Why Incremental Progress on AI in Banking Will Be the Best Way Forward
“In our incremental AI landscape, choosing partners that value a financial institution’s relationship with its employees (and those employees’ relationships to customers) will be critical. Humans will play a significant part in banking processes for a long time – as they should, given the risks of getting things wrong in our industry. They should feel empowered by technology, becoming superusers while managing the risk involved with AI processes and ensuring there is no break in the customer experience. Banks have been experts in risk management for a long time – this is their time to shine.”
AI can help banks unleash a new era of software engineering productivity
“As AI models advance, they should boost the productivity of software engineers across the software development life cycle—including designing, developing, testing, and maintaining software—and reduce total software spend.6 In aggregate, Deloitte predicts that AI tools will help save between 20% and 40% in software investments for the banking industry by 2028 (see “About this prediction”). But on a per-engineer basis, Deloitte estimates cost savings of US$0.5 million to US$1.1 million by 2028 (figure 1).”
The Banking AI Adoption Gap: Leaders pull ahead while others struggle to catch up
“The path forward for banks to adopt AI
For financial institutions looking to close the AI adoption gap, Evident’s research suggests several priority actions:
- Invest in data infrastructure before chasing the latest AI applications
- Establish clear leadership commitment with measurable AI adoption targets
- Develop practical ROI measurement frameworks, acknowledging their imperfections
- Consider organizational structures that attract elite AI talent
- Look for strategic opportunities in agentic AI, not just generative
- Build on existing risk management frameworks for responsible AI governance”