„AI use is widespread, but the vast majority of companies cannot demonstrate measurable financial or productivity impacts, and scaling stalls.”
Counter-narrative
AI delivers real results and productivity gains, with a significant portion of leaders reporting positive returns. This is represented by the Wharton–GBK study, which says 80% of leaders report positive ROI. BearingPoint (AI delivers real results) and EY (AI increases productivity) argue similarly.
Carriers
PwC CEO Survey, Gartner, McKinsey, IMD, EY-Parthenon, Deloitte
Analysis
The narrative posits a persistent gap between AI investment and demonstrable results, documented by many successive surveys. It is fueled by major consulting firm surveys and KPMG data, which states that nearly half of leaders have scaled back agents due to cost. Scaling is also stalled: BearingPoint states that 13 percent of organizations are scaling AI, while Deloitte states that 15 percent have reached multi-agent implementation. Paradoxically, consultants promoting the gap also have an interest in the narrative, because the solution (transformation, scaling) means new contracts. Its weakness is that the measurement itself is incomplete: EY states that only 14 percent of UK CEOs fully see costs and returns, so the gap is partly a measurement gap. Early, individual-level gains (EY: half of leaders see productivity improvements) have not yet appeared in corporate results.
Evidence: moderate — Több nagy mintás felmérés jut azonos irányú eredményre: PwC (4454 vezérigazgató), IMD (6000 felsővezető), Gartner, és egy 1200 vezérigazgatós felmérés. Mindegyik vezetői önbevalláson alapul, közvetlen pénzügyi mérés nincs mögöttük, és a Wharton–GBK kutatás ellentétes irányú eredményt mutat.
What's at stake: Whether the persistent return gap leads to reduced investment before organizations learn to turn AI into real results.
Narrative sub-threads
The narrative splits into 5 branches; a story may belong to several branches, and some may not appear in the main narrative's list.
Everyone uses it, few see the benefitAI return on investment
no measurable search
0
Senior executives do not see returnsAI efficiency
no measurable search
0
Stuck in the experimental phaseAI implementation in a company
1
Agents: cost and retreatAI costs
no measurable search
0
Hungarian and European usage–benefit gapAI use in companies
no measurable search
0
No profit without redesignAI productivity
no measurable search
0
World
Topic and search term
Weekly
Average
Everyone uses it, few see the benefitai roi
6
Senior executives do not see returnsai productivity
16.1
Stuck in the experimental phaseai pilot purgatory
no measurable search
0
Agents: cost and retreatai agent costs
0.6
Hungarian and European usage–benefit gapenterprise ai adoption
2.7
No profit without redesignai value realization
0
Google Trends relative search index over the period studied, weekly average. A narrative and its sub-threads appear in a single comparison: 100 is the group's most-searched day, and the figures can only be compared within the group. The search term was chosen by machine analysis; it measures how much the term is searched, not how widespread the narrative is.
According to Economx, AI brings no profit to 95% of domestic companies. It is advisable to start with a single use case tied to revenue or cost, not a general tool subscription.
The benefit often shows up on their side, yet they cannot demonstrate it. It is worth documenting time savings and error counts, as these form the basis for further funding.
Hungary
Domestic data aligns. According to Portfolio, 92% of companies use AI, but nearly two-thirds of them do so experimentally or on a limited scale. Economx reports that 95% of them do not generate revenue. Bell Research states that 84% of respondents use AI applications, but only 30% for work. A Bell Research survey covering 302 companies found that 40% of development firms evaluate AI business value based on experience, and some cannot quantify the impact.