AI is already interacting with the workforce in a more natural way and opens the doors for entirely different processes. Solutions for these processes can now be developed not as 1's and 0's, but rather with natural language providing great flexibility and speed to solution.
Therefore, true value to banks will be delivered when costly and long duration processes are reconceived. As banks evolve in maturity with AI and Gen AI, they will begin to give front line employees increasing autonomy and improved tooling that will enable increasing revenue while also reducing non-value add work. But once that tooling is in place and banks begin to reconceive processes there must be a focus to continue to redeploy staff to higher value roles.
The continuous upskilling of teams who use these new tools to do mire is not a one-time effort, it should be built into the talent model and measured. Banks who simply implement AI and GenAI to augment existing processes will likely not see the full value realization and could in fact only see increased costs. Banks who leverage AI and GenAI to support continuous transformation and improvement can take the foundational investments already made (e.g. cloud and data) and unlock further value.
Considering these points, the FinTech subsector is likely to move quickest, due to distinct execution advantages. Namely:
The relative simplicity of their current operating models (considering products, processes, technology, data and organization) makes them less encumbered by the constraints of legacy systems and processes. They still have the flexibility to jump straight to newly-conceived processes without lengthy re-engineering of legacy.
They typically have a culture tilted to more rapide growth and innovation - their greater risk appetite means they will be willing to push AI capability to customers and intro production processes sooner. But there are risks associated with doing this, before having the appropriate guardrails and risk infrastructure in place.
Source: Deloitte