Tom Pirone, Industry Lead for Financial Services, Appian As banks enter 2026, the industry finds itself at an inflection point where artificial intelligence (AI), digital ledgers, and other advanced technologies are moving further into the operational core of financial services. The vast majority of financial institutions now have some form of
AI embedded in their technology stack, and
digital ledger technology adoption is accelerating to help streamline payments, tokenize assets, and improve post-trade settlement. All the while,
regulatory shifts are forcing firms to adapt to new governance models and frameworks for KYC, AML, fraud prevention, and other forms of governance.
Against this backdrop, 2026 will favor institutions that can innovate responsibly, balancing the promise of technology to orchestrate processes across multiple transaction rails while ensuring proper controls and governance remain solidly in place. Here are six predictions that define the conditions under which firms will be working to strike this balance:
1. AI implementations will become a core competency, not a pilot program – In 2026, banks will be judged less on whether they “use AI” and more on how effectively they operationalize it. Institutions will define success by their ability to embed AI into end-to-end processes, define measurable performance indicators, and ensure human oversight is built into decision points. AI that cannot demonstrate accuracy, transparency, and repeatability will increasingly be viewed as a liability rather than an asset, especially in regulated workflows.
2. Perpetual KYC will shift from concept to regulatory expectation – What has long been discussed as “perpetual KYC” will begin to harden into regulatory expectation. Rather than periodic reviews conducted every few years, banks will be expected to trigger KYC refreshes dynamically based on risk signals. The challenge will not just be collecting more data, but also filtering intelligently for relevance, reducing false positives, and invoking reviews only when justified. Institutions that can orchestrate continuous KYC efficiently will gain both compliance and cost advantages.
3. Practical applications for digital ledger technology will expand dramatically – Digital ledger technology will move more fully into the operational mainstream. As consumer and corporate expectations evolve, banks will be required to support ever-more seamless interactions between traditional accounts and digital wallets. Tokenization initiatives, stablecoin discussions, and early real-world implementations will push institutions toward multi-rail transaction orchestration.
4. The convergence of AI, digital ledgers, and economic volatility will redefine operations – While each of these forces is significant on its own, their convergence will define the next operating model for banking. AI will drive real-time decisioning; digital ledgers will enable faster and more transparent settlement; and economic uncertainty will demand resilience and flexibility. Banks that view these factors as interrelated and adopt a holistic strategy that manages their impacts across the entire operation will be better positioned to adapt under pressure.
5. Fraud and financial crime will escalate faster than controls unless modernization accelerates – As payment systems become faster and more interconnected, fraudsters continue to innovate aggressively. Real-time payments, cross-border complexity, and fragmented systems expand the attack surface. In response, banks will need better orchestration across systems, AI-enhanced pattern recognition, and faster feedback loops between detection and response. Static controls will prove insufficient in an increasingly dynamic threat landscape.
6. Transparency and governance will become non-negotiable standards for AI – Regulators are demanding clearer explanations for how AI-driven decisions are made. Black-box models will face increasing scrutiny, particularly in areas affecting customer outcomes and risk management. Banks will need to demonstrate data privacy controls, human-in-the-loop oversight, and auditable decision paths. As this happens, transparency will emerge not only as a compliance requirement, but as a market differentiator for trust.
What These Predictions Mean in Practice
All the predictions above will play out against the backdrop of an industry that must modernize without destabilizing core operations. Banks will need platforms and architectures that support continuous change, integrating new capabilities without introducing unnecessary complexity, operational risk, or governance blind spots.
At the infrastructure level, platforms will be required that can engage AI across the full lifecycle of a process. The ideal foundation for this is a robust data fabric capable of drawing from diverse internal and external sources without relying solely on rigid integrations or point-to-point automation. Institutions should also seek to apply AI selectively and contextually across workflows, allowing teams to determine where automation adds value and where human judgment must remain central.
Resilient platforms will also support reuse and adaptability. AI capabilities should not be locked into single use cases but designed as reusable skills that can be invoked at different points in a process, including document handling, decision support, and exception management. This flexibility allows banks to address unique customer and regulatory requirements without repeated re-engineering.
Finally, institutions must prepare for an increasingly multi-rail world, where traditional fiat systems coexist with digital-ledger-based transactions. Infrastructure must be able to orchestrate activity across these environments while remaining adaptable to regulatory changes, economic shifts, and emerging technologies. Platforms that combine end-to-end visibility, process intelligence, and AI-driven insights supported by human oversight will be best positioned to identify bottlenecks, optimize performance, and evolve safely over time.
Conclusion
The year ahead marks a turning point for banking as transparency, flexibility, and measurable outcomes emerge as the defining characteristics of leadership in 2026. Institutions will not be evaluated simply for whether they have embraced AI, modernization, or digital assets, but rather on how well they integrate these capabilities in real-world systems to create demonstrated value and efficiency gains. For banks willing to rethink how technology, processes, and governance intersect, the opportunity is significant in a sector that increasingly rewards clarity, adaptability, and operational discipline.
