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GLG releases agentic AI implementation report based on 110 senior leaders

The expert network's playbook leans on practitioner interviews to map where agentic AI projects stall in production.

INFLXD Research··3 min read
GLG releases agentic AI implementation report based on 110 senior leaders

GLG, the expert network, released a report on agentic AI implementation on February 12, 2026, built on input from 110 senior leaders responsible for agentic AI deployments at their companies. The firm positions the report as a tactical playbook for unlocking value inside workflows, with a section on compliance framework and another on the technology's key challenges and strategies to overcome them.

The document is the latest in a string of expert-network-branded research products from the major platforms (GLG, Third Bridge, AlphaSense/Tegus, Guidepoint) that take primary-source interviews and re-package them as thought leadership. The implicit pitch to corporate buyers and investors: if you want this kind of operator panel on your own questions, hire us.

GLG's framing matters as much as the contents. The press release leads with the line that organizations are "hit[ting] early pitfalls" on agentic AI. That is a notable rhetorical shift from the 2024 and early-2025 vendor cycle, where most outputs from consultancies and platform vendors emphasized transformation upside. A report that opens by acknowledging implementation friction reads as a deliberate calibration toward the buyer-side audience, the operators and CIOs who have spent eighteen months running pilots and now have to defend production budgets.

The sample, 110 senior leaders, is small enough to be qualitative rather than survey-grade, large enough to escape the n-of-12 problem that plagues most vendor research. GLG has not, in the public release, disclosed the geographic split, industry mix, seniority distribution, or methodology for selecting respondents. Those are the questions a research analyst would put to the expert panel before citing the document in a memo.

What to watch in the next ninety days: whether competing expert networks publish counter-research with different sample compositions, and whether any of the AI infrastructure vendors (LangChain, CrewAI, the hyperscaler agent platforms) cite the GLG numbers in their own materials. The latter would tell you the report has crossed from marketing artifact into industry reference, which is the bar for these documents to matter.

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