More Than Half of Organizational Leaders Say Recent Technology Investments Failed to Achieve Intended Outcomes, New Eagle Hill Research Finds

An Eagle Hill Consulting survey found that 51% of senior business leaders said recent technology investments failed to fully achieve intended outcomes, with only 35% considering day-to-day work impacts before rollout. Continued reliance on legacy processes and workarounds, plus insufficient workflow and behavioral change, are cited as key obstacles to realizing returns from AI, automation and cloud investments. The findings highlight execution and adoption risk rather than technology deployment as organizations increase spending on emerging technologies.

Analysis

This is not a direct earnings signal for IPS; the survey is small, unweighted, and commissioned by a consulting firm with an incentive to emphasize implementation gaps. The investable read is instead that enterprise AI budgets may shift from new-seat purchases toward integration, governance, workflow redesign, and managed-services spend. That mix is relatively favorable for ACN, IBM, and ServiceNow (NOW), but it can delay the revenue conversion and margin payoff embedded in premium valuations for application software vendors whose AI monetization depends on customers rapidly scaling usage.

Over the next 1-3 months, the key risk is not a broad reduction in AI spending but longer sales cycles, expanded proof-of-concept periods, and lower initial deployment sizes—particularly in regulated, legacy-IT-heavy verticals. In the 6-18 month horizon, vendors that can quantify task-level productivity and embed controls into existing workflows should gain share from horizontal copilots that remain discretionary. Consensus may be underestimating implementation-services capacity as a bottleneck: if enterprises cannot operationalize deployments internally, consulting utilization and pricing can improve even while software consumption growth disappoints.

The contrarian point is that weak adoption is not uniformly bearish for software. It supports durable demand for platforms with system-of-record ownership and workflow orchestration, because customers will consolidate tooling rather than add another standalone AI interface. The thesis is falsified if upcoming results show accelerating paid AI-user conversion and consumption revenue across broad SaaS, rather than the expected pattern of strong bookings but muted production usage.

Key Decisions for Investors

• No position in IPS on this item: there is no identifiable company-specific revenue linkage, and the survey methodology is insufficient to support a directional trade.
• Favor a 3-6 month pair trade of long NOW / short an equal-dollar basket of higher-multiple, AI-narrative SaaS exposure via IGV. NOW is better positioned if budgets migrate toward workflow integration; target 10-15% relative upside, with a stop if NOW subscription-revenue growth decelerates by more than 300 bps versus IGV constituents over the next two earnings cycles.
• Accumulate ACN on market weakness ahead of the next earnings report rather than chase: implementation, data modernization, and change-management work can extend AI spending duration even if license deployment is delayed. Underwrite mid-single-digit downside versus 12-18 month upside if consulting bookings and utilization reaccelerate; exit if bookings remain negative and management does not identify AI-related services as a material pipeline contributor.
• Use next earnings season as an alert for software shorts rather than an immediate broad short: monitor net-revenue retention, consumption growth, and disclosed paid AI attach rates at CRM, NOW, and MSFT. A divergence of rising AI bookings but flat production usage would support reducing IGV exposure and increasing the NOW/IGV relative-value position.