Free tools Windows power users keep installed
One-click scans. No signup required.
iTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
Yes—business use of AI and generative AI is expanding across functions. McKinsey’s 2026 global survey found that 88% of respondents said their organizations regularly use AI in at least one function, while Stanford HAI reported that 70% used generative AI in at least one function during 2025. Those figures measure different populations and definitions. Adoption is broadening faster than companies are scaling systems enterprise-wide or reporting material financial impact.
Is generative AI adoption increasing at work?
The answer is yes, but no single percentage captures “adoption.” Surveys distinguish broad AI from generative AI, regular use from experimentation, and use in one function from deployment across an enterprise.
| Measure | Finding | What it means |
|---|---|---|
| Regular AI use in at least one function | 88% in McKinsey’s 2025 survey, up from 78% the year before | General AI use, not generative AI alone |
| Generative AI use in at least one function | 70% of organizations surveyed for Stanford HAI’s 2026 AI Index, covering 2025 | A GenAI-specific, one-function-or-more measure |
| AI scaled across the enterprise | 44% in McKinsey’s 2026 survey, up from 38% in the prior survey | Self-reported enterprise scaling |
| AI used in three or more functions | 56% in McKinsey’s 2026 survey, up from 51% | Broader organizational reach; not a GenAI-only rate |
McKinsey summarizes the trend this way: “Nearly a decade into McKinsey’s survey research on companies’ use of AI, organizations are deepening their use of these technologies.” The wording describes survey responses, not a causal estimate of business performance.
The Tool Desk
Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Sources: McKinsey, The State of AI: Global Survey 2026; McKinsey, The State of AI in 2025; Stanford HAI, 2026 AI Index.
#1 Best Overall
How many companies use AI in more than one function?
McKinsey’s 2026 survey says 56% of respondents report AI use in at least three business functions, compared with 51% in the previous survey. This indicates wider organizational distribution of AI, but it does not establish that those applications are generative AI, fully integrated, or producing comparable results.
The same survey reports that 44% see AI scaled across the enterprise, up from 38%. “Scaling” is therefore less common than having AI somewhere in the organization. A company can count as a user while still limiting AI to pilots, individual teams, or isolated workflows.
Which business functions are using generative AI?
Available surveys show recurring concentration in knowledge-heavy and technology-oriented work, while industry changes the pattern.
Do these 3 things before closing this tab:
1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsIT, knowledge management and software engineering
McKinsey’s 2026 findings identify IT, knowledge management and software engineering as the functions where respondents most often report scaling AI agents. Agent scaling is a narrower category than ordinary AI or GenAI use: it implies systems performing multi-step work with some degree of autonomy or orchestration.
Marketing and sales
McKinsey’s 2025 findings place IT, marketing and sales, and knowledge management among functions with frequent AI use. In consumer goods and retail, McKinsey’s 2026 respondents most often point to marketing and sales when reporting agent use.
Supply chain, inventory and manufacturing
Advanced-manufacturing respondents most often identify supply chain or inventory work and manufacturing when describing agent use. This industry variation means there is no universal ranking of “the” leading GenAI function.
What the surveys do not establish
The reviewed sources do not provide a fully comparable year-over-year GenAI adoption series for every individual function. A statement that a function is frequently used, scaled, or associated with agents should not be converted into a precise market-share ranking.
Are companies scaling AI or still running pilots?
Both are happening. The increase to 44% reporting enterprise-wide scaling suggests progress beyond isolated experiments, yet the majority of McKinsey respondents did not report that level of scaling. Function-level use can therefore coexist with fragmented tools, limited governance, or proofs of concept that have not become standard operating procedures.
Agent deployment is an even earlier stage. Stanford HAI reports that agent deployment remained in the single digits across nearly all business functions. Broad GenAI use should not be read as widespread deployment of agents that independently execute complex workflows.
Why adoption is ahead of business impact
McKinsey’s 2026 survey reports that 80% of respondents say AI improved individual productivity, but only 37% attribute at least some EBIT impact to AI. The EBIT figure is essentially unchanged from the 2025 survey. Both numbers are respondent-reported associations, not independently verified causal estimates; productivity gains do not automatically translate into profit.
Workflow redesign matters
Among McKinsey’s survey-defined high performers—organizations reporting at least 5% EBIT impact and significant value—nearly three-quarters say they fundamentally redesigned workflows. About one-quarter of other respondents report such redesign. This is an association within a small, self-reported high-performing group, not proof that redesign alone causes superior financial results.
Recommended Free Tools
The practical implication is that adding a chatbot to an existing process is different from changing approvals, data flows, roles, controls and performance measures so AI can handle meaningful work.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the OpenAI enterprise data adds—and what it cannot show
OpenAI’s 2025 enterprise report combines aggregated, de-identified usage data from its customers with a survey of 9,000 workers across almost 100 enterprises. It offers a provider-specific view of how OpenAI customers use the technology, not a representative estimate for all organizations or industries.
Ronnie Chatterji, OpenAI’s chief economist, writes: “Looking ahead, the next phase of enterprise AI will be shaped by stronger performance on economically valuable tasks, better understanding of organizational context, and a shift from asking models for outputs to delegating complex, multi-step workflows.” That direction is consistent with the distinction between widespread assistance and still-limited agent deployment.
Read the report at OpenAI’s The state of enterprise AI (2025).
Crashes, No Sound, or Screen Glitches?
Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteWindows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallQuick Recap
How to interpret an AI-adoption statistic
- Identify the technology. Check whether the source means broad AI, generative AI, or agents.
- Check the unit. “At least one function,” “three or more functions,” regular use and enterprise scaling describe different levels of reach.
- Read the date and sample. McKinsey’s figures come from its global surveys; Stanford’s 70% figure covers organizations reporting GenAI use in 2025; OpenAI’s figures concern its own enterprise customers.
- Separate use from value. A reported productivity improvement or EBIT impact is a survey response, not proof that AI caused the outcome.
- Look for operating change. Evidence of redesigned workflows, controls, data integration and repeatable deployment is more informative than a pilot count alone.
What this trend means for businesses
- Expect AI to appear in several departments before it is governed as a single enterprise capability.
- Prioritize functions with clear data access, repeatable processes and measurable outcomes.
- Treat agent projects as a separate risk and readiness decision; current deployment remains single-digit across most functions.
- Measure cycle time, quality, revenue or cost outcomes alongside employee usage, and document the baseline.
- Plan for workflow redesign, security, human review and accountability rather than assuming a model can simply be added to an existing process.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
