Finance teams embrace AI but 93% question the insights it generates, revealing deep trust crisis

AI adoption rises, but 93% of finance professionals question AI-generated insights: Report

Even as finance teams increasingly adopt artificial intelligence (AI) to improve business decision-making, 93 per cent of finance professionals remain concerned about the integrity and verifiability of AI-generated insights, according to a joint report by ACCA (the Association of Chartered Certified Accountants) and Chartered Accountants Australia and New Zealand (CA ANZ). Even as finance teams increasingly adopt artificial intelligence (AI) to improve business decision-making, 93% of finance professionals remain concerned about the integrity and verifiability of AI-generated insights, according to a joint report by ACCA (the Association of Chartered Certified Accountants) and Chartered Accountants Australia and New Zealand (CA ANZ). The report titled - "Enabling Finance Insight: Bridging Skills and Data Gaps for AI-enabled Finance", based on a global survey of 1,600 finance professionals, said concerns stem from issues such as AI hallucinations, inaccuracies, incomplete datasets, lack of transparency and bias, highlighting the need for stronger governance and upskilling as AI adoption gathers pace. The report said the finance function is moving beyond its traditional role of historical reporting, with organisations increasingly expecting finance teams to provide forward-looking business insights. It noted that "the finance function stands at an unmissable opportunity," as stakeholders demand "proactive leadership - requiring finance to evolve from a retrospective reporting engine into a strategic enabler of enterprise-wide insight." According to the report, while AI is becoming a core part of finance's analytical toolkit, organisations must deploy the technology strategically to create business value rather than simply automate existing processes. "AI is becoming a fundamental component of finance's analytical toolkit - finance leaders must strategically deploy these technologies to generate value, not merely automate existing inefficiencies," it said. The study also found that finance teams are increasingly relying on real-time operational data and AI-powered analysis. More than 60% of finance teams have increased their use of real-time operational data over the past two years, while the use of internal text data such as meeting transcripts, contracts and documents is also growing as generative AI tools become embedded in day-to-day work. However, the report said poor data quality, skills shortages and difficulties in integrating multiple data sources remain the biggest barriers to using AI effectively. Data quality issues and lack of appropriate skills were each cited by 42% of respondents, while 40% pointed to the challenge of integrating data from multiple sources. It also highlighted a widening skills gap as AI adoption accelerates. According to the survey, 72% of respondents reported having only basic or no generative AI skills, although 41% said they are pursuing AI training and upskilling on their own. ACCA Chief Executive Helen Brand said finance leaders must focus on governance alongside technology adoption. "CFOs and finance teams need to lead in the responsible adoption of AI across organisations, ensuring robust training and governance is in place. Critical thinking, sceptical validation and an ethical approach is vital," she said. The report concluded that finance teams are uniquely positioned to lead responsible AI adoption because of their role in governance, data stewardship and performance measurement. It recommended greater investment in structured learning, stronger collaboration with IT and data teams, and improved data governance to ensure AI delivers trusted insights and measurable business value.

The AI Dilemma: 85% of Indian Finance Leaders Pressed for ROI Without Clear Governance

27% of Indian respondents say accountability for significant AI agent errors is unclear or sits with no one, higher than all other markets surveyed Avalara, Inc. today released new research showing that Indian finance teams face mounting pressure to deploy AI agents quickly. This rush to demonstrate measurable ROI is causing governance and internal controls to struggle to keep pace. As a result, more than one in four Indian finance leaders said accountability for significant AI errors was unclear or sits with no one, higher than other markets surveyed. The report, "Agents of Change: How the Race to Deploy AI Agents is Outrunning Financial Governance," surveyed CFOs and senior finance leaders across the US, UK, India, and Australia. 85% of Indian respondents feel moderate or significant career pressure to demonstrate that AI agent investments are delivering ROI. 71% say the pressure to deploy agents is focused primarily on deployment speed, and consequently, while only 8% say their organization prioritizes governance over speed. This speed-first approach is creating a widening governance and compliance gap. 10% of Indian finance leaders say they are not confident they could give a regulator or auditor a clear and complete explanation of an AI agent's actions, much higher than the share reported in the US, UK, and Australia. Furthermore, 24% of Indian finance leaders have not updated their internal controls within the last year to reflect AI agents taking or recommending actions. Only 28% say AI agent controls have been reviewed or tested by IT or cybersecurity teams, while just 34% report review by risk or compliance teams. "While Indian enterprises are moving fast to automate, their internal rulebooks are being left behind," said Dulles Krishnan, VP & General Manager, India Operations at Avalara. "Running new AI tools on outdated compliance policies is a massive blind spot. CFOs in this market need to ensure their risk frameworks are actually updated to monitor automated decisions before an auditor comes knocking." This is compounded by a lack of available knowledge, as 76% lack dedicated in-house expertise to understand how their AI agents work. When asked what would most increase their confidence in expanding AI agents, Indian finance leaders consistently prioritized capabilities that reinforce trust and accountability, including outputs grounded in verified tax and financial data (27%), human review controls for higher risk actions (26%), audit trails documenting every AI action (22%), and stronger vendor commitments around accuracy and accountability (20%). As Indian finance teams embed AI agents more extensively into tax, compliance, and regulatory processes, the survey suggests that confidence in explaining those actions to a regulator will need to catch up with the pace of deployment. Closing that gap will depend less on how quickly AI agents are deployed and more on embedding trusted data, audit trails, governance controls, and documentation from the outset so automated decisions remain transparent, explainable, and audit-ready.

