The CFO’s search for AI value – Technology News

According to EY’s 2025 C-suite GenAI Survey, while one-third of surveyed companies had allocated budgets for AI initiatives, only 8% were able to fully measure and allocate AI-related costs. Given its transformative potential and organisation-wide impact, AI has become a regular topic in boardroom discussions. Boards are increasingly looking to CFOs for clarity on whether AI investments can move beyond promise and deliver measurable business value.

One reason this is difficult is that both the costs and benefits of AI are often spread across the organisation. AI-related spending may be distributed across IT budgets, consulting fees, software subscriptions and employee costs across multiple departments. At the same time, the returns may be hidden within operational improvements and may not immediately show up in revenue or profit figures.

Invisible Return

Many of AI’s benefits are indirect. These can include faster customer service, better inventory management, improved collections, reduced manual effort and higher product or service quality. Such improvements can lead to meaningful productivity gains, even if they are not immediately visible in financial statements.

At the same time, organisations must recognise that AI is not a substitute for efficient processes. Deploying AI on top of outdated or inefficient workflows may not create significant value. In many cases, business processes need to be redesigned before AI can deliver its full potential.

Measuring revenue impact can also be challenging. In some cases, the contribution of AI may be easier to identify in digital and online channels, where customer interactions and sales can be tracked more precisely than in traditional channels.

Another challenge is that AI investments are not concentrated in a single area. Generative AI and agentic AI can be used by different functions for different purposes. As a result, expectations around returns and methods of measurement must be tailored to the specific use case.

Within the finance function itself, GenAI can automate repetitive tasks, improve forecasting accuracy, enhance cash-flow visibility and strengthen working capital management. The value generated in such cases may be reflected in greater efficiency and better decision-making rather than direct revenue growth.

The way forward is to design AI investment proposals with value realisation in mind from the outset. Organisations must define clear objectives and establish mechanisms to measure outcomes. CFOs must also account for data privacy requirements, cybersecurity risks and governance obligations. At the same time, they need to protect and maximise the value of existing investments in enterprise systems such as ERP and sales platforms by exploring ways to integrate them with AI tools. Ultimately, the return on investment from AI depends on several factors, including the application, level of adoption and business outcomes achieved.

Balanced Scorecard

Most organisations recognise that AI has the potential to create competitive advantage through smarter and faster decision-making. Therefore, CFOs should view AI not as a single investment but as a portfolio of investments, each with its own objectives and performance measures.

An effective AI ROI dashboard should track a combination of metrics covering costs, adoption levels, business outcomes, quality improvements, risk management and overall value realisation. Such an approach can help CFOs connect AI initiatives to measurable outcomes such as improved working capital, stronger compliance, avoidance of penalties and higher revenue per employee.

By adopting a structured framework for measuring AI investments, CFOs can provide boards with clearer estimates of returns and enable more informed decisions about future transformation initiatives.

The writer is chairperson, GTT Foundation.

Disclaimer: The views expressed are the author’s own and do not reflect the official policy or position of Financial Express.