Business leaders in financial services know that they have to embrace AI but there’s a huge amount of uncertainty in knowing which one to use. I am often asked to “use agentic AI” to help improve
efficiency and productivity from the bottom up. Other times, I have seen pressure on the C-suite to make significant cost reductions but the briefs feel overly simplistic and lack overall strategic planning for the long term. Instead of making knee jerk reactions
to cutting costs and introducing AI that could do more harm than good before fully understanding its best use, focus must shift to a longer view whereby better overall engagement and therefore customer retention, could bring much greater returns to the bottom
line.
Whilst I remain a firm believer in Return on Investment (ROI), especially where improved user experience (UX) creates measurable and quantifiable benefits,
I am increasingly mindful of the hidden costs, regulatory hurdles and adoption challenges that are often underestimated, while the potential for deeper customer engagement, as a whole, is overlooked.
McKinsey’s latest research found that more than 80 percent of global companies using AI saw
“no significant
bottom line impact”, despite 78 percent already applying it in at least one function. S&P Global adds that
42
percent of firms abandoned most of their AI pilots in 2024. Accenture reported that in China, despite state mandated adoption, only
9 percent of
companies reported meaningful gains.
In the financial sector there have been several high profile cases of companies walking back supposed gains. Following claims that AI was fulfilling the
workload of 700 full-time service agents, Buy Now Pay Later giant Klarna announced a pivot to
hiring
human customer service agents earlier this year due to “lower quality” customer service. Commonwealth Bank of Australia similarly
reversed its plan to
replace 45 call centre roles with AI, admitting that it “did not adequately consider all relevant business considerations” and “should have been more thorough in our assessment of the roles
required” amid reported increases in call volumes.
This is what McKinsey calls the “gen AI paradox”: rapid adoption, heavy investment, and thin results. Gartner reminds us this is a classic feature of the
hype cycle, as inflated expectations give way to disillusionment when early implementations fail to deliver. But to reduce it to hype is to miss the point.
Enter ROX: Return on Experience
Thinking about ROI in terms of immediate cost-cutting forestalls the opportunities to transform the customer experience across the business. I believe that
the real winners will be the companies who use AI to deliver a white glove experience at a scale that was previously impossible, democratising access to world-class financial products and advice and permanently resetting expectations around the speed and cost
of checks, payments and settlements. This requires a different way of thinking, and an entirely new metric: return on experience (ROX).
Banking has unique challenges, with regulatory requirements and legacy tech creating a wealth of opportunities for new challengers to leapfrog incumbents,
but success ultimately comes down to what banks can offer their customers. The shift to seeing AI first and foremost as a differentiator in experience requires further thinking about the key metrics you will use to measure progress.
Speaking at FinTech Live this October,
Ed Patrick of
L&G shared that he is not planning on making heavy bets on AI replacing whole teams in the near future, but is focussing on using the tools at hand to demonstrate the value of AI to speed up
processes and improve experience. While he acknowledged that measuring non-financial ROI can be hard to get right, he stated that
at this stage in the cycle, an AI initiative should “wash its face”.
However, the reality of working with AI as a non-deterministic technology means that those holding out for perfection will be left behind. “You
are going to make mistakes in your implementation,” said Simon Foley of Lloyds Banking Group frankly in the same discussion. He shared that regulators value transparency over perfection and are keen to work with banks to navigate the shift. For stakeholders,
it’s about surfacing early wins, showing green shoots of impact in the first in one to three months.
Supercharging customer experience with AI
There are already some exciting examples of digital financial products that are harnessing AI to offer step changes in customer experience, with concierge-style
services applied at scale.
Cleo
surfaces insights and data visualisations through chat with the goal of improving customers’ relationships with money, with distinctive branding and tone of voice that feels human and relatable.
Starling
Bank likewise recently launched its Spending Intelligence, a tool that lets customers analyse their spending patterns with AI.
Robinhood
also uses AI to provide timely analysis of stock movements in response to breaking news, promising, “We will keep introducing AI tools that prioritise customer education and help our investors navigate the market with confidence.”
Despite the bad press, Klarna has delivered its own innovations in customer experience, with features including
personalised
shopping advice and a
CEO hotline.
However, they are now clear on the value of keeping a human in the loop. “I just think it’s so critical that you are clear to your customer that there will be always a human if you want,” said CEO Sebastian Siemiatkowski. “As cost unfortunately seems to have
been a too predominant evaluation factor when organizing this, what you end up having is lower quality.”
A CEO’s ROX playbook
For leaders looking to bridge the AI paradox then, the lessons are clear:
-
Define metrics upfront: design dashboards that track customer, employee, brand, and operational outcomes.
-
Govern for alignment: create cross functional forums, democratise access to data, align incentives
-
Pilot for scale, not novelty: test for ROX impact, not one off demos
-
Amplify employee value: Keep a human in the loop where this is necessary to ensure quality
-
Tell the story: ROX wins need to be made visible to boards and teams
ROI will keep the lights on. ROX will decide who grows. The paradox of AI is not about hype, it is about perspective. If banks measure only
what they cut, they will miss what they could create. The institutions that treat ROX as their true compass will turn digital innovations into loyalty, trust and entirely new streams of revenue.
