AI in 2026: Scaling Tools, Seeking ROI

Organizations are rapidly scaling AI and agentic tools, yet enterprise-level financial impact remains flat for the majority of businesses. While individual productivity has soared and companies are increasingly building their own software, operating costs are starting to limit usage. The path to significant ROI requires a fundamental redesign of workflows rather than simply inserting AI into existing models.

Key Points

• AI adoption is shifting toward enterprise-scale scaling, with large organizations leading in the use of autonomous agents.
• Agentic coding tools are enabling companies to build custom software in-house, disrupting traditional software procurement models.
• There is a disconnect between high individual productivity gains and stagnant enterprise-wide financial ROI.
• AI operating costs, including token expenses, are emerging as a constraint for one-fifth of organizations.
• High-performing companies achieve superior results by fundamentally redesigning workflows and prioritizing innovation over simple efficiency.

Sentiment

Cynical and skeptical, particularly toward the source of the report and the long-term viability of AI-generated in-house software.

In Agreement

• Organizations are indeed attempting to use agentic coding tools to build software in-house rather than purchasing external products.

Opposed

• The trend of building in-house with AI tools is likely to create significant technical debt, similar to the 'Microsoft Access' issues of the 1990s.
• The report is perceived as a promotional piece for McKinsey's consulting services rather than an objective industry analysis.
• There is doubt regarding the actual realization of ROI, despite the report's optimistic framing.
• McKinsey is viewed by some as a firm that has been historically damaging to the software industry.