Finance teams brace for rising AI risks, fatigue & compliance in 2026

Finance and compliance teams are preparing for a year of increased risk and operational challenges in 2026, driven by rising adoption of AI tools and evolving global regulations. Experts point to shifts in fraud threats, productivity concerns, compliance requirements, and infrastructure bottlenecks as key areas set to shape business strategies in the coming year.

AI-driven fraud

As generative AI becomes increasingly sophisticated and accessible, finance professionals are facing heightened exposure to synthetic expense claims. According to Medius research, a substantial number of finance staff are already struggling to detect AI-generated documents.

"Medius research shows almost one in three finance professionals admit they wouldn't recognise an AI-generated receipt if it landed on their desk, whilst 30% are already seeing a rise in fabricated claims since GPT-5 came into effect. That blind spot will only widen in 2026 as generative AI becomes more realistic and accessible. In the coming year, finance leaders will need to shift their focus from traditional compliance to real-time verification. GPT-5 has shown how easily synthetic data can pass for real. 2026 will be the year finance teams start thinking like fraud investigators. The question won't be 'is it approved?' but 'is it authentic? For that, finance teams need intelligent anomaly detection systems, not manual guesswork, to stay ahead of what's coming."

Workplace fatigue

With repetitive administrative work persisting across finance departments, productivity and morale are coming under increasing pressure. Research conducted by Medius highlights significant fatigue among finance teams, raising the risk of error and making organisations more vulnerable to fraud.

"Repetition is quietly eroding productivity across finance departments. Our research into workplace fatigue has found finance professionals lose focus after just 41 minutes of repetitive work - and 74% are considering quitting over it. The cost isn't just morale; it's measurable in mistakes, with a quarter of finance workers admitting they've missed signs of fraud due to distraction. In 2026, finance leaders will need to tackle this "boredom dividend." The shift will need to be away from low-value admin towards analysis, forecasting, and decision support. The most progressive teams will start treating attention as a finite resource and design processes that protect it. Automation in the right places should give finance professionals their time back, and the ability to take on tasks that provide better fulfilment," said Chris Wilmot, Chief Financial Officer, Medius.

Compliance evolution

AI is transforming how companies interact with customers and conduct internal operations, with regulators responding by expanding compliance requirements. Chatbots and AI agents now fall under regulatory scrutiny, especially in tightly regulated sectors.

"As chatbots and AI agents handle more customer and internal conversations, regulators are paying attention. Organisations will need to archive and manage these AI-based interactions like any other communication for compliance purposes- particularly in regulated industries like financial services. Soon, 'machine-generated' messages will be just as much a compliance concern as human ones," said George Tziahanas, Vice President of Compliance, Archive360.

Data sovereignty

Governments are redefining data protection as a matter of strategic national interest, leading to new digital borders that influence how and where data-including that generated or processed by AI-can move and be stored. These changes complicate compliance for international businesses and could fragment the global regulatory landscape.

"Data protection is moving beyond traditional security concerns. Countries are now treating strategic data as a "national interest", creating digital borders that control how AI and data can be used across markets. This will create digital "iron curtains" as nations invest heavily in AI infrastructure and compete to maintain control over their strategic data assets. For businesses, this means navigating a patchwork of rules that go well beyond privacy," said Tziahanas.

Boardroom trade-offs

Business leaders are confronting difficult decisions over how quickly to embrace AI, weighing the benefits of innovation against increased risks of data breaches and regulatory non-compliance.

"Boards will face a constant trade-off: adopt AI quickly and accept governance and data exposure risks or move cautiously and risk falling behind. This weigh-up may well mean we will see more data breaches and cybersecurity incidents related to poorly secured AI and underlying data. Yet, how well an organisation balances these risks will define its competitive edge," said Tziahanas.

Infrastructure challenges

As AI workloads grow, available power and robust physical infrastructure are becoming limiting factors for national and industry competitiveness. Countries that fail to support sufficient data centre expansion risk falling behind in AI adoption and capability.

"AI needs power and lots of it. Government decisions around energy policy and data center infrastructure will create significant regional advantages or disadvantages in AI capabilities. Countries that cannot provide sufficient power for data centers will fall behind in the global AI race, regardless of their regulatory frameworks," said Tziahanas.

Adoption pace

Enterprise use of agentic AI-AI systems that act autonomously within business workflows-will remain gradual rather than widespread in the short term.

"AI agents are not taking over enterprise workflows overnight. Instead, they will augment existing software systems, as these platforms' workflows are too complex for AI to fully disrupt in a single year. Scaling agentic AI takes infrastructure, governance, and compliance considerations, particularly in regulated industries. Therefore, the adoption we will see is set to be gradual, not explosive," said Tziahanas.