Artificial intelligence is moving into a new phase of business adoption. Rather than being limited to individual experiments and pilot projects, organizations are increasingly using AI across multiple business functions.
McKinsey’s 2026 Global Survey on AI found that nearly nine in ten respondents reported regular AI use in at least one business function, while 44% said AI was scaling across their enterprise, compared with 38% a year earlier.
One of the notable developments is the growing use of agentic AI—systems designed to perform tasks, make decisions, and work across business processes with greater autonomy. Among large organizations with annual revenue above $1 billion, 40% of respondents reported scaling AI agents in at least one function, up from 27% the previous year.
AI is also influencing how organizations approach software development. McKinsey reports that 32% of surveyed organizations had decided against purchasing at least one software product or feature because they could build the functionality internally using agentic coding tools.
However, wider adoption does not automatically translate into financial results. The same survey found that 37% of respondents attributed at least some EBIT impact to AI, a figure that remained broadly unchanged from the previous year. AI-related operating costs were also reported as a constraint by about one in five respondents.
The research points toward an important shift in how businesses approach AI. Successful implementation is increasingly connected to workflow redesign, strong data foundations, governance, and organizational readiness, rather than simply adding AI tools to existing processes.
McKinsey’s 2026 technology research similarly identifies AI as a major investment priority, with companies increasingly looking at agentic automation and data capabilities as part of broader business strategy.
For businesses evaluating AI solutions, the focus is therefore moving beyond the question of whether to use AI. The more practical questions are where AI can create measurable value, which processes can be improved, and what technology and organizational foundations are required to scale it responsibly.
Source: McKinsey, The State of AI: Global Survey 2026; McKinsey Global Tech Agenda 2026.
