September 12, 2024 – A recent Gartner survey reveals that artificial intelligence (AI) adoption within finance functions has reached 58% in 2024. This significant uptake highlights a growing trend among finance leaders embracing AI technologies to enhance their operations.
The survey, which surveyed 121 finance leaders, also indicates that half of the remaining 42% of finance functions not yet utilizing AI are planning to implement it soon.
Rapid AI Integration and Increased Optimism
Marco Steecker, Senior Director of Research in Gartner’s finance practice, observes, “AI adoption in the finance function is advancing quickly.” He also points out that two-thirds of finance leaders are now more optimistic about AI’s impact compared to the previous year, particularly those who have already integrated AI solutions into their processes.
Steecker notes a significant shift from last year, when administrative functions such as HR, legal, and procurement were twice as likely to adopt AI solutions compared to finance. This year, the gap has almost disappeared, reflecting the growing embrace of AI within the finance sector.
Top AI Use Cases in Finance
The Gartner survey identified four prominent AI use cases in finance:
Intelligent Process Automation (44%): Enhancing existing automation tools like Robotic Process Automation (RPA) with AI capabilities to improve information processing.
Anomaly and Error Detection (39%): Utilizing AI to identify and report errors and outliers in large datasets, including internal claims, expenses, and invoices.
Analytics (28%): Leveraging AI to create more accurate financial forecasts and analyses, thereby improving decision-making processes.
Operational Assistance and Augmentation (27%): Implementing AI to simulate human judgment in operational decisions, often through generative AI technologies.
Challenges in AI Adoption
Despite the advancements, finance leaders face notable challenges in AI adoption. Gartner highlights two primary obstacles: inadequate data quality and availability, and insufficient data literacy and technical skills among staff.
Steecker emphasizes the growing difficulty CFOs encounter in sourcing the necessary talent for AI implementation. “As interest in AI rises across various sectors, finding the right talent is becoming increasingly challenging, and this issue is likely to worsen,” he says.
To address these challenges, Steecker advises CFOs to develop a comprehensive strategy for acquiring and cultivating AI skills. The key issues include:
- Limited understanding of the specific roles and skills needed for AI implementation.
- Difficulties in attracting and retaining AI talent.
- Slow progress in developing AI competencies within existing teams.
Recommendations for Data Management
Regarding data quality, Gartner experts recommend moving away from the traditional “single version of the truth” approach. Given the complexity and volume of modern data, achieving this ideal is often impractical. Instead, Gartner suggests adopting a “sufficient versions of the truth” approach, which focuses on balancing data quality with its utility in decision-making processes.
As AI continues to transform the finance sector, these insights from Gartner provide valuable guidance for finance leaders navigating the evolving landscape of artificial intelligence.
