SynopsisFor the past two years, enterprises have encouraged employees to adopt AI tools at scale. Now, some of the biggest corporate users of AI are introducing limits, usage controls, and cost-management frameworks, signalling a shift from widespread experimentation to measurable business value.ET OnlineFor much of the AI boom, the goal was simple: get employees using AI.Today, that strategy is evolving.Some of the world's largest companies are beginning to place greater emphasis on how AI is used, how much it costs, and whether it delivers measurable returns. The shift suggests that enterprise AI adoption is entering a new phase, one focused less on access and more on accountability.According to a Bloomberg report, Walmart has recently introduced usage limits for Code Puppy, its internal AI coding assistant. The move comes after strong employee adoption reportedly drove costs significantly higher. The company has implemented a token-based system to manage usage and encourage employees to deploy AI tools where they create the most value. Employees continue to have access to other AI platforms, including Claude and ChatGPT.Walmart is not alone. Uber reportedly rolled out Claude Code to approximately 5,000 engineers earlier this year and is said to have exhausted its annual AI budget within months. Microsoft has also asked thousands of engineers to transition from Claude Code to an internally developed alternative by the end of June, a decision widely linked to managing rising AI usage costs. Meanwhile, GitHub has adopted token-based pricing for Copilot, directly tying costs to consumption.Taken together, these developments point to a broader trend across the enterprise technology landscape. The conversation is no longer centred on whether organisations should adopt AI. Instead, businesses are increasingly focused on identifying which use cases generate meaningful outcomes and how AI investments can be scaled sustainably.This marks an important shift in how enterprises view artificial intelligence. Early adoption was driven by experimentation and rapid deployment. The next phase appears to be defined by governance, cost optimisation, and measurable return on investment.AI remains a strategic priority for businesses, but unlimited access is gradually giving way to more deliberate deployment. As adoption continues to mature, the organisations that gain the greatest advantage may not be those using the most AI, but those using it most effectively.Disclaimer Statement: This content is authored by a 3rd party. The views expressed here are that of the respective authors/ entities and do not represent the views of Economic Times (ET). ET does not guarantee, vouch for or endorse any of its contents nor is responsible for them in any manner whatsoever. Please take all steps necessary to ascertain that any information and content provided is correct, updated, and verified. ET hereby disclaims any and all warranties, express or implied, relating to the report and any content therein.Read More News onRead More News on