AI confidence is on the rise despite cost concerns

2026-07-08 · Source: Information and Enterprise Technology News | CIO Dive - Www.ciodive.com · Field: Business & Management — Corporate Strategy & Leadership, Artificial Intelligence & Machine Learning, Operations & Process Management · Depth: Intermediate, short

Summary

KPMG's Q2 2026 AI survey, based on responses from over 2,100 senior tech decision-makers across 20 countries in April and May, reveals a significant increase in enterprise AI confidence. The report indicates that 71% of organizations are progressing well towards an integrated AI-human workforce, a rise from 60% in Q1. Furthermore, nearly a quarter of organizations (25%) are now embedding AI into daily workflows, up from 13%. Companies with clear leadership accountability for AI outcomes are achieving materially better results, including established ROI at three times the rate of those without. The survey also notes a shift towards more mature AI deployment phases, with 29% in later stages, and a growing focus on scaling AI and understanding its business role, rather than debating the technology itself. Cost visibility, rather than strict control, is highlighted as essential for realizing AI's value.

Key takeaway

For Directors of AI/ML or CTOs overseeing enterprise AI initiatives, prioritize establishing clear C-suite accountability for AI outcomes. Your focus should shift from merely sponsoring AI to defining who owns its results, as this directly correlates with achieving three times higher ROI and greater confidence in value delivery. Implement robust cost visibility mechanisms to understand AI's true economic impact and guide strategic scaling decisions, ensuring your organization moves beyond theoretical discussions to practical, value-driven AI integration.

Key insights

Clear leadership accountability for AI outcomes significantly accelerates value realization and ROI in enterprise AI adoption.

Principles

• Defined AI accountability structures yield materially better results.
• Cost visibility, not just control, is essential for AI value.
• AI maturity shifts focus to scaling and business integration.

In practice

• Implement C-suite accountability for AI system outcomes.
• Prioritize human-AI collaboration and robust AI governance.
• Build capabilities to measure AI deployment and operational costs.

Topics

• Enterprise AI
• AI Adoption
• AI Governance
• Cost Visibility
• Leadership Accountability
• ROI Measurement

Best for: Executive, Director of AI/ML, VP of Engineering/Data, CTO

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Editorial summary, takeaway, and curation by AIssential. Original article published by Information and Enterprise Technology News | CIO Dive - Www.ciodive.com.