As governments and businesses across the Middle East accelerate investment in artificial intelligence, finance professionals are calling for stronger governance, better data foundations and enhanced workforce capabilities to ensure AI-generated insights can be trusted and used effectively.
A new report from the Association of Chartered Certified Accountants (ACCA), titled Enabling Finance Insight: Bridging Skills and Data Gaps for AI-Enabled Finance, finds that finance teams are increasingly using artificial intelligence and real-time operational data to move beyond traditional reporting and provide more strategic, current and forward-looking insights.
However, 93% of finance professionals surveyed remain concerned about the integrity and verifiability of AI-generated insights, highlighting the challenges organisations face as AI becomes more deeply embedded in financial decision-making.
Finance Teams Take on a More Strategic Role
The growing use of AI is changing the role of finance functions from primarily producing retrospective reports to supporting strategic decision-making across organisations.
Finance professionals are increasingly working with broader sources of information, including real-time operational data and unstructured internal text, while AI technologies are changing how that information is analysed and interpreted.
The trend is particularly significant across the Middle East, where artificial intelligence has become a strategic priority for governments and businesses. GCC economies, including the UAE and Saudi Arabia, are investing in AI as part of wider efforts to diversify their economies, improve productivity and develop globally competitive digital sectors.
As organisations adopt AI across financial operations, finance professionals are increasingly expected to contribute not only to reporting but also to governance, data stewardship, risk management and strategic insight.
93% Concerned About AI-Generated Insights
The ACCA research, based on a global survey of 1,600 finance professionals, highlights both the growing adoption of AI and the concerns surrounding its use.
The findings show that:
- More than 60% of finance teams have increased their use of real-time operational data over the past two years.
- Almost 60% now work collaboratively with IT or data teams.
- 93% remain concerned about the integrity and verifiability of AI-generated insights.
- The biggest barriers to AI adoption include data quality, skills shortages and integrating multiple data sources.
The findings suggest that simply deploying AI tools will not be sufficient. Organisations also need the governance structures, reliable data and professional expertise required to assess whether AI-generated information is accurate and appropriate for business decisions.
Middle East Case Study Highlights Role of Data Foundations
The report includes a Middle East case study involving a major Abu Dhabi-based real estate and hospitality group.
The organisation's finance team transformed its budgeting and reporting processes by replacing complex spreadsheet-based systems with an integrated Power BI platform.
The project involved processing more than 700,000 rows of data, enabling real-time reporting and improving collaboration across the organisation.
The case demonstrates how investment in data infrastructure can strengthen the foundations required for more advanced analytics and responsible AI adoption, while also allowing finance teams to take on a more strategic role.
Data Quality and Skills Remain Major Obstacles
Despite growing interest in AI-enabled finance, organisations continue to face practical challenges.
According to the report, data quality issues and lack of appropriate skills each affect 42% of respondents, while 40% identify difficulties integrating multiple data sources as a barrier.
Strategic priorities were identified by 45% of respondents as a key driver behind increased data analysis for generating insights, while 43% cited regulatory requirements.
These findings indicate that AI adoption is being driven not only by technological ambitions but also by business priorities and increasing regulatory expectations.
Finance Professionals Need New Capabilities
The report also examines how the skills profile of finance professionals is changing.
While organisations increasingly expect finance teams to work with AI and advanced analytics, the research identifies a potential mismatch between current capabilities and the skills needed for emerging roles.
Areas requiring greater development include generative AI literacy, predictive analytics, collaboration, data storytelling, data governance and ethics.
As finance professionals become more involved in data and AI-related responsibilities, traditional technical accounting skills will increasingly need to be complemented by critical thinking, analytical capabilities and the ability to communicate complex insights effectively.
Governance Must Keep Pace With AI Adoption
Kush Ahuja, Head of Eurasia and Middle East at ACCA, said finance professionals have an important role in ensuring that AI delivers reliable business outcomes as investment in the technology accelerates across the region.
“AI has the potential to transform how organisations generate insight, but its value depends on strong governance, professional judgement and people with the skills to apply it responsibly,” Ahuja said.
Helen Brand OBE, Chief Executive of ACCA, similarly emphasised the need for finance leaders to take an active role in responsible AI adoption.
She said finance teams are evolving from “retrospective reporting engines” into strategic enablers of enterprise-wide insight, while stressing the importance of upskilling, critical thinking, sceptical validation and ethical approaches to AI.
From AI Adoption to AI Value
The ACCA report argues that organisations should distinguish between using AI primarily to improve productivity and using it to generate measurable business value.
Its recommendations focus on strengthening data foundations, responsible stewardship of data and AI, developing critical capabilities and supporting collaboration between finance, technology and data teams.
The report also highlights the need to move beyond informal learning, suggesting that structured upskilling will be necessary as AI-related responsibilities become increasingly embedded within finance functions.
For Middle Eastern organisations investing heavily in artificial intelligence, the findings underline a central challenge: AI adoption may be accelerating, but trust, governance and skills must accelerate with it.

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