Dive Brief:
- A significant proportion of retail and banking executives expect to spend up to 20% more of their 2026 tech budgets on AI and machine learning, according to a Bain survey released Wednesday. The company surveyed 280 tech executives globally for the report.
- Increased AI investment comes as businesses highlight an ongoing skills shortage in the sector. Seven out of 10 business leaders said capabilities such as data engineering are particularly difficult to source.
- Amid an uptick in AI risk concerns, cybersecurity represents another leading area of enterprise interest. More than half of surveyed leaders ranked cybersecurity among their top three IT priorities.
Dive Insight:
The role of AI within business strategies is changing — and so is the way companies invest in it.
While previously the tech operated on an experimental, peripheral basis, its transition to a core tenet of digital transformation means companies are looking to invest in its integration from the ground up.
That shift aligns with broader spending increases in digital capabilities. Global IT spending is expected to surpass $6.3 trillion in 2026, according to recent Gartner projections, with AI infrastructure, services and software driving enterprise investment.
Sectors including retail, banking and oil and gas are showing particular interest, with agentic AI seen as an opportunity to streamline workflows and shorten production timelines. The appeal is particularly concrete for banks. McKinsey projected AI adoption could cut industry costs by up to 20%, and agentic AI is expected to have the most significant operational impact.
Expectations around ROI are rising alongside investment.
Financial institutions are targeting use cases with clear productivity gains, including automating customer service, accelerating software development and streamlining internal workflows.
Leading firms are investing heavily in AI agents, with banks such as BNY, Capital One and JPMorgan Chase building architecture for agent-specific workflows. Enthusiasm is, however, tempered by concerns over costs and demonstrating tangible outcomes.
Talent shortages also remain an obstacle to fully meeting companies’ demands.
Executives across industries cited cybersecurity, AI/ML engineering and data science as among the hardest skills for which to source talent, according to Bain’s report. Application programming interface engineering, full-stack cloud-native engineering and cloud modernization were also highlighted across sectors.
