Defining And Measuring Return On Investment For Ai Pwc

Bonisiwe Shabane

-Dec 27, 2025, 6:35 PM

defining and measuring return on investment for ai pwc

Executive leadership hub - What’s important to the C-suite? Global AI Lead; US Innovation Lead, Emerging Technology Group, Boston, PwC US Artificial intelligence has a problem: a lackluster return on investment (ROI) that affects many companies that deploy the technology. And while our most recent AI survey found that businesses are beginning to reap AI benefits, the reality is they’re not often seeing a financial return — or worse, not even covering their investments. Compounding the challenge is the fact that many organizations struggle to define ROI for AI in the first place. Most people probably think they know what AI is and does, but it’s a term that encompasses many technologies, processes and functions, so it’s difficult to pin down.

It’s definitely not a one-size-fits all field. That can make it challenging to determine a return on investment. In its simplest form, ROI is a financial ratio of an investment’s gain or loss relative to its cost. In other words, when you invest in AI, the benefits of your investment should outweigh the costs. Since the generative AI boom erupted in late 2022, organizations have raced to implement AI initiatives that enhance their business objectives. Leaders have been on the hunt for scalable AI strategies that streamline operations, inform data-driven decision-making, reduce costs and turbocharge product development.

But though the hype surrounding AI implementation continues to surge, many organizations are finding that the return on investment (ROI) of their AI solutions is falling short. A 2023 report by the IBM Institute for Business Value found that enterprise-wise AI initiatives achieved an ROI of just 5.9%. Meanwhile, those same AI projects incurred a 10% capital investment1. So why are most businesses struggling to profit from AI-driven solutions? And how can they achieve a better ROI in 2025? It turns out that having AI isn’t nearly enough.

Some business leaders jumped on the AI bandwagon in a FOMO-driven, short-term impulse move to stay ahead of their competitors. Others envisioned enterprise AI as the business strategy hammer for every nail. Both groups forgot the importance of nuance and planning. “People said, ‘Step one: we’re going to use LLMs (large language models). Step two: What should we use them for?’” remarked Marina Danilevsky, Senior Research Scientist, Language Technologies at IBM. Her comment is a warning to companies potentially falling into the same shortsightedness trap with AI agents in 2025.

Achieving positive ROI on an AI transformation requires the inverse approach. Fortunately, there’s a sunrise on the horizon for businesses and artificial intelligence. It’s not only possible, but likely, to achieve measurable ROI gains when implementing AI systems correctly—when organizations let strong data quality and AI strategy take the lead. Artificial Intelligence (AI) is no longer a futuristic luxury – it’s a competitive necessity. Businesses worldwide are leveraging AI to optimize operations, enhance customer experiences, and drive revenue growth. But with significant investment comes an important question: Is AI a good investment and delivering measurable returns?

Understanding AI Return on Investment (AI ROI) is essential for companies looking to justify their AI spending, refine their strategies, and maximize their technological advantage. In this article, we will break down what AI ROI is, why it matters, and how businesses can effectively measure and enhance their ROI with AI to achieve long-term success. As you explore how to measure and maximize the return on your AI investments, it’s important to see how strategic implementation drives real business outcomes. For organizations ready to turn innovation into measurable value, discover how AI-driven software development can help you achieve sustainable growth and competitive advantage. AI ROI is the measurement of the financial and operational benefits an organization gains from investing in artificial intelligence (AI) solutions compared to the costs incurred. This metric helps businesses assess whether AI implementation delivers real value, such as cost savings, revenue growth, increased efficiency, or improved customer experience.

A PwC survey of investors reveals expectations for productivity and financial gains, but also workforce investment When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Investors are making it clear what they want from generative AI: solid financial and productivity returns, but no job cuts. That's according to a survey of AI investors by PwC, which found three-quarters of respondents believed generative AI would be beneficial for the companies they've backed. And six-in-ten investors polled said they expect not only revenue growth but also increased profitability, suggesting a close eye on the costs of AI.

A recent study by Gartner suggested that 80% of the CFOs will be increasing their spend on AI in the next two years. There is no debate on the potential of such an investment to bring significant value from transforming business operations to redesigning customer experiences. However, when the question comes to quantify this ‘significant value’, business leaders struggle to find an answer. A PwC Pulse survey revealed as high as 88% of business leaders struggle to measure the return on their digital investment. This is a huge problem. If we cannot measure the return, the ability to prioritize the investment behind the right AI project becomes a question mark.

Similarly, monitoring and thus governing the investment becomes a challenge. An AI deployment is not linear — unlike a conventional system implementation with clear go/no-go decision — AI continues to evolve over time. Once the first-cut model is put into use, it generates more data, more data means better algorithm (in most cases), better algorithm means more usage, and the cycle continues. With that the potential value it can generate, and the cost it incurs also increases. To address this dilemma, CFOs and business leaders cannot just rely on conventional measures like NPV, IRRs, and Payback periods, nor doing it once at the start of the project approval time will suffice. This requires a balanced approach towards defining key metrices of success and monitoring those throughout the AI product Lifecyle.

Is your organization investing in artificial intelligence (AI) but not seeing the expected payoff? You are not alone. According to CDO Magazine, generative AI tools have become the most widely implemented AI applications in the workplace, with expectations of productivity gains and transformative customer experiences. Yet, the report highlights a significant issue: 49% of organizations struggle to estimate and demonstrate the value of their AI projects. This issue is considered more important than other challenges, such as talent shortages, technical issues, data problems, and overall trust in AI. This difficulty in showing AI's value is a potential roadblock to broader adoption and success.

If AI is the future, why are organizations struggling to identify, measure, and report its value? The dilemma is straightforward: while recognizing AI’s potential is easy, the absence of a method to measure its impact makes it feel like a risky investment. The key to success involves developing a return on investment (ROI) framework that is customized to align with your organization’s AI strategy and associated goals, with anticipated benefits identified. Measuring ROI is necessary to justify the costs of deploying an AI strategy, including technology, talent, and infrastructure, to achieve specific organizational goals. ROI helps verify if AI initiatives are generating value beyond their costs. Unlike traditional investments that target immediate financial returns, AI may deliver long-term results that build up gradually.

For example, AI in customer service can enhance user experience by personalizing interactions and improving response times, which may not immediately increase profits but can improve customer satisfaction and loyalty over time. The ROI from AI investments can achieve tangible and intangible benefits. Tangible benefits (also known as hard returns) are measurable in financial terms and include increased revenue, reduced costs, and productivity savings. Intangible benefits (also known as soft returns), while harder to quantify, are important as they contribute indirectly to customer relationships, organizational culture, and business growth. Examples of intangible benefits include improved employee engagement, enhanced customer experience, and increased innovation. AI initiatives can deliver a range of benefits, from tangible to intangible, short-term and long-term gains, as well as, strategic and tactical impacts, which influences the ROI model.

Therefore, to fully capture the value and impact of AI initiatives, they should be evaluated across 3 distinct ROI categories to fully capture their value and impact, as illustrated in figure 1.

Defining And Measuring Return On Investment For Ai Pwc

People Also Search

Executive Leadership Hub - What’s Important To The C-suite? Global

It’s Definitely Not A One-size-fits All Field. That Can Make

But Though The Hype Surrounding AI Implementation Continues To Surge,

Some Business Leaders Jumped On The AI Bandwagon In A

Achieving Positive ROI On An AI Transformation Requires The Inverse