# Becoming ‘AI native’ might not be as profitable as you think. Unless your company does it right > Source: > Published: 2026-09-21 13:01:00+00:00 [AI](https://www.fastcompany.com/section/artificial-intelligence) is changing everything, from how employees work to what they are working on.  But a new *Fast Company* report in collaboration with [Tata Consultancy Services](https://www.tcs.com/) (TCS) revealed that only about 7% of companies are actually generating measurable value from artificial intelligence. According to leaders surveyed for the report, most companies are either scaling AI with only moderate returns (23%), piloting AI initiatives that haven’t scaled (23%), in the early stages of experimenting with AI (21%), or not even using it yet (18%). Another 8% have paused or abandoned AI initiatives after starting them. Among 380 C-level executives across a wide range of industries, a clear return on investment (ROI) remains a top challenge at 39% of their companies as they attempt to become AI-native. “There is a lot of excitement around AI, and there should be,” Amit Bajaj, president of TCS, told *Fast Company*. “But the more important question now is practical: Who is creating measurable value? What separates the companies that can scale AI value from the ones that don’t? And what are leaders doing to build the contextual awareness and trust required for the technology to actually deliver on its potential?” In addition to the survey, the report includes insights from executives at top companies across industries, including Mastercard, E.l.f. Beauty, Autodesk, and others. AI deployment doesn’t happen overnight. Scaling AI to a native capacity requires an intentional business-minded approach. According to the survey, a defined mission around AI drives company success. Only 13% of surveyed companies have a “mission-critical” system—meaning AI is integral to a company’s process and success—and 18% of companies that attempted AI deployment rolled back because of performance risk or adoption failure. Companies using AI simply as a tool are falling behind. Injecting AI on top of traditional processes can make tasks easier, but it isn’t transformative. Leading companies—the ones gaining significant value from AI—say they are reengineering their entire workflow. The survey showed that 70% of leading companies use multiple mission-critical AI systems across production, allowing them to generate significant business value by comparison. Successfully AI-native companies also have a structured AI and human collaboration model. While the majority of companies implement a combination of AI and human [productivity](https://www.fastcompany.com/section/productivity), 26% of companies have no structured human and AI collaboration model.  Meanwhile, every surveyed AI leader has a structured model. About one-third have deployed autonomous models. More than half of leading AI-native companies give a majority or all employees access to AI, compared with 39% for companies overall. But at more than half of all companies, access to AI is still limited, and 28% of overall companies reported insufficient AI skills within their organization was the biggest barrier to AI deployment. Many employees are scared of AI because of its potential to disrupt workflow and job security. But executives at surveyed companies want to ease employees’ transition to AI. For instance, every [Mastercard](https://www.fastcompany.com/section/mastercard) employee gets a [Copilot](https://www.fastcompany.com/section/copilot) subscription, and the financial services company is implementing hands-on training to make workers AI fluent. [HP](https://www.fastcompany.com/section/hp) holds regular meetings where employees can ask whatever they want about AI.  The software giant [Autodesk](https://www.fastcompany.com/section/autodesk) started a yearlong AI Academy, committing $350 million over the next three years to provide technology, training, and certifications to students pursuing AI-powered jobs worldwide. AI relies on the data it’s fed. Bad data means poorly functioning AI models. For 30% of leaders and 36% of companies overall, data quality, governance, or infrastructure limitation is their largest barrier to AI adoption. “Automated governance”—software and code enforcing organization policies automatically—could improve data readiness and make AI innovation more responsible, the report reveals. When data users understand what’s allowable, they don’t have to waste time asking questions; the entire innovation process moves faster. Leading companies focus more on growth than others. Fully 82% measure revenue growth from AI-enabled products or services, compared with 51% of companies overall. Only 7% of leaders find ROI to be a challenge in AI deployment. But to these companies, success can mean a number of things. For instance, AI tools have allowed Mastercard to improve its prevention of fraudulent transactions by 300%, and [E.l.f. Beauty](https://www.fastcompany.com/section/e-l-f-beauty) to ensure adequate inventory when products go viral.  Canva, the design software company, defines its AI-powered success simply: It’s being able to do the work of a bigger organization with the same staff. While these results might not always be financially quantifiable, they take each business to the next level—and write the playbook for the businesses that will boom in an increasingly AI-native market. “The most interesting examples are the ones tied to business outcomes: new revenue, better margins, stronger execution, and more resilient operations,” Bajaj of TCS told *Fast Company*. “Used well, AI can help companies become more adaptive and better prepared for what comes next.”