Unlocking the ROI potential of generative AI: A CFO’s guide to measuring business value
Generative AI is the latest buzzword in the tech world, with CFOs and financial executives eagerly jumping on the bandwagon in hopes of reaping massive benefits from the technology. The potential for generative AI to streamline operations, improve customer service, enhance forecasting, quicken software development, and boost marketing and sales is undeniable. However, the path to realizing these benefits is not without its challenges.
One of the biggest hurdles faced by CFOs is the difficulty in measuring the ultimate business payoff of generative AI. With the rapid adoption of the technology happening primarily from the bottom-up, from consumers, rather than top-down from businesses, CFOs must act quickly to demonstrate ROI or risk wasteful spending. This pressure is further exacerbated by shareholder expectations and rising customer demands for AI-enabled efficiencies and service.
The fear of missing out on the potential benefits of generative AI has led to a frenzy of investment, with 37% of U.S. companies planning to invest at least $100 million in the technology. This surge in investment is expected to drive spending on AI software to $298 billion by 2027, with a significant portion focused on generative AI. The high stakes involved in the race to adopt AI have also raised concerns about hype and potential fraud, prompting the SEC to issue warnings about the risks associated with AI investments.
Despite the promise of generative AI, some financial executives and AI experts caution that the road to realizing its benefits may be fraught with challenges. The illusory nature of some short-term payoff from AI, coupled with the difficulty in measuring the value of data, poses significant obstacles for CFOs looking to gauge the ROI of generative AI across their operations. Additionally, the evolving landscape of AI technology means that cost estimates may fall short or exceed expectations, making it challenging for CFOs to accurately predict the investment required.
In the midst of this generative AI paradox, CFOs must navigate the murky waters of AI investment with caution and diligence. By understanding the potential risks and challenges associated with generative AI, financial executives can better position themselves to maximize the benefits of the technology while mitigating potential pitfalls. In part two of this series, CFO Dive will explore strategies for financial executives to limit costs and maximize the payoff from generative AI, even in the face of uncertainty about the potential gains.