The concept of overestimating the impact of new technologies in the short term and underestimating their impact in the long term—Amara's Law—reminds us to consider the broader context and timeline when predicting technological advancements.
Amara’s Law can certainly be applied to the use of AI in corporate finance, where some quarters assume it can revolutionize finance departments overnight.
Yes, artificial intelligence has a lot to offer in terms of automating repetitive, time-consuming tasks and generating valuable insights. It can also improve the working conditions of finance professionals by allowing them to concentrate on more strategic tasks.
However, this can only be achieved with a clear plan for what the technology will deliver, supported by high-quality data and insights from finance staff who have received the appropriate training.
After a relatively slow start compared to other corporate functions, the use of AI by finance teams has accelerated over the last year. This should come as little surprise given the capacity for AI to automate manual tasks and enable finance professionals to adopt more of a strategic role within their organization, informed by the insights generated by systems that can analyze and identify patterns in huge volumes of information.
Given the increasingly prominent role played by chief financial officers, finance directors, and other senior finance staff in shaping corporate strategy, it makes sense to maximize the value of those with the greatest insight into the business's financial health.
Taulia recently commissioned a survey of more than 600 directors and decision-makers in finance and treasury functions earlier this year to assess the impact of AI on financial decision-making. The topline finding was that AI-generated data insights were the most valued resource for helping these senior managers make commercially important decisions within their business.
At a regional level, just over three-quarters of Australian respondents said AI had a major influence over decision-making within their finance functions and a similar percentage in Singapore were using AI-generated data insights to make commercially important decisions.
None of the German survey respondents felt AI had a negative impact on their ability to make decisions, while their counterparts in France only 1% had no plans to use AI in their finance functions over the next 12 months.
Other markets still need to catch up. In the US and UK, for example, directors and decision-makers are still guided more by internal and external data, respectively.
AI is already influencing decision-making
Six out of 10 of the companies surveyed were using AI in their finance function, and only 1% had no plans to use the technology over the next five years. Inventory and supply chain management was the department that was seen as having the most to gain from the deployment of AI.
Almost half (45%) of the directors and decision-makers surveyed for the report said they planned to expand their team by bringing in new expertise and increasing AI-related headcount.
The influence of AI within specific industry segments was particularly strong. Among utilities and energy companies, 71% of respondents said AI had a major influence on decision-making within their finance functions while 96% said it had a positive impact on those decisions.
Two-thirds of respondents from IT and computing companies were using AI-generated data insights to make commercially important decisions, and more than half were planning to integrate AI with internal expertise, data, and insights to generate new outcomes.
There has also been a closing of the gap in the use of AI by different departments. Finance functions were slower to commit to AI solutions than other administrative functions, such as HR and procurement, but this gap has narrowed considerably.
