Guide To Measuring Ai Roi By Brado Greene

Bonisiwe Shabane

-Dec 27, 2025, 6:40 PM

guide to measuring ai roi by brado greene

Why measuring AI ROI is different and more complex than traditional technology investments A clear, step-by-step framework for defining business objectives and establishing baselines How to calculate the full cost of AI, including hidden and ongoing expenses Methods for quantifying both tangible and intangible benefits in bu… AI’s impact has rapidly expanded across various industries and regions. It has helped businesses unlock new opportunities, supported cities in enhancing their services and empowered leaders to achieve greater efficiency, innovation and growth.

Despite the AI market’s explosive growth — projections estimate it could reach USD 757.58 billion by 2025 — many leaders continue to face a key challenge: proving a clear return on investment (ROI) from... Measuring AI success is essential for ensuring alignment with business goals, driving long-term value, empowering data-driven decision-making and optimizing performance and resource allocation. Without a clear framework for assessing ROI, wasted resources and missed opportunities could overshadow AI’s potential. Understanding a project’s ROI is essential for businesses and investors. However, when it comes to AI projects, the definition and approach for measuring ROI require a more nuanced perspective that captures both tangible and intangible benefits. Traditional ROI typically focuses on easily measurable financial results and metrics, such as boosted sales, higher profit margins or improved Net Promoter Scores (NPS).

These metrics are clear-cut and directly tied to revenue or cost savings, making them relatively simple to track and interpret. For instance, an increase in sales or customer retention can directly showcase the success of a specific initiative. After two decades of helping organizations implement technology solutions across manufacturing and healthcare sectors, I have learned that the ability to measure and demonstrate return on investment (ROI) is often the determining factor between... The challenge with AI ROI measurement extends beyond traditional technology investments. AI systems often deliver value through improved decision-making, enhanced customer experiences, and risk mitigation—benefits that can be difficult to quantify using conventional financial metrics. However, with a systematic approach and appropriate measurement frameworks, organizations can accurately assess and communicate the business value of their AI investments.

This guide presents a comprehensive methodology for measuring AI ROI, developed through my experience working with organizations across diverse industries and refined through practical application in complex operational environments. Ready to calculate your AI ROI? Use our free AI ROI Calculator to get instant projections based on your specific business metrics and industry benchmarks. Traditional ROI calculations rely on straightforward comparisons between investment costs and measurable returns. AI investments, however, often generate value through multiple channels and over extended timeframes, making direct attribution challenging. Actionable insights on AI adoption, ROI trends, and strategy—helping leaders find signal in the AI noise.

We are a partner in confidently building, scaling, and evolving software products backed by 11+ years of experience. In April 2024, Arun Chandrasekaran, Distinguished Vice President Analyst at Gartner, whose research focuses on artificial intelligence, wrote in a Gartner blog about a prediction: By 2027, more than 50% of the GenAI models... Additionally, in 2023, businesses began spending money much more actively, as confirmed by a report from Statista. Based on these facts, he calls for planning to deploy and manage multiple domain-specific GenAI models. However, before doing so, he suggests looking for off-the-shelf, domain-specific models that can be trained or tuned to meet enterprise needs. This sounds like a plan, but I think it's very important to have one's own data.

Reports about the ROI of AI that has been implemented, or predictions of future plans for implementing AI, are crucial before starting to invest in popular solutions or trying new optimization methods with AI. From pilots to profit, understand ROI in AI with proven ROAI frameworks, KPIs, and strategies to measure the true Return on AI. Your company spends half a million dollars on an AI solution. Six months later, senior leaders ask, “Where’s the return on AI?” The technology works. Teams are using it. But when pressed for hard numbers like cost savings, revenue lift, or productivity gains, the answers are vague.

Most enterprises are no longer asking whether they should invest in AI. The real question is far more uncomfortable. Is AI actually delivering measurable business value? Across industries, AI budgets are growing faster than ever, yet boardrooms continue to struggle with one fundamental issue: proving the ROI of AI. While pilots show promise and demos look impressive, translating those efforts into clear financial outcomes remains difficult. This gap between expectation and reality has given rise to a more focused way of thinking about AI investments: ROAI.

According to a 2025 survey of over 3,400 senior leaders of global enterprises, a whopping 88% of those diving deep into agentic AI think autonomous systems that handle tasks with minimal hand-holding are already...

Guide To Measuring Ai Roi By Brado Greene

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