Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Ravi Nemalikanti, Abrigo
Two decades ago, the internet quietly began rewriting how banking worked. What started with simple online account access soon reshaped customer expectations, operational models and competitive dynamics. Banks that moved early gained durable advantages in reach and efficiency. Those that waited spent years trying to catch up as digital-first players redefined speed and convenience.
AI is now creating that same kind of inflection point, only faster. What took a decade during the internet or even the mobile era is compressing into months with generative AI. Core workflows are shifting from manual to agent assisted, decisions are becoming more data driven, and customer interactions are growing more intelligent. AI is slated to become the new operating system for community banks, and institutions will begin weaving it into the fabric of everyday operations rather than treating it as an experiment.
In 2026, banks will increasingly rely on AI-powered solutions for critical tasks such as enhanced monitoring, decision-making and process optimization. Nearly 40% of institutions plan to adopt or expand AI and automation tools in 2026, according to Abrigo’s survey of 157 bankers. The data reinforces what leaders are already seeing on the ground: AI has moved from a theoretical advancement to a practical requirement for institutions seeking efficiency and competitiveness.
One of the clearest areas where this shift will be felt is in banks’ pursuit of growth while managing risk. Generative AI helps speed credit decision workflows by cutting manual work behind the scenes such as by automating document and borrower data summarization. It also introduces new capabilities, such as AI-driven pattern detection for early risk indicators, which would be difficult to scale manually. This acceleration aligns directly with strategic priorities: 73.9% of banks say expanding loan and deposit growth is their top focus for 2026, according to Abrigo’s survey. With lending volume and speed so closely linked to revenue, banks have a strong incentive to adopt AI tools that enhance and speed decision-making without compromising risk management.
The impact, however, won’t be limited to credit, underwriting or back-office functions, as customer-facing channels will also quickly change. Nearly half (45.9%) of institutions in the survey cite improving digital customer experience as a key 2026 priority, suggesting that AI adoption will shape how banks interact with customers every day. In practice, more banks will use generative AI for direct customer chats, contextual responses and real-time document summarization and analysis for bank employees during conversations. As customer expectations continue to rise, AI becomes both a competitive necessity and an operational advantage.
Yet these gains are only possible if banks have the infrastructure to support them. Some 34.4% of banks cite legacy systems as a major challenge to reaching their 2026 goals, and 28.7% cite data quality and integrity issues, which can impede AI implementation. Modern AI systems require powerful compute and networking, as well as high-quality data and secure, resilient storage systems. Without these foundations, even the most advanced AI models can’t operate with accuracy, speed or reliability that’s critical in financial environments. These systems also must be secure and resilient to protect sensitive data and ensure that it is accessible for critical functions in case of disruptions or outages.
Agentic AI and emerging agent-to-agent protocols may become a key integration strategy for banks to leverage modern capabilities with legacy systems. This will unlock faster product launches, easier fintech partnerships and a better experience for their customers and employees. But AI-readiness remains uneven, and banks are approaching AI adoption from very different starting points.
While 45.9% are exploring AI, and 29.9% have partial pilots, only 4.5% feel fully ready. Meanwhile, 60.5% lack internal expertise, 43.3% face budget constraints, 40.8% are concerned about regulation and 33.1% struggle with ROI clarity. As a result, expectations should be kept within realistic timeframes, despite the tremendous potential.
Despite these challenges, GenAI will be a key factor in defining competitive advantage in 2026. Banks are looking to move beyond experimentation to adopt AI applications that provide clear efficiencies, cost savings or better experiences for customers and employees. Core upgrades and AI adoption in 2026 will set the stage for even greater transformation in 2027. Institutions that invest early with a thoughtful approach will be best positioned to lead in a market where innovation, speed and data-driven intelligence are essential.
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ABOUT THE AUTHOR
Ravi Nemalikanti is Abrigo‘s chief product and technology officer, responsible for leading the company’s technology strategy and setting product and development priorities to drive innovation and strengthen competitive advantage.
