GenAI and the Finance Function; how can Finance Leaders adapt?

AI is no longer a sci-fi buzzword or gimmick; it has now reached the workplace and has started disrupting many different industries. CFOs need to weigh up the opportunities and risks associated with AI adoption in their Finance function. The recent Deloitte 2024 CFO Sentiment report sheds light on Australia’s current business landscape through the eyes of its financial leaders. The report highlight’s that 82% of CFOs believe in the transformational potential of GenAI on Finance, however they are lagging in terms of adoption with only 12% having piloted or implemented the technology.

It would appear their current priorities are elsewhere, with over 60% of CFOs focused cost control initiatives. While CFOs acknowledge the potential of generative AI in improving efficiency, the uncertainty posed by data and cyber risks and confusion on where or how to start has led to delay any significant investment. 

There is also a legitimate question on whether to wait for the major platform providers to embed this functionality into their Finance tools versus building in-house. To overcome these hurdles there are some questions CFOs need to consider.

What is the value equation of GenAI in Finance?

Generative AI provides the finance function with the ability to accelerate, automate, and scale tasks that were once exclusively performed by humans. This enhances operational efficiency and allows human talent to focus on strategic aspects of the CFO role across four key areas:

1. Strategist: Generative AI-powered predictive models can uplift financial planning and analysis (FP&A) through advanced scenario and impact analysis.
2. Operator: Automation of transactional processes, such as reconciliations, journal entries, and consolidation activities, can level up finance operations.
3. Catalyst: The efficiency and effectiveness of financial and management reporting can be improved through the reliable production of draft reports, enabling more time to be spent on narrative and interpretation.
4. Steward: Continuous monitoring and financial anomaly detection facilitated by generative AI enhances financial controls.

Organisations are starting to see the potential benefits that generative AI can bring to their Finance functions as they prepare for a new wave of innovations in the year ahead. The Finance AI^TM Dossier published by the Deloitte AI Institute is a curated selection of high-impact generative AI use cases for the Finance function.

What are the challenges with GenAI adoption according to CFOs?

While generative AI tools have significant potential, they still don’t “think” like humans. They require human input and guidelines, a well-structured data landscape, and a compatible technology environment to determine what to do and what is incorrect. Many finance leaders will find the key challenges they are facing are:

1. Data quality, access and security: With 43% of CFOs citing data management, cyber security, and analytics capability as a significant risk for businesses in 2024. Our Tech Trends 2024 report delves into the cyber security risks AI poses and advises CFOs to not wait for new regulations to make your first move. Start improving AI fluency, set up governance frameworks and stay up to date on global trends. 
2. Finance technology: 33% of CFO’s cite implementation challenges as a key reason for not investing in GenAI; Any technology transformation initiatives comes with it’s complexities and an array of challenges to overcome; however GenAI applications really on many working pieces for success. Leveraging this new technology on-top of poor data or incompatible finance technology infrastructure may introduces significant issues particularly within risk, governance, and data management.
3. Talent : GenAI is evolving rapidly, finding the right talent with the functional and technical understanding needed to design, build and maintain this environment is a key constraint, with 44% of CFOs citing this as a reason to delay investment. With limited expertise workforce trust is also a concern, the Deloitte AI Institute’s The State of Generative AI (2024 Q2 report) cites worker trust as a key area to bridge to enable large-scale adoption, employees are at this stage aware of the technologies faults in the form of “hallucinations” and may not be convinced that GenAI will bring net positives to their role at this stage.