Lloyds Bank’s group head of AI has said that the organisation is on track to meet its target of delivering £50 million worth of incremental value through 50 genAI use cases this year.

Speaking at FTT Festival in London on Monday, Rohit Dhawan said that the bank’s AI journey has been more focused on innovation rather than fully advanced models in production, with Lloyds tracking the “total number of AI advances.”

The comments come days after Lloyds announced it is piloting a multi‑feature, AI‑powered financial assistant within its mobile app, positioning the tool as a 24/7 “financial companion” that offers personalised coaching, spending insights and guidance on savings and investments.

The bank said last week it is currently trialling its AI assistant with 7,000 staff members before a broader customer rollout and that it will be the “UK’s first agentic AI financial assistant” when it launches in early 2026.

The Group is currently scaling generative AI, with 50 live use cases across five domains in 2025, including customer interactions, operations, colleague support and engineering.

At the London event, Dhawan went on to say that the organisation currently keeps its traditional AI and genAI measurements separately.

“This allows us to distinctly track the incremental gains specifically from genAI initiatives, without mixing it with our existing AI measurements,” he noted.

By separating these metrics, the bank expects to gain a clearer understanding of the unique value and progress of its efforts in genAI specifically.

Dhawan added that while machine learning continues to mature and become more sophisticated, genAI has created additional “momentum and excitement” in the bank’s innovation efforts.

During the panel, he also described the organisation’s approach to genAI as a portfolio-based and federated model.

“Each business unit generates ideas and initiatives related to genAI, which are then centrally prioritised across the group to ensure scalability,” he explained.

He emphasised that while it refines its approach, the bank maintains a connection between genAI, agentic AI and machine learning.

“While some initiatives will continue to use only machine learning or only genAI, others may combine multiple AI technologies,” he said.

“These different AI technologies are not mutually exclusive but can work together to solve complex problems more effectively,” Dhawan added.

Commenting on how to effectively control AI development, he noted that for large, complex organisations such as Lloyds, creating cross-functional teams remains crucial.

“Unlike smaller organisations where coordination is simpler, larger companies need more structured approaches,” he said.

He added he favours a top-down approach in which AI initiatives are carefully evaluated before being launched in a pilot phase.

“The goal is not experimentation for its own sake, but to develop a minimum viable product (MVP) that can be practically implemented and moved into production,” Dhawan said.

When asked about predictions for the coming year in the field of AI, he said that this is challenging due to the sector’s rapid evolution.

“However, we believe the AI economy will continue growing, offering opportunities across various layers of the AI value stream, from applications to infrastructure,” added the head of AI.

He added: “I think this is a significant positive opportunity for humankind, to solve the problems that have not been solved yet.”

. Built on Lloyds Banking Group’s generative AI and agentic framework that mines curated bank data, the system aims to provide accurate, tailored responses and can route users to human experts when required.

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