Generative AI (Gen AI) is a powerful new technology with the potential to revolutionize many industries, including finance. However, CFOs are grappling with the high cost of implementing Gen AI while still recognizing its potential benefits. The WSJ explores the challenges and opportunities CFOs face as they navigate the world of generative AI.
Key Points from the Article
Innovation is expensive – Gen AI can be expensive, requiring investment in infrastructure, personnel, and partnerships. Companies can either buy pre-built models or build their own from scratch, but both options come with a hefty price tag.
- Finding the Value Beyond ROI – Since calculating a traditional ROI can be difficult, CFOs are looking at other metrics to measure success, such as increased employee satisfaction and productivity, and even higher revenue generation.
- Success Stories – Some companies are already seeing success with Gen AI. Motorola Solutions uses it to summarize contracts and assist with coding, while Intuit leverages AI for customer service and marketing, potentially leading to higher service fees.
- Taking it Slow and Steady – Not all companies are rushing to adopt Gen AI. Cisco Systems, for example, sees potential but wants a clearer understanding of the costs and benefits before diving in.
- The Future of Finance – Companies like Autodesk are exploring how generative AI can streamline internal finance functions, potentially leading to long-term cost savings.
- The Bottom Line – While Gen AI holds immense promise for the financial industry, careful planning and a focus on measurable value are essential to maximize its return on investment. CFOs who can navigate these challenges will be well-positioned to leverage generative AI and gain a competitive edge.
Generative AI promises big, but finance chiefs are carefully weighing the potential gains against the hefty price tag.
Companies across industries are experimenting with generative AI, a powerful technology that can create new content or complete tasks. While the potential benefits are vast, from boosting worker productivity to improving customer service, figuring out the true return on investment (ROI) is a challenge for CFOs.
The High Cost of Innovation
Generative AI can come with a multi-million dollar price tag. Companies can purchase access to pre-built models or build their own from scratch, but both options require significant investment in infrastructure, personnel, and partnerships with software providers.
A recent KPMG survey highlights this spending trend: nearly half of large U.S. companies plan to invest at least $100 million in generative AI within the next year.
Finding the Value
To justify these costs, CFOs are looking beyond traditional ROI metrics. They’re tracking factors like increased employee satisfaction, improved productivity, and even higher revenue generation.
Some companies are finding success with specific applications. Motorola Solutions, for example, is using generative AI to summarize complex contracts and assist software developers with coding tasks. They track the time saved with these tools to measure the value they bring.
Intuit: A Case Study in ROI
Intuit exemplifies a strategic approach to generative AI. They leverage a combination of purchased models and in-house development using open-source models. This allows them to control costs while still reaping the benefits of the technology.
One example is their use of AI to answer customer questions and generate invoice reminders. Additionally, they’re testing AI-powered marketing tools to see if they can deliver a higher return on investment for their customers. If successful, this could translate to higher service fees for Intuit.
Taking it Slow and Steady
Not all companies are rushing to embrace generative AI in every department. Cisco Systems, for instance, sees potential applications in finance but is waiting to fully understand both the costs and benefits before diving in.
The Learning Curve of AI
CFOs acknowledge the difficulty of precisely calculating ROI upfront. However, they also recognize the potential for AI tools to improve with use. As these technologies become more sophisticated, their value proposition is likely to grow.
The Future of Finance
Companies like Autodesk are exploring how generative AI can streamline internal finance functions, such as forecasting and reporting. While the initial investment in AI for finance might be small, it could lead to long-term cost savings through process automation and reduced hiring needs.
This article explores the challenges and opportunities CFOs face as they navigate the world of generative AI. While the technology holds immense promise, careful planning and a focus on measurable value are crucial for maximizing its return.