Reflecting on the defining trends of the finance sector, one undeniable spotlight emerged—the mainstreaming of artificial intelligence (AI). The success of Open AI’s ChatGPT played a pivotal role in shifting perceptions from skepticism to active discourse within the business world. Previously hesitant to embrace AI, companies transitioned from keeping it at arm’s length to acknowledging its potential contributions.
From boardrooms to conference halls, discussions revolved around AI and generative AI solutions customized for various functions, like the flagship GiaGPT solution designed specifically for finance and credit. But even with heightened interest, the journey from fascination to implementation could best be described as a gradual process for most companies in 2023.
“Despite AI’s potential, most finance functions’ AI implementations have remained limited,” said Marco Steecker, senior principal in the Gartner Finance Practice. “As they begin to chart out a plan for how best to prioritize that additional investment, CFOs should partner with their finance leadership teams to compare their current progress against their peers’ and identify concrete recommendations from early adopters on how best to accelerate AI use.”
Those who have implemented AI into the finance function at some levels of significance have found that some simple rules for the road are helping drive noteworthy successes, according to recent Gartner studies, among others.
Strategies for AI Implementation Success
It may seem counterintuitive: implementing the front edge of technology while also aiming to keep such a change simple (for the most part). But that’s exactly what’s paying dividends for most of 39% of organizations currently using AI in the finance function, according to a recent Gartner Inc. survey.
This was the three-step roadmap Gartner laid out to help ensure the switch to AI-based automation and autonomous finance a successful endeavor:
1. Remember that “transformative” results take time
Although short-term benefits from AI are possible through simple or purchased solutions, the transformative value of AI in finance requires a level of maturity that takes time to build.
2. Data science emerges are a new role in finance
Most of the finance teams in the survey reported using data scientists. Once seen as a risky and frivolous headcount, modern finance teams commonly use data scientists whether they leverage AI or not.
3. Acceptance plays a role in AI’s success
Organizations with a high level of AI acceptance report a high level of success. Without the buy-in from knowledgeable process owners, building AI-driven processes that emulate their decisions and actions proves difficult.
“These three quite simple factors have an impact on success rates with AI in the finance functions,” said Mark McDonald, senior director analyst in the Gartner Finance Practice. “Put the data scientists close to the processes and people that will train AI, make sure those people understand that AI can make their jobs easier, and give them the time needed to produce transformative results.”
The Landscape of AI Adoption
Gartner’s survey reveals that while 39% of respondents actively use AI in finance functions, another 29% have plans to do so. However, a significant portion of this 29% is still in the initial
phases of implementation or planning. Small businesses, as per Bredin Insights and Constant Contact research, exhibit a lower AI adoption rate, with short-term plans focusing on virtual/digital assistants or website/social media analytics.
Yet, Constant Contact’s findings underscore the success of small businesses actively using AI—91% reported increased success, with 60% noting time savings and improved staff efficiency.
“AI has been around for years, but it has finally matured to a point where it is making a real difference for small businesses,” said Laura Goldberg, chief marketing officer at Constant Contact. “Our report shows that small businesses who harness the power of AI and marketing automation to solve their biggest challenges, like acquiring new customers and creating more memorable experiences, are much better positioned for success.
Gartner noted that larger business’ financial leaders agree that their adoption so far has proven largely positive, even in its earliest days.
“This should be encouraging news for CFOs and other finance leaders who are contemplating whether they should invest and, if so, where they should direct that initial investment,” added Steecker.
Across the board, however, study after study finds that those dragging their feet cite a lack of familiarity, fear of the learning curve and, of course, the cost to implement are two of the biggest factors holding businesses back. Notably, a cautious approach to implementation can prove costly in the long run.
The Unyielding Reality of AI Costs
Addressing the concern of costs, Gartner anticipates that the transition to AI-based solutions will not become more affordable for businesses over time. Financial leaders, keenly aware of
this reality, anticipate a substantial increase in the cost and effort to implement AI changes—52% expect a rise of at least 10% in the near term. In conclusion, as the finance sector traverses the landscape of AI adoption, early adopters illuminate a path of strategic patience, data science integration, and organizational acceptance as key drivers of success. While challenges persist, the undeniable benefits make the investment in AI an imperative consideration for CFOs and financial leaders navigating the evolving financial landscape.
