What happens when the cost of intelligence sinks to zero? This question, posed at a recent industry roundtable hosted by Cognizant and Raconteur, cuts to the heart of the financial services industry’s transformation challenge.
When artificial intelligence can write reports, conduct research and generate ideas instantaneously, traditional ways of working – including customer relationships – face fundamental disruption. The winners will be those who move the fastest to transform AI from a back-office tool to a front-line competitive advantage. Those quick enough to harness AI’s shift from internal efficiency to external value creation will find themselves competing in an entirely new game.
The race is already underway. By 2030, AI-friendly consumers are expected to drive 55% of all purchases, according to recent Cognizant research, equivalent to £690bn in UK consumption alone, which will fundamentally change how the financial services sector must operate.
For financial institutions, this will mean competing for the attention of customers who use AI for interaction. When AI agents evaluate mortgage rates or process loan applications at machine speed, traditional customer touchpoints become obsolete.
The solution lies in what David Fearne, director of generative AI at Cognizant, calls the “agentic enterprise” – moving beyond isolated AI tools to interconnected systems that mirror human organisational structures, with enterprise intelligence coordinating task-based AI across business units. This breaks down the walls between individual AI applications, creating a unified intelligence layer that can pursue opportunities too marginal for traditional approaches to handle.
In turn, UK financial firms are responding with investment with many seeing increases in their annual technology budgets as firms seek to capitalise on the gains offered by AI. Yet, at the same time, research from Cognizant has found that only 30% of BFSI organisations have rolled out cross-enterprise GenAI use cases.
Speed becomes survival
The transformation’s velocity defies traditional planning cycles. At Pismo, CEO Vishal Dalal describes the pace as “whiplash-inducing”. “A few months ago, we were doing the basics well with Copilot,” he explains. “Then suddenly one customer said: ‘Show me how you can deliver value with AI, and we were off to the races.”
This stinging comment spurred a scattering of AI experimentation that is already bearing fruit. Out of Pismo’s last 10 client proposals, five have demanded AI capabilities – a significant increase in just a month. Core banking transformations that historically required years can now compress processes from months to minutes. Dalal’s team, in a recent demonstration, were able to achieve deposit configurations in minutes, when it previously took several weeks to complete – all thanks to automation.
Andrew Bateman, executive vice-president of lending at Finastra, sees similar acceleration. The company’s survey of 1,100 senior executives, across 11 countries, revealed 61% of financial institutions deployed or improved their AI capabilities last year, nearly doubling from 37% in 2023. “If you don’t adopt now, you’re still going to be taking six to nine months to get an idea out, whereas your peers will be doing it in weeks,” he warns.
Andrew Shannon, global head of IT infrastructure at TP ICAP, observes the evolution from chatbots to collaborative agents. “We’ve started to evolve to agents that can act on tasks, be part of teams and work together,” he explains. “There are huge opportunities to re-engineer how organisations work.”
Building enthusiasm over resistance
Cultural transformation proves as crucial as technology. TP ICAP deliberately started with AI productivity applications in lower-risk environments before expanding into revenue generation. Now, by encouraging an “AI culture” and recently establishing an “AI and Innovation Lab”, the company has sparked widespread interest in exploring possibilities. “I’m inundated by enthusiastic people from across the business who want to understand opportunities,” says Shannon.
Elsewhere, Finastra hosts “GenAI expos” featuring “prompt-a-thons” – an evolution of hackathons that builds repositories of effective natural language instructions. “Getting people to think about how to have that interaction is sometimes the hardest thing,” explains Bateman. “You want natural language rather than programmatic approaches.”
However, resistance persists. Fearne encounters “unhealthy levels of scepticism” across financial services, primarily driven by fear, from clients and their employees. His solution? “Write internal charters defining what AI will and won’t do.”
Indeed, governance and regulatory concerns compound the challenges, although attitudes are likely to shift rapidly as competitive pressures intensify. Blue Prism research, published earlier this year, shows that 76% of financial firms plan to implement agentic AI within the next 12 months, while 64% of UK consumers say they already comfortable trusting AI to detect financial fraud and flag suspicious activity on their bank account, according to Attest. Both percentages look set to rise quickly.
The talent landscape transforms, too. Shannon notes that certain generations will soon only accept jobs that utilise AI tools. Companies that restrict usage risk excluding top talent, particularly as all graduate interns now use ChatGPT and similar systems.
Rethinking skills and systems
What is increasingly clear is that many employees require immediate reskilling to adapt to AI-driven changes. As a result, traditional technical skills are giving way to human capabilities, including emotional intelligence, strategic thinking and effective communication.
Fearne’s team hired their first psychology graduate as an “AI psychologist” to understand how sophisticated models respond to inputs. “These models are so complicated that even big labs can’t understand what’s going on,” he explains. “We study them by cause and effect, the same way we study humans.”
Financial services recruitment shifts accordingly, prioritising communication skills over traditional computer science backgrounds. “Natural language is the new programming language,” notes Fearne. “Everyone’s going to become an AI boss of some description.”
Technical infrastructure and partnerships, as well as data quality and management, remain vital for financial services firms to stay ahead with AI innovation and, more crucially, remain relevant. Fearne says, for example, that Microsoft’s Azure AI Foundry provides the platform for this enterprise intelligence layer, integrating across multiple systems rather than being limited to single applications like traditional vendor AI. “This enables the strategic coordination that makes agentic enterprises possible,” he adds.
Early movers are enjoying substantial advantages. “The clients who begin AI initiatives in 2023 are leaps and bounds ahead of their competitors,” says Fearne. “They took the plunge, learned repeatedly and now that understanding is paying ridiculous dividends.”
Leadership advice for financial services leaders seeking to improve AI capabilities and capture external value centres on three principles. First, act immediately. “Don’t wait,” urges Dalal. Fearne adds: “Be careful not to let perfection be the enemy of good. Businesses operate successfully with imperfect humans.”
Second, maintain what Dalal calls “curiosity on steroids”. He advises that leaders adopt this mindset when future-proofing, focusing on the changes needed today to remain competitive as the industry rapidly evolves. Third, embrace the learning curve that early movers now enjoy as a competitive advantage.
“We’re going to see the individual use cases that people have been working on start to become increasingly interconnected with AIs talking to other AIs and an order starting to emerge as the agentic enterprise fully emerges,” adds Fearne.
Ultimately, financial institutions are at an inflexion point. Success requires combining technological capability with human insight, creating AI-enabled cultures while maintaining trust. In turn, institutions must recognise that those who master AI will compete with each other on a higher level in tomorrow’s market, while those who hesitate will find themselves scrambling for relevance in today’s market.
Unlock the value of AI within financial services with Cognizant
What happens when the cost of intelligence sinks to zero? This question, posed at a recent industry roundtable hosted by Cognizant and Raconteur, cuts to the heart of the financial services industry’s transformation challenge.
When artificial intelligence can write reports, conduct research and generate ideas instantaneously, traditional ways of working – including customer relationships – face fundamental disruption. The winners will be those who move the fastest to transform AI from a back-office tool to a front-line competitive advantage. Those quick enough to harness AI’s shift from internal efficiency to external value creation will find themselves competing in an entirely new game.
The race is already underway. By 2030, AI-friendly consumers are expected to drive 55% of all purchases, according to recent Cognizant research, equivalent to £690bn in UK consumption alone, which will fundamentally change how the financial services sector must operate.
For financial institutions, this will mean competing for the attention of customers who use AI for interaction. When AI agents evaluate mortgage rates or process loan applications at machine speed, traditional customer touchpoints become obsolete.
