McKinsey’s 2026 State of AI survey reports that 32% of organizations have decided against buying at least one software product or feature because they built it in-house with agentic coding tools. The survey, published on 25 August 2026, polled 1,719 respondents across 97 countries between 4 May and 8 June 2026.
The report was authored by Dan Tinkoff, Lieven Van der Veken, Michael Chui, and Tara Balakrishnan of McKinsey’s QuantumBlack practice. The build-versus-buy question is new to the survey this year, so the 32% figure is a baseline, not a trend. The same survey finds that 37% of organizations attribute any EBIT impact to AI — a figure unchanged from 2025 — while 80% of respondents say AI improved their individual productivity.
What McKinsey’s 2026 State of AI Survey Found on Build vs. Buy
Nearly one in three organizations now build software internally instead of purchasing it, according to McKinsey’s ninth annual State of AI report. The report states: “Nearly a third of respondents (32 percent) report that their organizations have decided against buying one or more software products or features because they could be built internally with agentic coding tools.”
The shift is concentrated among the best-performing AI adopters. Nearly half of McKinsey’s AI “high performers” have stopped buying at least one software feature, compared with 31% of all other organizations. McKinsey defines a high performer as an organization that attributes 5% or more of EBIT to AI and describes the impact as significant — a group that makes up 6% of respondents.
McKinsey frames the finding as a cost-discipline story as much as a capability story: “Organizations are discovering that AI capabilities not only give them more options for building rather than buying enterprise software but also increasingly require them to develop new disciplines for managing AI’s costs.” 20% of organizations report constraining AI use because of operating costs, including token costs.
Large Companies Scale AI Agents at Twice the Rate of Small Ones
40% of large organizations with revenue above $1 billion are scaling AI agents in 2026, up from 27% in 2025, while smaller organizations stayed flat at 22%. Across the full sample, about 20% of organizations are scaling AI agents, and a similar share is scaling software coding agents.
AI chatbots remain the most widely deployed AI tool: 47% of respondents report scaling chatbots across the enterprise. High performers are 2.7 times more likely than other organizations to be scaling agentic AI. For buyers weighing which AI agents for business tasks to deploy, the McKinsey data shows agent adoption is now a large-company norm and a small-company exception.
Why 80% Productivity Gains Produce Only 37% EBIT Impact
The gap between individual productivity and enterprise profit exists because most organizations add AI to existing workflows rather than redesign the workflows, according to McKinsey. 80% of respondents say AI improved their personal productivity and 50% say it helps them make better decisions, yet the share reporting EBIT impact stayed at 37% for a second year.
High performers behave differently on this one variable: 75% of high performers fundamentally redesign workflows around AI, compared with 25% of other organizations. McKinsey concludes: “the organizations that translate individual productivity gains into lasting enterprise-level financial performance are likely to be those that transform their businesses, not just adopt AI tools.”
Workforce expectations also outran reality. 39% of respondents expect AI-related workforce declines in the coming year, but only 14% saw a decline in 2025–26, against 32% who had predicted one a year earlier. 60% expect their organization to increase AI investment in the next year.
What the McKinsey Data Means for Software Buyers
The McKinsey survey turns tool selection into a two-sided decision: which software to buy, and which software no longer needs buying. A business evaluating the best AI tools for business in 2026 is also evaluating whether an agentic coding tool, such as Claude Code, GitHub Copilot, or Cursor, can replace a SaaS line item outright. McKinsey does not name affected vendors, and the survey measures decisions not to buy new products, not cancellations of existing subscriptions.
Frequently Asked Questions
What is McKinsey’s State of AI 2026 survey?
McKinsey’s State of AI 2026 is the firm’s ninth annual global survey on AI adoption, published August 25, 2026. It draws on 1,719 respondents in 97 countries, surveyed between May 4 and June 8, 2026, and is authored by Dan Tinkoff, Lieven Van der Veken, Michael Chui, and Tara Balakrishnan.
How many companies have stopped buying software because of AI?
32% of surveyed organizations decided against buying at least one software product or feature because they could build it with agentic coding tools. Among McKinsey’s AI high performers, the share is nearly half; among all other organizations, 31%.
Does the McKinsey report say AI is causing layoffs?
No. 14% of organizations reported an AI-related workforce decline in 2025–26, well below the 32% that had predicted one. 39% expect a decline in the coming year.
What separates AI high performers from everyone else?
High performers — 6% of respondents — attribute at least 5% of EBIT to AI, redesign workflows around AI (75% vs. 25%), and are 2.7 times more likely to be scaling agentic AI than other organizations.
For Context
WithO2 has tracked the enterprise shift toward AI agents and the cost pressure that comes with it through 2026:
- Temporal’s 2026 report found 8 in 10 engineers now use AI agents daily — the developer-side adoption that makes in-house software builds feasible.
- Salesforce data showed enterprise AI agent deployments tripled in a year, matching McKinsey’s large-company scaling curve.
- KPMG and OpenAI predicted enterprises would stop clicking through software — McKinsey’s 32% is the first survey measurement of that prediction.
- Databricks warned that AI coding bills are exploding, the operating-cost constraint McKinsey says 20% of organizations now face.
