Larger companies lead AI agent adoption in 2026<\/h2>
In 2026, 40% of respondents at organizations with $1 billion or more in revenue said they were scaling AI agents in one or more functions, compared with 22% at smaller organizations, according to a McKinsey survey<\/a>. Smaller here means under $1 billion in revenue, which includes many midsize companies. <\/p> The large-company share was 27% in 2025, while the smaller group stayed flat. About two in 10 respondents said their organization had reached the scaling phase across the whole organization, a stricter measure than scaling in one function.<\/p> KPMG’s AI Pulse survey<\/a> found 62% of 314 US C-suite and business leaders at organizations with $1 billion or more in revenue building, deploying, or developing AI agents, up from 53% a quarter earlier. And 25% were developing or implementing multi-agent systems, up from 6% in each of the two quarters before.<\/p> In a LangChain survey<\/a> of 1,340 professionals, most of them in technology roles and already working with agents, 57.3% had agents in production, and another 30.4% were developing them with concrete plans to deploy. That’s a lower bar than McKinsey’s scaling phase, and the respondents lean toward early adopters, so the share runs higher. <\/p> Size made a difference here, too: 67% of organizations with 10,000 or more employees had agents in production, compared with 50% of those with fewer than 100 employees, though another 36% of the smaller group were developing them<\/p> Across the surveys, smaller organizations are working on agents almost as often as large ones, but fewer have moved them into production or scaled them.<\/p> Customer service and research are nearly tied as the most common jobs for AI agents: 26.5% of respondents in LangChain’s survey named customer service as their primary use case, and 24.4% named research and data analysis. Between them, the two account for more than half of primary deployments, and another 18% use agents mainly to automate internal workflows.<\/p> Big companies lean toward internal uses. At organizations with 10,000 or more employees, internal productivity tops the use-case list at 26.8%, ahead of customer service at 24.7% and research and data analysis at 22.2%.<\/p> McKinsey ranks agent work differently because it asks a different question: where agents have reached the scaling phase, not each team’s main use case. By that measure, respondents most often scale agents in information technology (IT), knowledge management, and software engineering, while respondents in consumer goods and retail most often use them in marketing and sales.<\/p> Coding agents are already shifting some buying decisions. About 20% of respondents said their organization was scaling software coding agents, rising to 31% at larger enterprises. And 32% of respondents at organizations using AI said they had skipped buying at least one software product or feature because it could be built in-house with agentic coding tools, most often in technology and healthcare. <\/p> The answer depends on what you measure: customer service and research are the most common main jobs for agents, while IT and software engineering are where they’ve scaled furthest.<\/p> Of the US small employer firms that use AI, 83% use it for writing or marketing, well ahead of individual productivity at 61% and planning or analysis at 51%, according to the Federal Reserve Banks report<\/a>. <\/p> Across all surveyed firms, 46% said their business or employees use AI, another 15% planned to start within 12 months, a third had no plans to use it, and 6% were unsure. These figures cover AI in general. None of the surveys here measure AI agent use at small businesses specifically.<\/p> AI users report gains: 71% saw higher productivity and 31% higher sales, while 77% saw no change in labor costs and only 16% saw them fall. Most of these firms are still early, though. About half of AI users are experimenting, 44% have partially built AI into their business processes, and 7% have fully integrated it.<\/p> Firms planning to start cite practical hurdles: 54% can’t find tools that fit their needs, and 37% lack the time to implement AI or train staff. Starting with one workflow you already run narrows the search to a single job, as our small business AI guide<\/a> shows.<\/p> US Census Bureau data shows lower AI use than the Fed survey, and a clear rise since spring. In the Business Trends and Outlook Survey<\/a>, 24.6% of US employer businesses used AI in a business function in the period ending October 18, 2026, up from 19.8% in the period ending May 3.<\/p> The smallest firms are following the same trend. Use at firms with one to four employees rose from 19.0% to 24.3% over the same months.<\/p> Larger firms use AI more. As of October 18, use reached 35.3% at firms with 100 to 249 employees and 43.6% at firms with 250 or more.<\/p> The two surveys aren’t directly comparable. The Fed asks whether a business or its employees use AI at all, based on a late-2025 sample of small firms, while the Census Bureau asks whether a business used AI in any business function in the past two weeks, across employer businesses of all sizes. <\/p> Both point the same way, though: AI use at small firms is growing, but most are still early in adopting it.<\/p> Agents account for 22% of the value companies get from AI in 2026, up from 17% in 2025, according to BCG’s Applied AI Index<\/a>. The index draws on a survey of more than 1,300 senior executives across 20-plus sectors.<\/p> Maturity makes a big difference. 44% of the most AI-mature companies, which BCG calls future-built, already get value from agentic AI, compared with 2% of laggards.<\/p> McKinsey’s survey shows a similar pattern. AI high performers, the roughly 6% of respondents who attribute at least 5% of EBIT (earnings before interest and taxes) to AI and report significant value, were more than three times as likely as others to be scaling agents in most business functions. The survey doesn’t say whether scaling agents drives the results or strong performers simply scale more.<\/p> Measurable value from AI overall is more common. In KPMG’s survey, 58% of leaders at US organizations with $1 billion or more in revenue reported measurable business value from AI initiatives, including but not limited to agents. Productivity gains led at 55%, followed by faster decision-making at 49%, better customer and employee experiences at 38%, and stronger financial performance at 37%.<\/p> Hostinger’s own support desk shows what this looks like in one operation. Hostinger’s AI assistant resolved 91% of roughly 1.5 million support conversations a month<\/a> without human involvement. That support work now runs inside Hostinger Agent<\/a>, which combines support with specialized agents for business tasks.<\/p>![\"Two-panel](\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/2\/2026\/11\/image-6.png\/public\")
<\/a><\/figure><\/div>Customer service and research lead AI agent use cases<\/h2>
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<\/a><\/figure><\/div>Small businesses use AI mostly for writing and marketing<\/h2>
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<\/a><\/figure><\/div>Agents are a growing share of the value businesses get from AI<\/h2>
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