AI ROI is rising, but not where companies expected

2026-07-15 · 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: Fundamental Awareness, short

Summary

An SAP survey, conducted with Oxford Economics and released July 15, 2026, reveals that enterprise AI ROI is increasing, with 69% of executives reporting satisfaction, a slight rise from last year. However, the primary benefits are not in cost efficiency or productivity, but rather in generating business insights, aiding decision-making, and enhancing customer interactions. The study, which surveyed 2,600 director and C-suite executives across 13 countries, found that 30% of tasks are currently AI-assisted, projected to reach 48% in two years. U.S. companies spent an average of \$37.2 million on AI this year, anticipating a 46% increase and an ROI jump from \$9.9 million to \$26.5 million in the next two years. Challenges include defining ROI, data, skills, governance, and managing "shadow agents." Success requires board-level AI literacy and strategic system revamping.

Key takeaway

Executives overseeing AI initiatives who are struggling to quantify AI's value beyond traditional cost savings must shift their focus. Your strategy should prioritize measuring gains in business insights, decision support, and customer engagement, as these are the primary ROI drivers. Prioritize board-level AI literacy and strategic resource allocation to revamp systems and mitigate risks from "shadow agents" accessing unauthorized data. This approach will maximize your AI investments.

Key insights

AI ROI is rising, driven by insights and customer interaction, not cost savings, requiring strategic measurement and governance.

Principles

• AI ROI is inherently difficult to measure.
• Board-level AI literacy drives success.
• Strategically allocate resources for maximum ROI.

Method

To define AI ROI, assess use cases for potential value, measure against implementation effort, and strategically identify processes for change, then quantify outcomes.

In practice

• Review AI deployment best practices.
• Address "shadow agents" for governance.
• Revamp systems for AI integration.

Topics

• AI ROI
• Enterprise AI
• Business Insights
• AI Governance
• Strategic Planning
• Customer Engagement

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

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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.