As companies speed up their digital transformation, CFOs will spend US$3.92tn on information technology this year. According to Clement Christensen, an advisory director at Gartner, “AI will probably be the most important investment that you’ll make in finance, and maybe the broader enterprise for the next 10 years. You have about two to three years to get investing in AI or forever be left behind”.
For those organisations that have piloted AI projects—mostly multinationals at this point—it’s a delicate calculation. AI done well can yield dramatic success. Amazon increased retail sales by almost 20%, UPS saved hundreds of millions of dollars annually, and the Memphis police reduced homicides by 35%. But most companies need over a year to develop a strong, ready-for-market AI application, which can be crippling if you crash and burn.
Are the Risks Worth It?
Currently, most firms use AI to automate select business systems, opting for an ad hoc approach rather than seeking to fully integrate it into their bottom line. They might dabble in AI-based accounts platforms or prototype test projects but never jump all in. Christensen noted that only 25% of AI pilots eventually move to production.
Does this mean that companies should wave the white flag now? Far from it. If anything, it’s time for CFOs to take the last chance to modernise their businesses. In Deloitte’s State of AI in the Enterprise report, the early adopter phase of artificial intelligence is ending. Out of 2,750 companies that had adopted some semblance of AI, 47% had launched several AI systems. Another 26% classed as “seasoned”, meaning that they’d built multiple mature, high-quality AI systems. And in the third quarter of 2020, just as the pandemic was in full swing, accelerated digitalisation—including artificial intelligence—ranked as one of the top CFO strategies to survive the COVID-19 economic crisis.
Once we consider that most competitive firms intend to integrate AI into their daily operations, the risks pale in comparison. There’s a risk in not acting. Without a doubt, there are difficult decisions involved. What project do you start with? Which employees do you select to lead the charge? And how do you meet, or even surpass, stakeholder, regulatory, and executive expectations?
Starting Off: Six Use Cases
According to EY, CFOs can start to modernise their finance departments with a little help from AI. Here are six of the top finance AI applications:
- Collect customer data and predicting prices
- Assess true asset value
- Forecast unpaid debt
- Track embezzlement and fraud
- Detect money laundering
- Automate repetitive tasks
The bottom line: if you’re a CFOs, you’re in a unique position to champion AI. You oversee production costs, customer data, and financial performance, all of which can benefit from automated intelligence. What’s more, with multiple platforms and integrated solutions on the market, you don’t have to assemble AI systems from scratch. “AI is not a traditional investment by any means”, Christensen said. “There are a lot of unknowns; there are a lot of risks...but also incredible potential”.