In the Gartner’s 2025 AI in Finance Survey, 59% of finance leaders reported using AI in 2025, a figure that held steady from the year prior. Rather than signaling stalled momentum, we see this stability as a shift toward more deliberate, sustained use across established workflows. 

Companies expressing optimism and confidence in AI are the ones mainly using it for practical applications. According to Gartner, the most common applications of AI in finance include knowledge management, accounts payable automation, and error and anomaly detection. The goal is to reduce manual work and improve accuracy in areas that already operate at scale. 

Impact is rarely immediate. Gartner reports that most organizations initially see low to moderate results, with stronger outcomes emerging as AI becomes embedded into production environments. It comes down to whether organizations are committing to operationalizing AI over time or simply relying on limited or experimental deployments. 

Workplace behavior reflects the same pattern. Gallup’s Q4 2025 data shows that while overall AI adoption has leveled off, usage among existing users continues to deepen. 26% of U.S. employees now use AI at least a few times a week, with adoption highest in finance and other knowledge-based roles where AI naturally supports document-heavy and analytical work. 

In addition to day-to-day operations, financial institutions are finding impactful applications to enhance customer and user experience. Since it’s launch in 2018, Bank of America’s virtual assistant Erica has supported nearly 50 million users, surpassed 3 billion client interactions, and now averages more than 58 million interactions per month.  

Clients have engaged with more than 1.7 billion proactive, personalized insights, and Bank of America reports that over 98% of users find the information they need—a signal that AI‑driven assistance is delivering consistently positive customer experiences while reducing call‑center volume and freeing advisors to focus on more complex conversations. 

Heading into 2026, there seems to be a stronger emphasis on reliability. Data quality, governance, and workforce readiness are top of mind for many leaders. As AI becomes more embedded, its value will be heavily tied to its ability support the work people already do, but at scale.  

Across banking and insurance, fraud, social engineering, and organized financial crime continue to evolve across all functions. The Federal Reserve’s November 2025 Financial Stability Report points to a steady rise in cyber‑related financial crime, noting that attacks are becoming more complex and harder to isolate. What once affected individual institutions now has the potential to ripple across interconnected systems, increasing both operational and financial risk. 

Speed is a big part of the challenge. Faster payment rails and always‑on digital access allows bad actors to move just as quickly as customers. The Federal Reserve notes that as these channels expand, controls need to expand with it. Not only that, they need to be able to operate in real time, rather than waiting for reviews after the fact. 

Technology is also changing how financial crime shows up. The report highlights that emerging AI tools can be used to scale attacks and make them more targeted. At the same time, those same technologies are becoming essential for institutions trying to detect unusual behavior before it causes harm. In other words, technology is unlocking new capabilities for both cyber offense and defense in what feels like a “chicken or the egg” call-and-response. 

Overall, there is a stronger emphasis on prevention over reconciliation. Rather than concentrating efforts on recovery alone, organizations are working to identify patterns earlier and share signals more effectively across systems. When done well, this approach can help teams act quickly without adding unnecessary friction for customers. 

The goal is not just stronger defenses, but empowering systems to keep up. 

Before, it was enough for anti-money laundering (AML) and know-your-customer (KYC) solutions to be treated as something assessed once and revisited later. However, rising threats are forcing organizations to reevaluate their current systems. 

Across the industry, fragmentation is driving this shift throughout organizations. Customer data, transaction activity, identity signals, and sanctions screening often live in different systems, making it harder to see risk clearly as it changes. As a result, institutions are under pressure to connect those signals and maintain a more current view of who they’re doing business with. 

Gartner’s research on AML and fraud use cases shows banks moving toward continuous monitoring, smarter alerting, and AI‑enabled anomaly detection. Like many other functions across the industry, the goal is to reduce manual review and prioritize more meaningful insights and alerts. 

And it’s not just organizations. Regulators like FinCEN reinforcing this direction. In the last couple years especially, FinCEN has emphasized risk‑based, technology‑driven AML programs and is encouraging institutions to modernize how they manage customer risk over time. Expectations are rising around how AML programs operate day to day and how institutions explain and stand behind their decisions. 

