IDC MaturityScape 벤치마크 : 전 세계 AI 활용 조직(2026년)

AI has moved from the periphery of the technology agenda to the center of enterprise strategy, yet scaling AI remains challenging. Many organizations continue to struggle to translate investments into measurable business value, and the rapid rise of agentic AI is adding a new layer of complexity to deployments. The AI-fueled organization is one in which strategy, governance, people, and technology are orchestrated so that intelligence is embedded across the operating model rather than confined to isolated pilots, supporting the full spectrum of AI technologies, including descriptive, interpretive, predictive, generative, agentic, and physical AI.This IDC study presents results from IDC's MaturityScape Benchmark AI Survey, released in May 2026 across 1,900 organizations worldwide. It is the updated edition of IDC's inaugural 2025 benchmark (IDC #US53271725, March 2025) and applies the framework set out in the 2026 definition study, IDC MaturityScape: AI-Fueled Organization 2.0 (IDC #US54450625, April 2026). The most significant change this year is the elevation of governance to a distinct fourth dimension alongside strategy, people, and technology, recognizing that trust, risk management, and responsible AI practices have become prerequisites for scaling AI. The benchmark assesses enterprise maturity across five stages and four dimensions, and is intended to guide line-of-business (LOB) leaders, C-suite executives, and the IT and data organizations that enable the AI agenda, helping them determine where they stand against peers and prioritize the moves that most accelerate progress. Key findings in this benchmark study are:Only 3.1% of organizations worldwide have reached the most mature optimized stage, and just 12.8% have progressed to the two most advanced stages (managed or optimized) overall. Becoming an AI-fueled organization is achievable, but it is a sustained journey rather than the product of a single deployment.More than six out of 10 organizations (61.3%) remain in the two least mature stages, ad hoc and opportunistic, underscoring how much foundational work in strategy, governance, and data still lies ahead before AI can deliver enterprisewide value.The worldwide mean maturity score barely moved, rising to 2.43 in 2026 from 2.39 in 2025. The near-flat result suggests that while the AI market is evolving at an extraordinary pace, execution is not keeping pace. The broad middle remains stuck in the early stages even as expectations, tooling, and competitive pressure escalate. But the share of organizations reaching the optimized stage jumped from 0.4% to 3.1%, which is evidence that a leading cohort is beginning to separate from the pack even as the broad middle advances slowly."IDC's 2026 IDC MaturityScape Benchmark: AI-Fueled Organization 2.0 confirms the disconnect between the AI supercycle's rapid infrastructure buildout and organizations' ability to execute. Strategy is outpacing delivery, talent remains the main barrier, and AI is still limited to incremental efficiency gains, not growth," says Andrea Siviero, global research lead, AI-Fueled Business Strategies at IDC. "Organizations are recognizing that scaling AI isn't just a technology challenge; it requires a deliberate strategy, strong governance, and a culture ready to embrace AI-driven change. Those that align business priorities with a coordinated AI road map will be the ones to turn experimentation into measurable business value," adds Xiao Liu, research manager, AI-Fueled Business Strategies at IDC.

IDC MaturityScape Benchmark figure

Executive summary

Analysis of AI-Fueled Organization Maturity Benchmark data

• Stages of the AI-fueled organization maturity framework
• Dimensions of the AI-fueled organization maturity framework
  • Survey findings: Maturity distribution across dimensions
  • Survey findings: Maturity distribution across regions
• Evaluating AI-fueled organization maturity: Survivors and thrivers
  • Survey findings: Comparison of survivors and thrivers

Advice for technology buyers

Learn more

• Related research
• Appendix
• Methodology
• Survey respondent segmentation