ROI of artificial intelligence: why should the CFO lead AI?

In recent years, the corporate market has plunged headlong into the so-called Age of Artificial Intelligence. Companies across all sectors are racing to integrate generative AI, automate processes, and create personalized virtual agents to optimize their operations. However, as projects progress, a nagging question begins to echo in boardrooms: where is the financial return on all this?

Many companies discover, the hard way, that there is a huge gap between running a technological pilot project and actually consolidating the ROI of Artificial Intelligence.

If your organization is struggling to extract real value from technology, the solution may lie in a radical leadership change. And the answer isn't in the IT department, but rather in the finance department.

The paradox of leadership in AI projects

Whose responsibility is it to make Artificial Intelligence deliver financial results? Intuitively, most companies point to technical roles. A recent study published by the Harvard Business Review reveals exactly this market trend:

• 38% of companies leave the responsibility for extracting value from AI to the Chief Data Officer (CDO).
• 35% delegate this task to executives from other business areas.
• Only 2% of organizations entrust this mission to the CFO (Chief Financial Officer).

Herein lies the great paradox: although the CFO is the least remembered leader to head up technology, he holds the best indicator of success. According to the same research, when the CFO leads the AI ​​strategy, 76% of organizations report significant achievements and robust returns.

But why does this happen? What is the "superpower" that financial leadership brings to the table of technological innovation?

Governance and metrics: the financial DNA applied to technology

The disparity in these figures does not arise from the position itself, but from the nature of financial governance. Finance professionals are rigorously trained to assess risks, validate post-implementation scenarios, and demand clarity in the economic model for every penny invested.

Looking at the current landscape, the biggest challenges in adopting Artificial Intelligence are not technical. The technology is already mature: modern tools integrate data from hundreds of systems and manage complex infrastructures minute by minute. The real bottleneck is corporate governance.

Without an analytical perspective from the financial sector, Artificial Intelligence risks becoming a money drain, characterized by:

• Endless pilot projects: technologies implemented simply for the "charm" of innovation, without a clear business problem to solve.
• Fluctuating and uncontrolled costs (FinOps): poorly sized cloud infrastructures that generate unpleasant surprises on the bill at the end of the month.
• Lack of success metrics: absence of quantitative and qualitative indicators capable of proving whether automation brought real efficiency or just additional costs.

How to combine finance and technology to guarantee the ROI of AI

For Artificial Intelligence to cease being an expense and become an engine of prosperity, leadership needs to adopt a framework focused on three fundamental pillars:

1. Establish predictable pricing models

Investing in AI cannot be a gamble. It is essential to seek solutions that offer cost predictability, such as transparent pricing in local currency, without variable fees or hidden licenses. This allows for secure and scalable budget planning.

2. Implement a FinOps culture

The cloud is the foundation that supports advanced AI models (LLMs). Therefore, continuous monitoring of computing resources is essential. The use of intelligent auto-scalinghelps to tailor the infrastructure to actual demand, eliminating wasted memory and CPU.

3. Focus on ready-made solutions that solve real problems

Instead of getting bogged down in the complex and costly world of developing fundamental models from scratch, the smartest strategy is to leverage existing infrastructure. Using platforms that integrate data tools (lakehouse), pre-built connectors, and conversational platforms accelerates time-to-market and drastically reduces development costs.

Conclusion: Responsible AI is profitable AI

The future of business belongs to organizations that can balance innovation and return on investment. Artificial Intelligence has the undeniable potential to revolutionize work, automate operational tasks, and free up human capital for strategic activities.

However, for this mechanism to function at maximum efficiency, the technology needs human oversight, governance, and, above all, the financial rigor that only the CFO can provide.

When designing your company's next innovation committee, make sure the CFO is not just the person who signs the checks, but one of the project's strategic leaders.

Do you want to ensure the technological and financial efficiency of your business?

Successful digital transformation begins with a secure, scalable cloud infrastructure with fully predictable costs.

If you want to modernize your company's systems, eliminate data silos, and prepare your operations for the age of Artificial Intelligence with complete budgetary control, talk to one of our strategic experts and discover how to sustainably boost your results.

By Rodrigo Tremante, CFO of Skyone

Written by Skyone