The Biggest AI Mistakes Finance Leaders Are Making in 2026

Artificial Intelligence
22.07.2026 11:19 am

AI adoption in finance has hit record levels, reaching 97% of the industry embedding AI solutions into teams.

UK organisations are developing AI governance frameworks but are using their responsiveness to take shortcuts and adopt AI for day-to-day decision-making. Finance leaders are hurrying to keep up with the AI rush in 2026 but are failing to review all variables, diving headfirst into AI adoption and leaving them at risk.

According to Gavin McGahey, CTO of AccountsIQ: “Finance teams are now expected to trust AI-generated insights despite not knowing how they were created. Teams are being pushed to act on AI recommendations and defend decisions to stakeholders, which is a dangerous game. 

“This is just one of many examples of the mistakes that finance leaders are making with AI, as without knowing how AI-generated insights were sourced, finance teams can take responsibility as they did not produce the initial recommendation.”

Considering this, McGahey has outlined the following AI mistakes leaders are currently making.

Skipping over governance

Compliance is falling short with existing frameworks focusing on data protection, security, and regulatory adherence. 

“Frameworks are failing to address explainability (if AI-generated insights can be clearly understood), Auditability, (if AI-driven processes can be reliably verified) and perceived fairness (if stakeholders can trust AI-driven outcomes),” added McGahey.
 
“With so many teams utilising AI to streamline their operations, simply following regulations is not enough to drive consistent confidence in financial decision-making. Financial leaders cannot rely on standalone tools and should be prioritising in-workflow AI solutions that support finance processes while maintaining full control and audibility.”

Trusting AI outputs with verification

In May, an EY report on loyalty reward programmes was withdrawn following an investigation finding that most of its citations were AI-generated.

Furthermore, an October 2025 KPMG report on customer experience and agentic AI from KPMG was found to contain a range of hallucinations following a GPT Zero investigation. The report consisted of fabricated case studies that claimed that the likes of UBS, the NHS, Swiss Federal Railways and Transport for London were using AI in ways that were proven to be untrue.

“Too many leaders are allowing AI-generated insights and numbers to proceed without proper verification against source data,” McGahey continued. “AI tools are known for adding in multiple layers of interpretations on top of processing data, with these inferred outputs offering limited visibility into how they were produced.”

“To combat this, finance teams can use screening tools to ensure compliant finance systems designed for AI regulation are implemented, allowing leaders to gain visibility and trust in newly adopted AI solutions.”

A lack of human judgement

“Finance leaders cannot risk relying on AI without control and transparency.. Their teams need regular human oversight of their AI use so they can take accountability for decision-making supported by AI data. AI should only be used to complete manual work, freeing up teams for strategic tasks,” said McGahey.

“A mistake from an AI model affects every dashboard, portfolio and decision output, rather than being a single mistake that can be contained. Reputational damage will outweigh savings on cost and clients, and regulators will not be very forgiving when learning of an AI-driven incident.” 

Rolling out AI without preparing finance teams

“The UK is facing an ever-growing AI skills gap, with 15% of CFO’s claiming that their teams were confident in their AI use.

“Investment in AI training is significantly lacking across finance teams, with 34% of finance leaders claiming that they are not getting enough. If finance leaders are poised to integrate AI solutions into their teams, then they need to ensure that they have an appropriate training plan in place. There is no point in leading investing in AI if they're not committed to investing in their teams to support its use. AI should not be treated as an IT deployment.

“Too many leaders are underinvesting in their people while overinvesting in AI solutions. Nevertheless, teams should be encouraged to use AI, but only with guided collective intent and encouragement to use it both responsibly and cautiously.

“Finance teams are continuing to rely on AI-driven insights and tools to support daily activities. The real challenge facing finance leaders is not ensuring that data is protected, but that decisions made on the data are transparent, explainable and trustworthy,” concluded McGahey.