AI Talk: Finance of 2030 – The impact of AI on the CFO’s function

Views on news 

Something is shifting in the CFO suite. The function that has been approving AI budgets for everyone else while remaining sceptical of the technology’s value closer to home is beginning to move. A recent Bain & Company survey of senior finance executives shows 56% are increasing enterprise-wide AI investment by more than 15% this year. Over the next two years, 83% of CFOs plan AI budget increases above 15%, with 42% expecting increases above 30%.

 

When CFOs describe their biggest AI win, speed and cycle-time reduction leads at 48%, ahead of headcount or cost savings at 34%. A finance function that compresses the cycle from market signal to management decision from weeks to days is better positioned to help the business move faster than its competitors. Workflow debt is still a serious concern – if a business implements AI on top of its legacy processes, it won’t reap the full benefit of the investment.  

 

Becoming a proactive partner while remaining a challanger 

Over 50 per cent of routine accounting and reporting tasks are expected to get automated by 2030. Current AI maturity levels vary widely. Although today we don’t see fully mature organisations yet, the pieces of the enterprise AI puzzle are gradually falling into place. AI will impact all functions within finance. Success requires strategic thinking and building solid processes around it, which can be run end-to-end by AI agents at the end of the transformation journey.  

 

Businesses must check their performance against industry benchmarks and work out how their deployments will give them an edge over competitors. AI will radically shrink the pyramid in the organisation, especially at the lower echelons, where at present a high number of people work with data carrying out transactional tasks, passing on insights to those who make decisions at the top.   

 

Trust will be key to AI adoption in finance – the most trusted corporate function. AI requires a corporate culture based on experimentation and continuous improvement. Experimentation, however, must always happen with data security in mind.

 

Different aspects – goals, processes and technology –  must always be aligned. Tools, such as Hackett’s AI centre of excellence can help identify AI opportunities, customise solutions to existing tech stack and processes and  learn about business transformation best practices. At the start, smaller successful AI projects can be leveraged to gain support for larger ones to be deployed across the organisation – a minimum viable product approach will take you further than striving for perfection.  

 

AI will have an impact on financial roles too. Compliance, for example, is expected to shift from execution to framing and oversight. A number of areas have already undergone large scale automation, where humans’ role got limited to oversight.

 

Meanwhile, new capabilities will be required too to manage AI delivery life cycles from ideation to no-code development to AI governance. Accordingly, many organisations have already set up a financial transformation officer role for that. Another new role, the AI Centre of Excellence (CoE) Manager will be either a role inside the finance function or will constitute the finance spoke of AI CoE. 

 

The panel’s advice 

• Define the 2030 operating model now to be able to think strategically, rather than making like for like skills replacements.  
• What we expect in four years’ time is a finance operating model defined by value, delivered by agents and governed by humans.   
• While CFOs increasingly support AI investment across the organisation, AI use within their own function is still in its infancy.  
• Running a structured ideation process is key to aligning goals, technology and processes.  
• Pick a project where you can demonstrate AI’s value and take it to scale incrementally – one geography or one business line at a time. Start small but think strategically as well.