Dive Brief:
- Large enterprises are scaling agentic AI faster than smaller companies, and their use is growing quickly, according to McKinsey data released this week. The management consulting firm surveyed more than 1,700 employees across industries and company sizes for the report.
- Some enterprises that are scaling agentic AI are using coding tools to replace some of their software purchases, the report found. Nearly one-third of respondents said they decided against buying at least one software feature because they can now build it in-house.
- Even though agentic tools use more compute than previous tools, and are therefore more costly, tech leaders are finding value from these use cases, Michael Chui, co-author of the report and senior fellow at QuantumBlack, AI by McKinsey, said in the report. “Organizations are planning to invest more, even as they develop new disciplines for optimizing ROI from their AI expenditures,” Chui said.
Dive Insight:
Although some organizations deploy AI to save time or money, most are struggling to define and realize ROI. Despite a lack of clarity, AI investments continue to rise.
Four in five respondents in the McKinsey report said AI has improved their productivity, but enterprise-level financial impact hasn’t yet followed — the proportion of employees reporting cost savings driven by AI remains unchanged from last year, according to the report.
As organizations face changing AI operating costs, even those that tout the technology’s upside have had to become budget-conscious.
One in five respondents said their organization limits a range of AI use because of its operating costs. Still, 28% of respondents said their organization is spending more than 10% of their total enterprisewide budget for information and communication technologies on AI, and they expect that number to grow next year.
Although the tech industry has seen job cuts this year, the overall number of roles in the industry remains steady, with the labor market favoring AI-savvy workers. The McKinsey report found two-thirds of companies have had little or no AI-related change.
To manage IT spending optimally, businesses should be deliberate about when to buy something instead of building it, and take greater ownership over their technology and change agendas, Lieven Van der Veken, senior partner at McKinsey, said in the report.
“They are also treating operating costs as a design constraint, not an afterthought, and making the deeper changes in workflows required for value realization,” he said.
The rise of in-house development and the evolving role of developers to manage AI outputs instead of writing code is part of this shift, Chui said.
“Spend on horizontal AI-enabled tools, such as chatbots, is increasingly managed as a necessary cost of doing business, similar to office productivity and communications tools,” Chui said. “AI influences other parts of the IT budget, too: Agentic coding tools are creating a more capable option for moving some software development in-house.”