As operations grow more interconnected, leaders will need to pay closer attention to how reliably their organizations can continue serving customers when systems are disrupted. 

Beyond cyber incidents, situations like cloud outages, third‑party failures, data‑center disruptions, and platform dependencies can all interrupt critical services. When core functions—payments, claims processing, or customer access—depend on shared infrastructure, a problem outside the organization can still have immediate impact. 

The Federal Reserve’s November 2025 Financial Stability Report reflects this shift, with 61% of market participants citing policy uncertainty and nearly half pointing to geopolitical risk as key threats—signals that institutions are planning for disruption, not reacting to it.  

Global conditions add another layer of complexity. Analysis from the World Economic Forum (WEF) estimates that geoeconomic fragmentation could cost the global economy up to $5.7 trillion, underscoring how external shocks and system fragmentation are becoming structural risks rather than temporary disruptions. For institutions operating across regions, this can affect decisions about vendors, infrastructure, and even continuity planning. 

Going forward, operational resilience will become more and more of a baseline expectation. Organizations that are better positioned seem to be building awareness and treating resilience as part of how the business runs day to day. 

Though data quality rarely gets the spotlight, it’s hard to deny its role in shaping what banks and insurers can do next. AI, personalization, pricing, and risk decisions all rely on data, and many organizations are still working through fragmentation, inconsistent definitions, and limited lineage. 

What’s changing is how visible the impact has become. Teams that invested in stronger data foundations over the past year are now finding it easier to move faster. They are able to test new ideas and scale what works with ease. When data is easier to access, understand, and govern, downstream efforts tend to follow more naturally. 

U.S. regulators are seeing the same pattern. In its December 2025 Supervision and Regulation Report, the Federal Reserve identifies governance and control weaknesses as the most frequent category of supervisory findings at large financial institutions, including issues tied to information technology, operational risk, and risk management practices. These deficiencies are significant enough to trigger formal supervisory actions, reinforcing how data quality and control discipline now sit at the center of safety‑and‑soundness oversight. 

That gap is still visible at the global level. The Basel Committee’s most recent updates on BCBS 239 implementation show that only 2 of 31 global systemically important banks are fully compliant with risk data aggregation and reporting standards, and that no individual principle has been implemented consistently across all institutions. In its January 2026 update, the Committee reinforces that these shortcomings continue to stem from fragmented data ownership, incomplete lineage, and legacy architectures—pushing firms to treat data as shared infrastructure rather than a byproduct of individual systems. 

This year, and potentially beyond, data quality will be a quiet differentiator to look out for. When platforms and workflows are all commoditized, the factor that could set an organization apart is its data, and more importantly, the quality of that data.  

The moments that build the most trust are when something goes wrong—when a charge looks unfamiliar, a claim gets delayed, or an alert raises more questions than answers.  

Billing issues, claim decisions, fraud alerts, or sudden changes carry more weight than routine transactions. When those situations arise, customers want clarity. How clearly an organization explains what happened, what comes next, and why a decision was made often determines whether confidence holds—or quietly erodes. 

Regarding their data, customers are more likely to trust financial institutions when they understand how their data is used and see that it leads to fewer surprises and clearer outcomes. In financial services, transparency around customer data has become a core component of trust—not just a technical or compliance concern. 

J.D. Power’s 2025 U.S. Retail Banking Satisfaction Study reports a 4% year‑over‑year increase in customers who feel adequately supported by their bank, signaling that trust is closely tied to how institutions handle high‑stress moments.  

Across financial services, trust plays a meaningful role in customer satisfaction, especially when customers feel stressed or uncertain. Feeling supported and informed during these moments continues to influence whether customers stay loyal or begin to look elsewhere. 

Trust also extends beyond individual customer interactions, holding importance at a system level. The WEF has pointed to trust as a factor in keeping confidence in financial systems as technology and global conditions change. Consistency and transparency have helped our partners stay credible when things are moving as fast as they are. 

Trust is becoming a clear line between organizations that retain loyalty and those that struggle to differentiate. Though products and platforms may look similar on the surface, how institutions show up for customers when it matters most is much harder to replicate—and far harder to forget.