Issue AI is where measuring and predicting technology returns breaks down
Summary
KPMG singles out new AI tools and platforms as the area where organizations find it hardest to predict and measure returns on technology. Many firms, the report explains, are still searching for the use cases that will genuinely change how they operate. HPE's Phil Mottram observes that some companies have found what works and embedded AI into daily business, while many others have not. Survey data shows that traditional return metrics fall short for AI projects, and many executives struggle to show AI value to stakeholders. The measurement difficulty itself therefore becomes an obstacle, since investment is hard to justify when its payoff cannot be clearly tracked.
Classification
Main topicMacroeconomy & Finance
Region menusGlobal
Impactscope:global
Time horizon0-3 years (2026-07-26)
Published2026-01
Last updated2026-09-30 12:56 KST
Evidence 2
- Global tech report 2026: Leading in the Intelligence Age - Excelling today, shaping tomorrow KPMG International page=13;section=Realizing value from tech investment / New measures for AI ROI 2026-01 accessed 2026-07-26
- Global tech report 2026: Leading in the Intelligence Age - Excelling today, shaping tomorrow KPMG International page=13;section=Realizing value from tech investment / New measures for AI ROI 2026-01 accessed 2026-07-26
Constituent trends 2
Directly linked signals 5
- Signal13 percent of high performers lack business sponsorship against 60 percent of the rest
- Signal17 percent of high performers struggle to communicate AI value against 57 percent of the rest
- Signal55 percent struggle to demonstrate the value of AI to stakeholders and shareholders
- Signal58 percent acknowledge that traditional ROI measures do not fit AI projects
- Signal74 percent see business value from AI but only 24 percent achieve ROI across use cases
Relation types: constitutes · direct_urgent
Public id: fm-bd664bed00a2
