Artificial intelligence, and generative AI in particular, catapulted onto the scene at lightning speed in November 2022. And today, 250 years after the first industrial revolution, experts believe we have entered the next (some say fourth, others fifth) industrial revolution as the latest advancements in automation and artificial intelligence (AI) are transforming industries and societies. This current industrial revolution is set to be one where humans and AI-powered technology will work hand in hand.
In many ways, the effective adoption of AI, specifically gen AI, both in finance and across an entire organization, rests with each company’s chief financial officer. This has placed the CFO into the driver’s seat and at the forefront of company strategy. It is now within the CFO’s power to decide where to allocate resources and how to effectively integrate AI into their company’s daily activities. By striking the right balance between risks and growth opportunities, CFOs can navigate and manage genAI transformation, maximize returns from AI investment, and create value for organizations both large and small.
The transformation pressure for CFO’s is firmly in place. And navigating and managing this transformation, both digital transformation and AI/GenAI, are the top two trends at the top of minds for CFOs and finance leaders, according to a December 2023 poll of the AICPA-CIMA Future of Finance Leadership Advisory Group. In addition to the focus on digital transformation and AI/gen AI, it is important to focus on the third-noted top issue of ‘Need for upskilling and reskilling.” The need for new skills like storytelling, data analytics, collaboration and strategic thinking are essential to elevate and accelerate finance and accounting teams to keep pace through these transformations.
I recently hosted a gen AI panel at the North America Finance Executives Summit, and along with two members of our AICPA-CIMA Future of Finance Leadership Advisory Group — Rachael Crump, chief accounting officer of Insight Enterprises, and Claire Bramely, CFO of Teradata Corp. — we addressed common misconceptions and barriers about AI, and shared AI implementation guidelines for CFOs and finance leaders to follow to ensure and enhance team efficiency, productivity, and accuracy.
“While broadly being led by finance, it’s important for gen AI implementation to be a collaborative process. Ideas from [all over the organization] are important and keep the conversation on ways to implement open,” noted Insight’s Crump.
Key guidelines for CFOs to follow when implementing gen AI:
- Start small and start now: There’s a strong consensus among finance leaders on the need to initiate gen AI projects on a small scale. This approach allows for manageable experimentation and learning, reducing risk while gaining valuable insights. The repeated advice is to “just start” and “start somewhere,” emphasizing the urgency of engaging with gen AI without being overwhelmed by its scope.
- Prioritize data security and intellectual property protection: Security and protection of intellectual property are critical considerations. Ensuring that information is safeguarded while exploring gen AI capabilities is paramount to maintaining trust and compliance.
- Learn from others: The importance of learning from the experiences of others before diving in too deeply cannot be overlooked. This can help avoid common pitfalls and leverage best practices for more effective implementation.
- Build a roadmap and plan strategically: Developing a clear plan and roadmap for gen AI integration is essential. This includes organizing data, aligning initiatives across the organization, and focusing on areas where gen AI can deliver immediate value.
- Evolutionary, not revolutionary: Adopting an evolutionary approach to gen AI is advised. Move forward with incremental changes rather than attempting an overnight transformation. This method supports sustainable progress and allows for adjustments based on lessons learned.
- Finance as a key leader in gen AI implementation: The CFO and finance team should play a leading role in the adoption and governance of gen AI, leveraging its unique position to drive process improvements and analytical enhancements.
- Addressing skepticism and building support: Winning hearts and minds across the organization is crucial for successful gen AI initiatives. This involves addressing skepticism, demonstrating value, and ensuring there is a common understanding of gen AI’s benefits and objectives.
- Navigating through disillusionment: Prepare for questions about managing expectations and navigating through potential disillusionment with gen AI. The key is to maintain open dialogue, adjust strategies as needed, and keep focused on long-term goals.
- Emphasizing data quality and trusted AI: The quality of data and the trustworthiness of AI systems are foundational. Emphasizing trusted, safe AI practices and ensuring high-quality data inputs are essential for reliable and effective outcomes.
- Experimentation and value focus: Encouraging experimentation and focusing on use cases that offer tangible value are effective and recommended strategies. Starting with pilot projects can help demonstrate gen AI’s potential and build momentum for broader adoption.
- Engagement and involvement: There is a call to “get more involved” and to “just try it” that reflects a proactive stance towards gen AI, suggesting that hands-on engagement is key to understanding and leveraging this technology effectively.
When navigating gen AI-driven transformation within your organization, Teradata’s Bramley emphasized that, “It’s important to remember that the role of gen AI is a journey. Be evolutionary rather than revolutionary. This start-small, functional focus approach will ensure you gain value from your implementation.”
The inevitability and transformative potential of generative AI in finance is unquestioned and advocating for a strategic, informed, and cautious approach to its adoption is key to success. For the CFOs driving AI strategy and implementation starting small, focusing on security, planning strategically, and building organizational support are essential steps toward harnessing Gen AI’s capabilities while navigating its challenges and opportunities.
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