In this digital era, the role of a Chief Financial Officer (CFO) is no longer confined to traditional financial management. With the advent and rise of Artificial Intelligence (AI), CFOs are now tasked with integrating and managing these advanced technologies into their business strategies. Failure to do so could result in a strategic blunder that could potentially have long-term repercussions. Conversely, CFOs who proactively embrace AI, ask tough questions, and formulate coherent frameworks for AI investment will likely ensure their businesses remain competitive in this rapidly changing landscape.
CFOs must now consider a dual approach to AI: implementing AI to enhance the products or services offered by the business, and leveraging AI to transform the way the business operates. Both tracks require adequate investment, governance, and crucially, leadership from finance.
Investing in what customers will pay for
As AI continues to evolve, it is becoming less of a novelty and more of an expectation among consumers. Businesses that fail to incorporate AI-enabled features into their products or services risk losing ground to competitors who have already made the leap. There are also potential financial gains to be had. By involving customers early in the development process, such as in pilot programmes and beta phases, businesses can foster loyalty and justify premium pricing, provided the value delivered is evident.
However, determining the financial viability of AI investments can be challenging. The variable costs associated with AI workloads can be difficult to model, particularly in the initial stages of deployment. Regulatory frameworks governing AI are continually shifting, carrying hefty penalties for non-compliance. The decision whether to build or buy AI capabilities is also constantly changing, due to the rapid advancements and decreasing costs of foundational models. CFOs must navigate these complexities to ensure the business remains profitable and is not overspending on AI development.
Getting the house in order
Internally, the benefits of AI are more readily apparent. Implementing AI in high-volume, low-complexity processes such as approvals, data entry, reconciliation, and routine reporting can yield measurable returns fairly quickly. Moreover, the data governance infrastructure needed to support these internal deployments sets the stage for external productisation and fosters AI fluency across the workforce.
Despite this, obstacles often arise in the form of human resistance to adoption, the use of unsanctioned tools without IT oversight, and an over-reliance on automated recommendations. Finance should treat internal AI adoption as a carefully managed experiment, setting clear metrics from the outset, rigorously measuring outcomes, and using the results to inform the broader AI strategy.
What AI will (and won’t) do for headcount
A common misconception about AI in the enterprise is that it will result in job losses. In reality, human intervention remains crucial for supervising AI systems, validating their outputs, handling exceptions, and providing commercial judgement that automated systems cannot replicate.
AI can also assist in streamlining various operations. For instance, AI-assisted coding tools can shorten development cycles, reduce time spent on boilerplate code, and help teams identify testing gaps earlier. In customer support, AI can handle routine queries at scale, freeing human teams to focus on complex, relationship-defining interactions. In procurement, AI can automate the almost entirely rules-based procure-to-pay cycle. Lastly, in finance, AI tools capable of running continuous variance analysis, flagging deviations in real time, remodelling forecasts, and narrating the results in plain English, have the potential to meaningfully bridge the gap between raw data and genuine commercial insight.
Looking ahead
As we approach 2026, it is clear that it will be a critical moment for enterprise software. Companies that have developed coherent AI strategies and built internal capabilities will be better prepared to navigate the changing landscape. As the year progresses, customer behaviour data, adoption metrics, and risk indicators will provide CFOs with a clearer picture of the market dynamics. Increasing macro-economic pressures, particularly around cost and supply chain, will put functions like procurement under scrutiny, making the case for intelligent automation stronger.
In conclusion, the enduring advantage of a CFO lies in evidence-based decision-making rather than mere enthusiasm. As the market continues to evolve rapidly, the organisations that will genuinely benefit from AI are those whose finance leaders have the rigour to invest deliberately, the patience to build properly, and the clarity to distinguish real innovation from expensive noise.
Brandon Nussey, CFO at JAGGAER
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