The Big AI Contradiction: 93% of Finance Pros Don't Trust the Tech They're Using

A major report, Enabling finance insight, from two of the world's leading accountancy bodies, reveals a clear trend towards greater use of real-time operational data, with more than 60 per cent of finance teams increasing its use over the past two years to support better business insight and decision-making. This shift from retrospective reporting towards current and forward-looking insights is driven by a greater breadth of data- from real-time operational metrics to unstructured internal text data - and increased use of AI technologies to reshape how data is analysed and interpreted. The global survey of 1,600 finance professionals also reveals a real shift in the way that finance teams are working with data and IT across an organisation. Traditional silos are breaking down, with almost 60 per cent reporting close collaboration with data and IT teams. But the research from ACCA (the Association of Chartered Certified Accountants) and Chartered Accountants Australia and New Zealand (CA ANZ) shows that 93 per cent of finance professionals are concerned by the integrity and verifiability of AI-generated insights. Issues include AI hallucinations, inaccuracies, incomplete data sets, lack of transparency and bias. These findings underline that awareness must be followed by upskilling in this fast-developing area. Md. Sajid Khan, Director - India, ACCA, said: "As organisations embrace AI and real-time data to support decision-making, a core message is the unique position of finance to lead responsible AI adoption across the organisation. With its end-to-end organisational perspective and inherent focus on governance - finance can define AI's business problems, measure its return on investment (ROI), and ensure robust data and AI governance frameworks are in place." ACCA Chief Executive Helen Brand OBE said: "This research shows how finance teams are evolving from retrospective reporting engines into strategic enablers of enterprise-wide insight. This is a great opportunity, but upskilling is critical. CFOs and finance teams need to lead in the responsible adoption of AI across organisations, ensuring robust training and governance is in place. Critical thinking, sceptical validation and an ethical approach is vital." CA ANZ Chief Executive Officer Ainslie van Onselen said: "AI is now a core part of the finance toolkit, but it's not a shortcut. CFOs and finance teams need to use it to sharpen judgement and generate real value, not just speed up old processes. That means investing in structured learning and working more closely with IT and data teams. Upskilling isn't optional. It's how you manage the risk." Data from the survey shows a growing skills gap, with 72 per cent of respondents reporting only basic or no GenAI skills, however 41 per cent are seeking training and upskilling in their own time. As real-time data becomes central to decision-making, thinking critically about its limits is becoming a core skill. Globally, the survey showed strategic priorities (45 per cent) and regulatory requirements (43 per cent) are the key drivers of the increase in data analysis to produce insights. While progress is significant, the report highlights the key areas finance functions need to address to improve business insights: data quality issues (42 per cent), lack of appropriate skills (42 per cent), and difficulty integrating multiple sources (40 per cent). Realising finance's potential as a strategic enabler of insight hinges on developing the right skills and strengthening collaboration. The research examined the talent profile of the modern finance function and found that while ambition is high, execution is threatened by a misalignment between skills and capabilities in areas such as generative AI literacy, predictive analytics, collaboration over coding, storytelling and data governance/ethics. The report aims to equip CFOs and finance leaders with actionable recommendations to help their teams provide trusted insight, effectively steward data, govern AI responsibly, and drive measurable value for the entire organisation.