Observed Signal · Feb 18, 2026 · Survey Release · Source: https://martechseries.com/feed/ · Impact: 3/5 · Sentiment: Negative
Survey Reveals Major Gap in Agentic AI Readiness
Reltio published results of a Harvard Business Review Analytic Services pulse survey, “Unlocking the Data Advantage in the Age of Intelligence,” which surveyed 325 global business and technology leaders. The survey shows strong AI interest—94% of organizations are exploring or implementing AI—but major gaps in data readiness for agentic AI. While 94% rank trust in data reliability as critical, only 39% say they are highly proficient; just 15% consider their data foundation "very ready" for agentic AI. Respondents cite data silos (46%), insufficient data talent (42%) and unclear data strategies (39%) as top barriers. The report stresses need for unified, real-time, governed data, semantic layers, and evolving governance from compliance to strategic differentiator.
The survey quantifies a widespread industry data-readiness gap for agentic AI—key insight for vendors, platforms and enterprises planning agentic AI deployments and data investments.
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Key Takeaways & Evidence Grounding
- Reltio announced the release of a Harvard Business Review Analytic Services (HBR-AS) pulse survey titled "Unlocking the Data Advantage in the Age of Intelligence."
- The survey sampled 325 global business and technology leaders.
- 94% of organizations surveyed are exploring or implementing AI; 94% rank trust in data reliability as the most critical capability for AI success.
- Only 39% of organizations say they are highly proficient in data reliability and only 15% consider their data foundation "very ready" for agentic AI.
- Top barriers to agentic AI readiness cited were data silos (46%), insufficient data talent (42%), and unclear data strategies (39%); 89% say data governance is highly important but only 37% report high proficiency.
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Data Management Emerges as Top AI Challenge for Enterprises
A Semarchy survey of 1,000 global C-level executives across the UK, US and France finds data management (51%) is now the single biggest AI challenge, overtaking cost and talent. The report says 51% of leaders are implementing AI initiatives without Master Data Management (MDM) foundations and 38% are not enforcing data quality standards. Consequences already reported include AI project delays (22%), operational inefficiencies (21%) and compliance issues (19%). While ethics/regulation prioritization rose from 50% in 2025 to 77% this year, optimism about meeting AI goals doubled to 92%. Nearly two-thirds (65%) are pursuing agentic capabilities and 48% are investing in DataOps. Semarchy CTO Craig Gravina warned that sidelining data leadership (only 7% of CDOs and 18% of CIOs seen as chief AI strategists) risks accumulating AI technical debt.
Survey: HR Less Confident Than C‑Suite on AI Readiness
Protiviti's fifth AI Pulse Survey, “The AI‑People Conundrum: Learning to Lead, Not Lag,” finds a confidence gap between C‑suite executives and HR leaders on enterprise AI readiness. Nearly 80% of C‑suite executives expect AI to boost revenue and bottom‑line performance within three years, while CHROs are significantly more skeptical about workforce readiness and HR process scaling: only 5% of CHROs expect AI to support at least half of HR tasks in the next three years, and just 13% strongly agree their job designs are ready for mass AI adoption. The report highlights differences across functions (IT, finance, supply chain, audit) and urges HR to lead workforce transformation alongside technology investment.
Why AI-ready Data Infrastructure Is Hard
The article argues that the core barrier to AI readiness is not new technology but organizational gaps around data: quality, governance, ownership, priorities, budgets, and trust. While traditional systems and data fragmentation have long created inconsistent definitions and manual workarounds, AI amplifies these faults by scaling poor data into automated recommendations and actions. The author recommends focusing on clear use cases — building the data foundation one prioritized use case at a time — rather than attempting an all-encompassing program. Technical barriers (legacy systems, unstructured content, integration challenges) and political friction among employees and leaders also require deliberate governance, change management, and judgment about which decisions remain human-led.
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