The question haunting enterprise leaders for years has finally gotten a clear answer: does AI investment actually pay off? According to a comprehensive survey of over 3,200 companies across financial services, retail, healthcare, telecommunications, and manufacturing, the verdict is decisive. Eighty-eight percent of respondents said AI has increased annual revenue in some or all parts of their business, with nearly a third reporting gains exceeding 10 percent. This marks a significant shift in how companies view artificial intelligence. After years of cautious pilots and assessment phases, enterprises are moving into active deployment at scale. Sixty-four percent of survey respondents said their organizations are actively using AI in operations, compared to just 28 percent still in the assessment phase and 8 percent not using AI at all. The momentum is unmistakable, and the financial results are backing up the investment. Are Larger Companies Really Seeing Better AI Results? The data reveals a clear pattern: company size matters significantly when it comes to AI success. More than three-quarters of respondents from large companies with over 1,000 employees report active AI usage, with just 2 percent saying they don't use AI at all. These larger organizations have deployed more use cases and report greater return on investment, largely because they have more capital to invest in AI infrastructure, data scientists, and specialized experts who can drive projects from pilot to production on highly specific and impactful use cases. Geographic differences also emerge in the data. North America leads in AI adoption with 70 percent actively using the technology, followed by the EMEA region (Europe, Middle East, Africa) at 65 percent and the APAC region (Asia-Pacific) at 63 percent. These regional variations reflect differences in access to AI talent, regulatory environments, and technology infrastructure investment. How Are Companies Turning AI Into Measurable Business Impact? - Revenue Growth: Thirty percent of respondents reported annual revenue increases greater than 10 percent from AI, while 33 percent saw increases between 5 and 10 percent, and 25 percent experienced gains under 5 percent. - Cost Reduction: Eighty-seven percent of companies said AI helped reduce annual costs, with retail and consumer packaged goods companies leading the way at 37 percent reporting cost decreases exceeding 10 percent. - Productivity Gains: More than half of respondents, 53 percent, identified improved employee productivity as one of the biggest impacts AI had on business operations, from accelerating financial market analysis to boosting efficiency on factory floors. Real-world examples illustrate how these gains materialize. Nasdaq, one of the world's premier stock exchanges, has built an AI platform to optimize internal operations and enhance external products. "At Nasdaq, we are a technology platform company, and AI has the ability for us to unite all the different businesses and products," explained Michael O'Rourke, senior vice president and head of AI and emerging technology at Nasdaq. "AI will help bring together data from all our businesses and technologies, and help us build better products and services". In manufacturing, PepsiCo is working with Siemens and NVIDIA to convert selected U.S. manufacturing and warehouse facilities into high-fidelity 3D digital twins that simulate end-to-end plant operations and supply chains. These AI-powered simulations have already delivered a 20 percent increase in throughput on initial deployments, driven faster design cycles with nearly 100 percent design validation, and produced 10 to 15 percent reductions in capital expenditure. The company can now identify up to 90 percent of potential issues before any physical modifications occur. Retail is experiencing similar transformations. Fortune 100 retailer Lowe's has built AI-powered, physically accurate digital twins of over 1,750 stores to speed operations. The company also used AI to streamline asset discovery and enable 3D model generation, transforming 2D product images into precise, high-quality 3D models within minutes at a cost of less than one dollar per model. What Are Companies' Top Priorities for AI Investment? When asked about their primary goals, companies identified three clear priorities. Creating operational efficiencies ranks first at 34 percent, followed by improving employee productivity at 33 percent, and opening new business opportunities and revenue streams at 23 percent. These goals reflect a maturation in how enterprises think about AI, moving beyond general experimentation toward targeted applications that address specific business challenges. The productivity improvements have cascading effects throughout organizations. Forty-two percent of overall respondents said AI created operational efficiencies, and 34 percent said the technology helped open up new business and revenue opportunities. In telecommunications specifically, 99 percent of respondents said AI helped improve employee productivity, with a quarter saying the technology provided a major or significant improvement. What's Driving the Next Wave of AI Adoption? Beyond traditional AI applications, companies are beginning to experiment with AI agents, which are advanced AI systems designed to autonomously reason, plan, and execute complex tasks based on high-level goals. Forty-four percent of companies were either deploying or assessing agents as of late 2025, with enterprises seeing those experiments become full-fledged deployments in early 2026. Telecommunications had the highest rate of adoption of agentic AI at 48 percent, followed by retail and consumer packaged goods at 47 percent. These AI agents are already making an impact in specialized domains. Mona by Clinomic, a medical onsite assistant that helps doctors and nurses manage patients in intensive-care units, consolidates, analyzes, and visualizes patient data in real time. The system has produced a 68 percent reduction in documentation errors, enhancing the accuracy of patient records. The broader takeaway from this year's data is clear: AI has moved from experimental technology to essential business infrastructure. Companies that have invested in AI infrastructure, talent, and strategic deployment are seeing measurable returns across revenue, costs, and productivity. As more organizations move from assessment to active deployment, and as AI agents mature from experimentation to production use, the competitive advantage of early adopters will likely continue to widen.
