WHY did sales rise or fall in a certain region? Where can we cut costs without affecting productivity? How do our profits vary across different customer segments?
Imagine having a command prompt that can instantly provide answers to these questions that typically take days to resolve. This scenario is not a distant dream but a practical use case of generative artificial intelligence (GenAI) that accelerates decision-making and drives tangible value for businesses. This may explain why many chief financial officers (CFOs) are evaluating how they might integrate this breakthrough technology into their workflows.
GenAI and finance may seem a natural fit, with the former powered by data and the latter drawing upon massive amounts of it. But in the adoption of emerging technologies, CFOs are confronted with a strategic conundrum: should they pursue early adopter or fast follower strategies?
Findings from Deloitte's latest Southeast Asia (SEA) CFO Agenda report revealed that while there is no one right answer to this conundrum, SEA CFOs adopt a highly astute and value-focused lens in formulating their approaches and strategies. On one hand, a CFO at a Thailand-based financial technology group intends to charge ahead of the pack, developing a data-obsessed culture and planning to embed AI into budgeting, monitoring and decision-making processes to drive both revenue generation and greater cost efficiencies. On the other, a CFO at a Singapore-based health care service provider prefers to adopt a fast-follower approach by gradually incorporating proven use cases into their operations and investing in pilot programs that provide clear benefits, cost savings and return on investment.
The question is: Where to start? How can CFOs determine where to deploy GenAI in the finance function?
Harnessing GenAI's capabilities is hardly simple or inexpensive. Unleashing this technology at full throttle can pose various risks, only some of which — cybersecurity, data privacy and regulatory compliance — are knowable in advance. It would be wise to start small: leverage pilot programs and implement AI in a targeted set of use cases aimed at delivering specific benefits. In Deloitte's 3Q 2023 CFO Signals survey, 52 percent of respondents ranked "reduce costs" among the top three benefits they hoped to achieve by using GenAI; 45 percent prioritized increasing margins, efficiencies and/or productivity.
For finance, this may mean using GenAI to streamline financial planning and analysis, and improve forecast accuracy. GenAI may also be used to analyze data from various sources to predict market trends and risks, generating insights that can help inform decisions.
First, however, CFOs may be wise to take some proactive steps in preparation for deployment:
– Gather intelligence on GenAI. Finance leaders do not have to be experts. They need to know enough to decide what outcomes they hope to achieve through the technology and understand how GenAI processes data and makes decisions.
– Assess data readiness. From our conversations with SEA CFOs, it is clear that most of them are in exploratory phases of AI and data. SEA CFOs frequently lamented the lack of clean and consistent data as the biggest impediment to their organization's uptake of advanced AI technologies. GenAI's voracious appetite for data can only be met once standardized data is consistent, accurate and complete. It also needs to be centralized to safeguard the consistency of the data.
– Collaborate with other functional leaders. GenAI represents a new way of accelerating decision-making. Business leaders must not look at it as an IT issue to resolve. CFOs and other functional leaders must work together in shaping strategy and driving AI adoption.
– Assess your company's technology skills. Prior to implementation of GenAI, ensure access to the necessary skills required — this may include familiarity with data analytics and engineering, machine learning algorithms and certain programming languages. In the first quarter 2024 CFO Signals survey, 93 percent of the 116 respondents said that bringing talent with GenAI skills into finance is important over the next two years. In the near term, AI education and fluency will be important to foster adoption and overcome initial resistance to change. In the longer term, upskilling or reskilling and redesigning work processes will likely be essential for capturing the full value of GenAI.
– Evaluate current infrastructure. Outside of acquiring and developing talent, organizations must develop a secure data infrastructure and have proper governance structures in place to embrace Gen AI and support the business transformation.
There's no question that GenAI can potentially unlock new growth opportunities and accelerate innovation. In the short term, most businesses view GenAI as a tool to improve productivity and reduce costs. In the long term, the big winners will use this technology to differentiate themselves and enable broad enterprise transformation to create value in new ways. But before companies can unlock GenAI's full potential, they will also have to address issues related to talent, governance and risk.
Rather than rushing into it, the key may be to prioritize understanding of GenAI capabilities and plan for gradual, small-scale deployment in finance and the enterprise.
The author is the assurance leader at Deloitte Philippines, a member of the Deloitte Asia Pacific Network. For comments or questions, email phcm@deloitte.com.
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