By Chris Livesey, chief executive of AutoRek.
Across the financial services software landscape, vendors and end-user customers are chasing a new goal, in how fast they can AI-ify or agentify everything that moves to claim unique differentiation and plant a flag for their brand as a market leader.
We’ve seen this cycle many times before, for example with internet, cloud and SaaS, and it’s an understandable response, where “do nothing” is definitely not an option. AI’s transformative potential is real and continually evolving, and being able to market AI-enabled services and applications has rapidly become table stakes to be relevant – often way beyond what is typically a reputation based on decades of solid and reliable capabilities.
The first-mover advantage with AI is something most organisations are hungry to claim, but ultimately speed alone is not what will separate the winners from the losers. The winners will be the firms that apply AI in ways that strengthen durable value, trust, and duty of care – not compromise them.
A Strategic Divergence?
Financial services technology buyers have long struggled to successfully integrate applications and data across their fast-moving businesses. Complicated and often frail integrations that exist on the edges of these applications are costly to implement and troublesome to maintain, while also presenting very clear operational risks around data security and resilience. And further, this is across a wide-ranging set of applications deployed on different stacks, with varying levels of interoperability, and quite commonly relying heavily on legacy systems of record.The allure of AI is clear, as a means of somehow navigating across these estates of applications and data in a frictionless manner, requiring little change to the underlying systems to create new insight and unlock new value. It’s tempting to imagine AI as a universal solvent – dissolving complexity without touching the underlying architecture.
Or further still, many technology buyers are now wondering if they could remove some of these applications completely and replace them with self-build agentic applications and services that fulfil the same need, but in a highly optimised and open manner across their domain, freeing them from the application costs, and enabling them to work at the speed of their business, not the speed of the supplier. Tempting!
There is another school of thought however, from the software vendor community itself, that disaggregating their applications into agentic services will present a new way to offer the value of their service expertise, and to protect their businesses from being eroded by customer self-build strategies.
Where Enterprise Architecture Is Heading Next
Large enterprise software stacks with expansive capabilities will almost certainly be disaggregated into capability platforms for a hybrid workforce of humans and AI agents to operate. These capabilities will sit alongside an extensive ecosystem of others, orchestrated centrally wherever possible, and underpinned by an operating model control plane sitting across data quality, governance, and interoperability. The competitive ground in software will shift from the perimeters of applications to the ownership of agentic orchestration and decision making. And that operating model control plane is where agents and humans meet, but it remains to be seen how that will work in practice. Ultimately, this space is where financial services technology buyers and their suppliers will also need to converge. Otherwise, their disconnected strategies could drive fragmentation of approach, standards, and methods, increasing frailty in the underlying business services. The opposite of the enduring value financial services firms are trying to offer their customers. In financial control, this convergence matters even more because the operating model itself is the product.
The Destination Is Trust
In our business, the “why” for our customers is trust, accuracy, and confidence. That trust is built on data. Without accurate, well-governed data, no amount of AI sophistication can produce a result worth relying on. The need for deeply provable results hasn’t changed, simply the range of technologies and approaches available to deliver them. AI is already transforming how financial services operate, and we’re embracing it across our platform, our delivery model, and our customer experience. We’re moving fast where AI creates real, durable value: shortening implementation cycles, improving configurability, enhancing user experience, and embedding intelligence into the heart of financial control.
In the world of financial controls and regulatory compliance, our work starts with the control and moves outward from there. The destination has always been clear. AI is an accelerator, not a substitute. The question isn’t whether AI will reshape the operating model – it will – but whether it will do so in a way that enhances the duty of care financial institutions owe their customers.
A lot of the current AI narrative suggests the opposite – characterising controls as secondary to the technology, alongside an implication that regulations will need to adapt to AI rather than the other way around. It remains to be seen how regulators and the audit profession will adapt to an AI world, but assuming their goals stay centred on protecting people and society, it’s unlikely that adaptation will easily accommodate new risk.
Our customers are excited about what we’ve already delivered – and even more about what’s coming. But what we and our customers are clear about is this: innovation cannot come at the expense of trust, accuracy, or confidence. AI strengthens these outcomes when applied well – and that is the destination.
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