“Game-changer” is overused in business circles, but it’s the term that best encapsulates AI’s potential impact on the CFO role and the finance function.
Both traditional AI and generative AI (GenAI) have the potential to transform productivity within finance teams by automating time-intensive tasks, enhancing management reporting, and performing advanced data analysis. AI can enable teams to turn both structured and unstructured data into strategic insights.
To fully harness these technologies, companies must establish a robust data infrastructure – which requires significant investment. CFOs must decide whether the potential returns justify the necessary expenditure.
While the productivity benefits of AI are clear, the terrain that companies must cross to reach them can be treacherous. The ethical and societal implications, as well as AI’s potential influence on capital markets, are still uncertain. In M&A transactions, for example, advanced AI could theoretically provide a buyer with an “ideal” valuation of an acquisition target. Yet if both buyer and seller are equipped with similar AI tools and the same “ideal” valuation, the implications for capital markets – historically shaped by information asymmetry – could be profound.
Drawing on insights from IMD’s World Competitiveness Center, including the World Digital Competitiveness Ranking and World Talent Ranking, CFOs should consider two key questions in their approach to AI:
GenAI and other rapidly evolving technologies are creating complex ethical, legal, and social challenges around data privacy, cybersecurity, inequality, and governance. While searching for the advantages that these tools offer, governments and business leaders must keep in mind the need to foster inclusiveness, trust, and resilience.
Currently, AI regulation lacks globally applicable standards. The EU is taking a top-down approach with the EU AI Act, which has been designed to distinguish between “limited-risk” and “high-risk” AI systems and prescribe an appropriate level of transparency for each. The framework is intended to work in alignment with the General Data Protection Regulation (GDPR), which asserts that individuals, rather than governments or corporations, have the right to decide how their data is used.
In contrast, the US has taken more tentative steps towards regulation with the Algorithmic Accountability Act of 2022, which mandates that companies monitor the privacy and transparency impacts of their AI systems. However, the federal government has, to date, failed to enact this regulation. Another prominent recent attempt at implementing new legislation, California’s proposed AI safety bill, was subject to a veto by Governor Gavin Newsom over concerns that overly strict regulation could hinder innovation and drive technology firms out of the state.
While proponents of the US approach often justify their support with the soundbite that “Europe regulates, the US innovates,” this overlooks the fact that effective regulation provides clarity and stability. Demonstrating the effectiveness of a regulatory approach, the 2023 IMD World Digital Competitiveness Ranking has five EU nations in the top ten. This progress is partly a result of the implementation of the EU Data Governance Act (DGA), which establishes protocols for the use of data in the public sector, including trade secrets, personal information, and intellectual property.
Without a clear regulatory framework, fear of contravening legal requirements may deter companies from harnessing data analytics and securing a first-mover advantage from the insights they provide.
CFOs should avoid adopting a safer but potentially complacent “wait-and-see” stance on AI regulation and best practices. The reputational and financial risks of inaction are too high. As a first step, companies should obtain a clear, centralized view of all AI tools in use across their organizations. Establishing governance structures with defined accountability for AI management is essential. Additionally, leaders should introduce employee training programs to ensure responsible development and use of AI tools across the enterprise.
“Research from the World Competitiveness Center emphasizes that creating a culture of lifelong learning requires collaboration above the corporate level, involving regulation, fiscal incentives, and educational reform.”
AI can enhance human creativity, problem-solving, and communication. However, as AI systems become capable of performing data analysis and even making decisions, the workforce may become nervous, feeling that the technology is threatening their job security.
While governments and regulators will need to manage the general social implications of automation-driven job reductions, business leaders have a crucial role to play in preparing their individual workforces.
Like technology, the required skills are themselves evolving. While qualities such as creativity and emotional intelligence remain valuable, the need for AI-specific skills is urgent. Employees must rapidly gain an understanding of how AI works, its limitations, and the tools available within their organizations. A 2024 survey found that more than half (52%) of Generation Z workers and 45% of millennials surveyed were worried that their employers could replace them with workers with more advanced AI skills within the next year (this does drop to 33% for Generation X).
Research from the World Competitiveness Center emphasizes that creating a culture of lifelong learning requires collaboration above the corporate level, involving regulation, fiscal incentives, and educational reform, all with sufficient urgency to keep pace with technological developments.
For CFOs, the increasing mobility of talent is another key factor. The 2023 IMD World Talent Ranking illustrates that, in an increasingly globalized talent landscape, companies can hire skilled professionals from anywhere, reducing reliance on high local educational standards and courses that produce graduates with relevant skills and expertise. The rise of remote working from home – or, in the increasingly popular “digital nomad” lifestyle, from wherever – has further fueled this trend.
At a national level, however, developing domestic AI skills remains critical to fostering innovation, enhancing productivity, and supporting industries such as AI hardware manufacturing. For tasks such as system control, monitoring, and compliance, the talent pool is global, but a skilled local workforce can bring significant competitive advantages.
Many finance professionals will already interact with GenAI tools and have developed an awareness of how these technologies could shape their roles and, sooner or later, take over certain tasks.
CFOs should focus training on those areas of the finance function where AI can make the greatest impact in optimizing the use of resources and investment.
A human-centered approach is equally important. Many finance professionals will already interact with GenAI tools and have developed an awareness of how these technologies could shape their roles and, sooner or later, take over certain tasks. Reskilling programs should acknowledge employees’ questions and concerns about the future, adopting an empathetic approach to deepen worker confidence and foster adaptability.
As they seek to navigate the developing regulatory landscape, finance leaders must be ever conscious of the ethical, regulatory, and human dimensions of AI. They can build workforce resilience by fostering a culture of continuous learning, investing in the required skills, and ensuring employees are prepared for an AI-enabled future. This requires robust governance and proactive regulatory engagement.
The journey towards AI-driven value creation is serpentine but, with a strategic and empathetic approach, CFOs can lead their organizations confidently into the future, excited by the opportunities to innovate with the required safeguards in place.
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