Uber Questions the ROI of AI Spending as Costs Continue to Climb
One of the most significant investment focuses of tech firms globally has been on AI. Organizations are investing billions of dollars in AI tools, infrastructure, and talent, hoping that these technologies will boost productivity, drive innovation, and generate new streams of income. But as the prices climb, some firms are starting to ask themselves a tough question: Does the return on investment justify it?
Uber seems to be one of the first big tech companies to publicly raise that concern. The ride-hailing and delivery company has reportedly already used up its annual AI budget within four months of 2026 and is questioning if its increasing spending on AI is yielding tangible results for the business.
In an interview with Rapid Response, Andrew Macdonald, president and CEO of Uber, noted that one of the problems many companies face after investing in AI to the hilt is that they are seeing usage metrics skyrocket, but the impact on the business isn’t necessarily measurable.
The Growing Cost of AI Adoption
In the last two years, coding assistants, automated tools, and large language models have proved their utility in software development, becoming an integral part of the process. Numerous companies have been urging their staff to adopt these instruments to speed up coding, to boost productivity and productivity and to streamline internal operations.
But, unlike conventional software subscriptions, a lot of sophisticated AI services are charged by tokens. The amount of data is processed, the number of requests or content created is used to determine the amount of the charge will be levied. With all the use by thousands of employees, the costs can quickly rise.
After just four months, Uber used up its set AI budget and reports that this was largely because of the high consumption of AI coding tools like Claude Code. This has led company leaders to consider whether the increased use of AI is providing them with the same amount of value.
Although developers are increasingly turning to AI tools, there’s been a lack of a direct connection between increased token use and the creation of improved products for the customer, Macdonald said.
Assessment of Real Business Impacts
A major hurdle in assessing the value of AI investments is the difficulty of separating activity from outcomes.
Metrics like a number of prompts submitted, number of tokens used, number of lines of code generated, or number of hours saved can be easily tracked by the company. But these are not always a sign of the experience that customers are having, or the efficiency of the business.
In the interview, Macdonald said that he does not see a clear correlation with the increased use of AI and the development of new, genuinely useful consumer features, yet.
He said the evidence is mainly indirect, though more software is being shipped and software development processes are going faster.
It poses an increasing dilemma for technology leaders. As costs for AI rise, without clear metrics of success it becomes harder to get shareholders and stakeholders to buy in on the costs.
AI Spending vs. Hiring Employees
The question takes on greater importance if AI investments are compared head-to-head with investments in the workforce.
Uber CEO Dara Khosrowshahi said earlier this month that the company is “trimming staff ahead of rising costs for artificial intelligence efforts. It’s a global phenomenon in the tech sector as businesses incorporate AI into their operations as a replacement for some jobs.
But Macdonald said it would be important to look closely at this comparison.
With the rising cost of AI, businesses will be forced to determine whether the millions of dollars they spend on AI services is worth hiring more employees, engineers, or product teams.
Without evidence of a direct impact of AI investments on business results, the case for replacing or downsizing human resources becomes much more challenging.
The Challenge is a problem that confronts the whole industry.
Uber’s worries aren’t alone. In the tech industry, AI has become a major investment priority for businesses but it is difficult to measure its ROI.
There have been great examples of productivity increases, but the challenge is to see those productivity increases actually result in quantifiable business benefits. While developers can code faster, customer service can be faster, and analysts can finish tasks more efficiently, it may be hard to determine if these benefits lead to higher revenues or better customer satisfaction.
This uncertainty grows as AI providers continue to make improvements to their pricing models. While token-based billing provides flexibility and scalability, it can also lead to unexpected costs for businesses with a large user base.
This has led to a growing demand from businesses for concrete proof of the return on investment from AI investments, rather than just a cost.
How AI is changing business.The future of AI in enterprise.
However, Uber is not giving up on artificial intelligence. It, like many tech firms, sees AI as a fundamental element of its future plans.
The connection between the use of AI and business results could be more evident with time as AI tools evolve and become more adept at being integrated into workflows, Macdonald said.
The company’s experience offers a broader glimpse into how organizations globally are struggling with the challenge of adopting AI – not simply experimenting or innovating, but also successfully integrating it into ongoing business operations. It’s more than ever a matter of being held accountable, getting things done and tangible results.
With businesses now beyond the hype surrounding generative AI and seeking to evaluate its use, management will increasingly be under the microscope to justify the expenditure of every dollar on AI technologies.
A Turning Point for AI Investment
Uber’s comments could mark the start of a new era in the AI revolution. Companies that have rapidly adopted and been spending tons of dollars on years of potential are now getting back to performance.
The next generation of AI success stories won’t necessarily be from the largest spenders: They’ll be from the businesses that can clearly articulate how AI will add value to their products, enhance their customer experiences, and provide real business value.
The real question for Uber and others now is whether AI is not only a good piece of technology, but a good investment.
