Are finance departments about to become unrecognisable from their pre-AI days? Until now, CFOs have mostly staffed their teams with fellow accountants, often with skills taught them by accountancy bodies around the world such as ACCA.
But the advent of artificial intelligence (AI) and, in particular generative AI, and the systems and solutions they power, could be about to transform the skills requirements for a CFO staffing a leading-edge team.
Ready for revolution
Dickla Gishen, an AI business coach and senior manager with PwC, has been posting regularly on LinkedIn about the change set to strike finance departments and the skillsets accountants may find themselves either acquiring or sitting next to in a fully AI-integrated finance team.
‘Finance departments are going to look very different from what we are used to seeing,’ she tells AB. ‘They’re not used to having data scientists and Python coding experts in their teams.’ And she has a word of warning for CFOs. ‘I’m not one who says, oh, you’ve got five years. You don’t. You’ve got to do it quickly because things are happening very quickly.’
The urgency is being stressed elsewhere too. Deloitte recently published a report highlighting the dilemmas facing CFOs now the technology currently being embraced by finance is changing what humans do – ‘sometimes a lot’. Finance may need storytellers who ‘bring financial information to life’, or technicians who ‘drive big automation projects’; CFOs will have to understand the mix of humans and machines that will be required as well as the roles and job descriptions to go with them.
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‘We are looking to people to do more data-driven decision-making’
‘Like any transformation, workforce modernisation will be disruptive. But the payoff for those who get it right can make it all worthwhile,’ the report says.
What’s hot
When US business magazine Forbes recently reported on the most in-demand skills for finance professionals, it put risk management at number one, fintech second, and finance and data analysis at number four, just behind expertise in regulation and compliance.
The shift towards the automation of many repetitive jobs currently staffed by accountants has been underway for some time. But as Forbes suggests, there are areas where accountants can learn new disciplines. ‘We are looking to people to do more data-driven decision-making,’ says Gishen. ‘They have that analytical brain able to interpret data and draw insights from that data.’
New skills on the block
Ali Al-Sherbaz, a professor and digital skills specialist at the University of Cambridge’s Institute of Continuing Education, teaches AI and fully expects new knowledge and abilities to arrive in finance departments. He says: ‘There will be a new group in the finance department, which is the AI expert or data scientist, and they will work side by side with the experts in finance.’
‘Knowing how to train an LLM to fit your needs is the value here’
Al-Sherbaz runs a course that turns professionals with a couple of years’ experience in data analytics into data scientists within seven months. Data scientists study the application of machine learning and gen AI for analysis. But data scientists would also typically gain knowledge of programming and algorithms and how they power AI.
These skills are also needed to train an large language model (LLM) on the data needed for a finance department to undertake business analysis. Increasingly these LLMs will be highly specific rather than general tools such as ChatGPT. Specialists in training on sectoral, or proprietary, data will be in high demand, Al-Sherbaz says. ‘Knowing how to data-engineer to train an LLM to fit your needs – that is the skills and the value here.’
Cracking coding
The expertise is needed for another reason too. If AI turns out results that fail to pass a sense check, someone has to know how to debug the algorithm or the Python code to get the AI back on course.
Keyvan Vakili, a professor and expert in strategy at London Business School, is already training personnel from big professional services firms. He says new skills, including coding, will bring confidence into finance departments and their CFOs.
‘If you’re a CFO and you ask your junior person, “Can you send me this report?”, and that junior doesn’t know Python, then you don’t have visibility,’ he says.
AI in finance will be like the autopilot in aerospace
Vakili’s additional point is that skills are required to address the ‘edge’ cases – those situations where AI struggles. He draws an analogy with the airline industry. Although autopilots handle most of the flying these days, a number of crashes demonstrated there were situations where the technology simply could not cope. Human pilots were therefore given extra training to ensure they could adapt and handle these difficult to predict events. The same will apply in finance with AI, he says.
‘When you train people,’ Vakili says, ‘you need to train the limitation of the tool so that you don’t ask the wrong question or you can direct the tool in the right direction.’ His emphatic view is that people in finance will not go jobless, and that the tools will likely ‘augment rather than replace people’. Most of the work, he says can be handled by upskilling existing staff.
Skills stocktake
Either way, now is the moment for CFOs to take stock of the skills in their departments and ask what a modern finance team should look like. It may not mean recruitment. Existing staff can be retrained, skills may be available elsewhere in an organisation such as IT or even marketing for storytelling and narrative building (see box).
There must also be a recognition that this won’t be a once-and-for-all change. AI is developing fast, Gishen points out, and the skills requirements are still emerging. ‘It’s about getting your people used to embracing change regularly,’ she says.
Build, borrow, buy
Options to deliver tech-enabled work in the finance function of the future include:
Build: Upskill team members, identifying people critical to future operations and ensuring they get the learning experiences they need to step up.
Borrow: Look for talent in other parts of the business – those with marketing, change management or storytelling skills who are eager to take on new challenges.
Buy: Consider purchasing robots and machine learning tools on the open market, along with full-scale outsourcing or the targeted hiring of employees, contractors and freelancers with in-demand skills.
Source: Deloitte report, The Finance Workforce in a Digital World
