consider engagement with policymakers, regulators and industry stakeholders, and anticipate new legislation. Engaging with policymakers, regulators and industry stakeholders can also be crucial to staying ahead of regulatory changes, understanding sectoral and regulatory expectations, and shaping emerging policies.

There are a range of use cases emerging or being explored in the financial sector with differing levels of maturity. Some use cases are already being tested or rolled out, for example in areas such as treasury management where platforms are being tested and launched to support 24/7 global treasury operations.

One such use case is seen in Deutsche Bank’s and Ant International’s strategic partnership to provide integrated cross-border payment solutions to global merchants.

The paper focuses on four use cases that have the potential to transform a range of industries. These are:

1. Improvements to smart contract development and performance through the ability to test and interrogate their functionality.
2. AI-powered blockchain oracles for enhanced reliability when connecting distributed ledgers to real-world data.
3. Controlled access to private datasets to further AI development.
4. AI agents using blockchain wallets to support payments processes and commerce.

The convergence of AI and DLT necessitates consideration of a complex patchwork of legal and regulatory requirements, including evolving technology-specific laws, data protection requirements, contract and private law considerations, as well as sector-specific regulations that could impact use cases for financial services, healthcare, energy, transportation and more. These parallel and overlapping regimes and laws demand careful, case-by-case legal analysis to ensure compliance and to mitigate liability and other risks.

The paper highlights some examples of key legal considerations including:

• The introduction of AI-focused legislation, which has developed alongside new regulatory regimes governing markets in crypto assets and crypto asset service providers.
• Liability issues in relation to how combined AI and DLT projects are structured and documented.
• Issues around contractual interpretation and technical errors in the context of smart contracts – and associated liability risks and potential disputes.

While there are numerous hurdles and complexities, for many organisations the potentially transformative opportunities arising from the combination of AI and DLT may significantly outweigh the challenges.

The groundwork for this transformation is already being laid, and, for many use cases, their implementation will not be in the far-distant future, but a shorter-term reality.

To read the white paper in full, download it using the link below: