IDC MaturityScape 벤치마크 : 유럽, 중동 및 아프리카의 AI를 동력원으로 하는 조직(2026년)

AI has moved from the periphery of the technology agenda to the center of enterprise strategy, yet scaling it 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 (of which 583 are in Europe, the Middle East, and Africa). It is the updated edition of IDC's inaugural 2025 benchmark (IDC MaturityScape Benchmark: AI-Fueled Organization Worldwide, 2025, IDC #US53271725, March 2025) and applies the framework set out in 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 - a recognition that trust, risk management, and responsible AI practices have become prerequisites for scaling AI. The benchmark assesses enterprise maturity across five stages and these four dimensions to guide line-of-business leaders, C-suite executives, and the IT and data organizations that enable the AI agenda. It helps them locate where they stand relative to peers and prioritize the moves that most accelerate progress. Key findings in this benchmark study are:Only 2.4% of organizations in EMEA have reached the most mature Optimized stage, and just 11.9% 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 (62.8%) 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.Nearly half of EMEA organizations (48.7%) are concentrated in the Opportunistic stage, making it by far the most common level of maturity. Most EMEA organizations at this stage have set an AI strategy and run structured experiments around a few high-return use cases, but delivery lags that ambition: talent remains the main barrier, governance is still fragmented, and gains stay confined to incremental efficiency rather than growth. These organizations remain in a selective, experimental phase rather than scaling AI enterprisewide. The sharp drop from Repeatable (25.3%) to Managed (9.5%) points to a critical bottleneck: many organizations are moving beyond ad hoc experimentation, but far fewer succeed in institutionalizing AI into managed, enterprisewide operations."IDC's AI MaturityScape Benchmark shows that in EMEA, the biggest challenges companies face in becoming AI-driven are related to people, a well-defined AI strategy, and the technological infrastructure of data quality and legacy systems. Addressing the gaps in these areas is essential to stay competitive," said Lapo Fioretti, EMEA research lead, AI-Fueled Business Strategies, IDC.

IDC MaturityScape Benchmark figure

Executive summary

Analysis of AI-Fueled Organization Maturity Benchmark data

• Stages of the AI-fueled organization maturity framework
  • Ad hoc - AI scramble
    • Description
    • Business outcome
  • Opportunistic - AI pivot
    • Description
    • Business outcome
  • Repeatable - AI alignment
    • Description
    • Business outcome
  • Managed - AI transform
    • Description
    • Business outcome
  • Optimized - AI-fueled organization
    • Description
    • Business outcome
• Dimensions of the AI-fueled organization maturity framework
  • Survey findings: Maturity distribution across dimensions
• Evaluating AI-fueled organization maturity: Survivors and thrivers
  • Survey findings: Comparison of survivors and thrivers

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• Related research
• Appendix
• Methodology
• Survey respondent segmentation