AI Adoption in Enterprise Finance: A Year of Steady Growth
The adoption of artificial intelligence (AI) in enterprise finance teams remains on par with anticipated trends for 2024, despite escalating optimism surrounding the technology. This insight was revealed in a recent survey conducted by Gartner.
Current Adoption Statistics
In the survey of 183 CFOs and senior financial leaders, 59% reported utilizing AI in their departments, a slight increase from 58% the previous year. While overall adoption within the finance function is progressing at a slower pace, 67% of those employing AI expressed greater optimism about its potential compared to the previous year.
Overcoming Challenges for AI Integration
Marco Steecker, senior research director in Gartner’s finance practice, emphasized that this growing confidence indicates that organizations tackling the complexities and hurdles associated with AI adoption are starting to reap significant benefits. He noted, “As AI technology evolves to cater to a broader array of use cases, CFOs are likely to witness a positive cycle between the advancement of AI in finance and emerging opportunities for leveraging this technology.”
Future AI Spending Predictions
Looking ahead, Gartner forecasts that global AI spending could reach nearly $1.5 trillion by 2025, surpassing $2 trillion in 2026. Major tech companies, known for their extensive investments in AI, are actively experimenting with the technology to enhance internal processes.
A Cautious Approach to Implementation
Danielle Fontaine, deputy controller at ServiceNow, articulated a thoughtful approach to AI adoption by stating, “We like to call it drinking our own champagne,” during a recent virtual conference organized by Financial Executives International. This underscores the careful consideration that leaders within significant tech firms are applying as they explore AI’s transformative potential without rushing into large-scale projects.
Key AI Use Cases in Finance
Gartner’s findings spotlight three prominent use cases of AI within the finance sector: knowledge management (49%), accounts payable automation (37%), and error detection (34%). Moreover, Steecker highlighted the potential of emerging use cases such as code generation, which is recognized by finance leaders as having substantial impact, enabling teams to uncover personalized opportunities for greater automation and insights.
Barriers to Widespread Adoption
Despite the optimistic outlook, Gartner identified two main factors hampering more widespread AI adoption. A minority within the financial services sector remains skeptical, with 16% of respondents indicating no AI implementation plans for the upcoming year. Additionally, 25% of finance organizations are uncertain about transitioning effectively from planning phases to pilot execution. Challenges such as data literacy and inadequate data quality continue to hinder progress.
Achieving Tangible Results
While initial AI pilot projects may yield low to moderate impact for the majority of organizations, those that successfully navigate the initial challenges can experience substantial benefits. According to the study, organizations employing AI are over twice as likely to achieve moderate impact and nearly three times more likely to see significant advantages. Steecker concludes by advising finance leaders to prioritize the acceleration of promising AI projects from the nascent stages to realize greater productivity and effectiveness.