The buzz around Artificial Intelligence promises a revolution in corporate profits, but a sobering new assessment from Apollo Global Management suggests reality is more complicated. What does the gap between AI spending and actual returns mean for business?
A Reality Check on AI Payoffs
A recent analysis by Torsten Slok, chief economist at investment firm Apollo Global Management, has sent a ripple of realism through the tech world. The report claims that despite massive investment, AI has delivered 'zero financial payoff' to most of corporate America outside the major tech giants. The analysis separates the S&P 500 into two groups: the 'Magnificent Seven' tech stocks (like Nvidia and Microsoft) and the remaining 493 companies. For the tech giants, metrics like revenue per worker and profit margins have soared. But for the vast majority of other businesses, these key performance indicators have remained almost entirely flat. This suggests that while the companies building and selling AI are profiting, the companies buying and using it are not yet seeing a similar boost to their bottom line. The report notes that many mainstream companies are beginning to see AI spending as a cost centre rather than a clear driver of growth.
The Challenge of Measuring Real Impact
The Apollo assessment aligns with broader industry findings that show a disconnect between AI adoption and proven profitability. A recent McKinsey report, 'The State of AI in 2026', found that while nearly 90% of organisations use AI in some capacity, only 37% could attribute any positive impact to their earnings—a figure that has not changed from the previous year. The core problem lies in translating individual productivity gains into measurable financial results. An employee might use an AI tool to write a report in half the time, but unless those saved hours are repurposed to generate more revenue or cut specific costs, the benefit never appears on a profit and loss statement. Furthermore, the costs of AI, from data management and specialised talent to the high price of computing power (often called 'inference'), are concrete and rising, while the returns remain scattered and difficult to quantify. Many businesses simply lack the frameworks to measure the true return on investment (ROI), especially when AI's benefits are qualitative, such as improved decision-making or customer satisfaction.
Where Are the Early Wins?
Despite the lack of aggregate profit growth, AI is delivering value in specific, targeted areas. The key difference between 'AI high performers' and the rest is not how much they spend, but how they use the technology. Companies seeing the best results are not just layering AI onto existing processes; they are fundamentally redesigning their workflows around it. Instead of focusing only on cost-cutting, they use AI to pursue growth and innovation. Early successes are often found in automating highly specific, repetitive tasks rather than attempting to replace complex human judgment. For example, AI is being used effectively to generate thousands of e-commerce product descriptions, automate aspects of software development, and support financial analysis. Success stories often involve starting with a single, well-defined problem, tracking a clear metric, and then scaling what works, rather than attempting a broad, undefined enterprise-wide rollout.
The View from India: A Story of Scaled Ambition
The Indian market for AI is booming, projected to exceed $7 billion in 2026. Unlike in some other markets, leaders in India appear to be aggressively pushing for scaled implementation rather than remaining in a pilot phase. One Deloitte report found that India leads globally in using AI for strategic decision-making. This rapid adoption is partly enabled by strong digital public infrastructure, like the Account Aggregator framework, which facilitates the consent-based data flow needed to train and deploy effective AI models. However, Indian firms face the same fundamental challenge: turning adoption into profit. While a recent survey showed 78% of Indian businesses use AI for marketing, another found that 84% of fintech respondents had yet to see measurable financial results from their investments. This echoes the global trend—enthusiasm and adoption are high, but the path to clear, auditable ROI remains a work in progress, with many projects at risk of being cancelled due to unclear value.
