As CFOs navigate AI adoption, the challenge isn’t just leveraging its potential—it’s ensuring control. Michael D. Watkins, leadership expert and IMD professor, explores how finance leaders can balance AI’s rewards with its risks through strategic governance.
As CFOs increasingly make crucial decisions about AI investments and implementation strategies, a pivotal question arises: can businesses effectively control the AI systems they implement?
The answer has significant implications not only for financial performance but also for corporate governance, risk management, and strategic decision-making.
As businesses accelerate AI adoption, finance leaders find themselves at the crossroads of innovation and responsibility.
CFOs must balance AI’s undeniable efficiency gains and competitive advantages against emerging risks related to algorithm bias, data privacy, regulatory compliance, and reputational damage.
This balancing act represents perhaps the most significant governance challenge of the digital era.
The fundamental issue with AI is that, without careful oversight, it lacks inherent ethical awareness. AI systems operate through algorithms and predefined objectives, which can lead to unintended consequences when deployed at scale. For finance leaders, these consequences extend beyond technical glitches to include:
What makes this challenge particularly acute is that many AI systems function as “black boxes” – their decision-making processes are not easily interpretable, even by those who design them.
This opacity leads to governance challenges that are unlike those in traditional technology implementations, where cause-and-effect relationships are more transparent.
For CFOs, this presents both a technical and strategic challenge. The financial implications of AI governance failures can be significant – ranging from regulatory penalties to impacts on market capitalization when AI systems fail publicly.
Financial leaders must now figure out how to establish control mechanisms for technologies that inherently resist straightforward oversight.
While the risks of uncontrolled AI are significant, the strategic argument for prioritizing AI governance extends well beyond risk mitigation. Controllable AI offers competitive advantages that directly impact financial performance:
Trust as a competitive advantage: In an era marked by growing privacy concerns and skepticism about data, businesses that showcase responsible AI governance can cultivate stronger customer trust. This trust leads to higher customer retention, enhanced pricing power, and lower customer acquisition costs.
Regulatory readiness: As governments around the globe create AI regulatory frameworks, businesses with established AI governance practices will experience lower compliance costs and fewer disruptions. The EU’s AI Act and similar emerging regulations will benefit organizations that have proactively tackled AI ethics.
Operational stability: AI systems that include adequate human oversight and explainability features foster more predictable operational environments. This predictability diminishes the volatility that can disrupt financial forecasting and strategic planning.
A global insurance company whose AI governance I have studied illustrates this approach in action. By implementing a comprehensive data governance strategy and establishing trustworthy AI principles, they have created a competitive edge in their market.
Their structured AI learning framework educates all stakeholders involved in AI implementation, ensuring that ethical considerations reach beyond the technical team to the entire organization.
Finance leaders play a crucial role in establishing effective AI governance. Drawing from organizations that have successfully implemented controllable AI systems, CFOs should consider the following framework:
Effective AI governance requires cross-functional leadership, with finance serving as a critical voice. CFOs should ensure that AI governance committees include financial representation focused on quantifying risks and evaluating the long-term financial implications of AI applications. These committees should have sufficient authority to influence AI deployment decisions and set boundaries for acceptable use cases.
Traditional risk assessment frameworks often fall short when applied to AI systems. Finance leaders should champion the development of specialized risk frameworks that address the unique characteristics of AI, including:
CFOs should establish clear standards for AI transparency within their organizations. These standards should specify when and how AI systems must be able to explain their decision-making processes, particularly for high-consequence financial decisions.
Explainability isn’t merely a technical consideration – it’s a fundamental governance requirement that enables proper oversight.
While automation promises efficiency, finance leaders must identify areas where human judgment remains essential. Creating “human in the loop” protocols for critical AI applications ensures that algorithmic recommendations can be reviewed before implementation.
This approach is particularly important for financial decisions with significant human impact, such as credit approvals, resource allocation, or workforce planning.
Controlling AI isn’t just a technical challenge – it’s an organizational one. CFOs should advocate for investments in AI education at all levels, ensuring that business leaders understand both AI’s capabilities and its limitations.
This literacy creates an organizational immune system that can identify problematic AI applications before they create financial or ethical problems.
As AI continues to transform business operations, the role of financial leadership must evolve. CFOs will increasingly need to serve as strategic partners in technology governance, bringing financial discipline and risk management expertise to AI implementations.
Those finance leaders who master the governance of AI will position their organizations for sustainable competitive advantage. They’ll enable innovation while preventing the reputational damage and regulatory penalties that come from uncontrolled AI deployment.
Most importantly, they’ll ensure that AI serves broader business objectives rather than creating unintended consequences that undermine long-term value.
The question isn’t whether businesses will adopt AI – that trend is irreversible. The critical question is whether businesses can control the AI they adopt.
For CFOs, developing governance frameworks that enable this control represents both a challenge and an opportunity to demonstrate strategic leadership in the digital era.
Ensuring that AI remains aligned with business objectives and ethical standards isn’t a one-time initiative but an ongoing commitment. Finance leaders must approach AI governance with the same rigor they bring to financial controls and risk management.
With the right governance approach, AI can deliver on its promise – advancing both business performance and stakeholder interests in a sustainable way.
Michael D Watkins is a professor of leadership at the IMD Business School, co-founder of Genesis Advisers, and a bestselling business author of books including The Six Disciplines of Strategic Thinking and The First 90 Days.