Agentic AI playbook
Access primary research from 100+ senior AI leaders on enterprise agentic AI strategy and implementation.
Report overview: a tactical guide to agentic AI adoption
The GLG Agentic AI Playbook doesn't just identify the problems; it gives you a framework to help your leadership move from ambition to action.
- Process Discipline: Identify the high-value workflows that could benefit from an agentic AI program vs. simple automation.
- Cross-Functional Collaboration: Align IT, security, and business units to ensure the agent serves the end-user effectively.
- Data Integration and Governance: Get strategies for building a secure, integrated data layer that agents can navigate without risk.
- Operationalization at Scale: Move beyond "one-off" experiments to a scalable framework.
Navigate your agentic AI strategy with GLG
In a world increasingly driven by automated agents, get trusted human expertise from leading agentic AI experts who have built, deployed, and governed these systems.
Leading agentic implementation expertise
Navigate technical hurdles by connecting directly with former CTOs, CDOs, and AI architects who have scaled these systems at Fortune 500 companies.
See our featured agentic AI experts.
Customized vendor & infrastructure benchmarking
Utilize targeted B2B surveys to evaluate the sprawling agentic AI ecosystem. Compare platform capabilities, assess legacy system integration requirements, and ensure vendor infrastructure meets the high data-privacy standards.
End-to-end support for your AI strategy
Agentic AI isn't just a technical shift; it's an organizational one. Access the specific depth required to scale safely, from HR specialists redesigning workflows to data governance leaders securing sensitive customer information.
Agentic AI implementation FAQs
What are the biggest challenges to implementing agentic AI in 2026?
According to our report, implementation is often stalled by two primary concerns:
- Accuracy & reliability: 71% of senior leaders are concerned about erroneous outputs or decisions made by autonomous agents.
- Data security: 65% of respondents worry about agents misusing or inappropriately accessing sensitive data.
Download the report for a step-by-step playbook to mitigate these risks through improved process discipline and governance.Why are companies struggling to move agentic AI from pilot to production?
While the hype is high, our research found that only 46% of organizations currently have at least one agentic AI solution in live production. A major roadblock is "leadership dissonance"-more than half of respondents noted that while their leaders publicly praise the technology, they struggle to articulate a specific, clear business need for it.
How do I build a tactical playbook for AI agent deployment?
The report outlines four critical pillars for successful operationalization:
- Process discipline: Identifying exactly where an agent adds value versus where it adds noise.
- Data integration & governance: Solving the 65% "security gap" by establishing strict data access protocols.
- Cross-functional collaboration: Aligning IT, security, and business units to ensure the agent serves the end-user effectively.
- Operationalization: Moving beyond "one-off" experiments to a scalable framework.
Not sure where to get started? Connect directly with leading voices in agentic AI through a GLG expert call. Learn more about some of our agentic experts.
Is agentic AI ready for enterprise-wide adoption?
The research shows we are at an "inflection point." While many organizations are hitting early pitfalls, the report highlights that "forward-thinking" leaders are now moving away from simple chatbots toward workflow-integrated agents. Success in 2026 depends on leveraging "trusted human expertise" to guide the autonomous decision-making process.
What is the difference between generative AI and agentic AI in a business context?
While generative AI focuses on content creation and responses, our report defines agentic AI by its ability to act within a workflow. It focuses on the technology's "transformative value" in executing multi-step tasks autonomously, which requires a much higher degree of data governance and process mapping than standard GenAI tools.
Can GLG help my company with AI vendor selection?
Yes. GLG connects you with independent experts who have used or implemented specific AI platforms, providing unbiased "user-perspective" insights that help you avoid costly missteps.
According to our report, implementation is often stalled by two primary concerns:
- Accuracy & reliability: 71% of senior leaders are concerned about erroneous outputs or decisions made by autonomous agents.
- Data security: 65% of respondents worry about agents misusing or inappropriately accessing sensitive data.
Download the report for a step-by-step playbook to mitigate these risks through improved process discipline and governance.
While the hype is high, our research found that only 46% of organizations currently have at least one agentic AI solution in live production. A major roadblock is "leadership dissonance"-more than half of respondents noted that while their leaders publicly praise the technology, they struggle to articulate a specific, clear business need for it.
The report outlines four critical pillars for successful operationalization:
- Process discipline: Identifying exactly where an agent adds value versus where it adds noise.
- Data integration & governance: Solving the 65% "security gap" by establishing strict data access protocols.
- Cross-functional collaboration: Aligning IT, security, and business units to ensure the agent serves the end-user effectively.
- Operationalization: Moving beyond "one-off" experiments to a scalable framework.
Not sure where to get started? Connect directly with leading voices in agentic AI through a GLG expert call. Learn more about some of our agentic experts.
The research shows we are at an "inflection point." While many organizations are hitting early pitfalls, the report highlights that "forward-thinking" leaders are now moving away from simple chatbots toward workflow-integrated agents. Success in 2026 depends on leveraging "trusted human expertise" to guide the autonomous decision-making process.
While generative AI focuses on content creation and responses, our report defines agentic AI by its ability to act within a workflow. It focuses on the technology's "transformative value" in executing multi-step tasks autonomously, which requires a much higher degree of data governance and process mapping than standard GenAI tools.
Yes. GLG connects you with independent experts who have used or implemented specific AI platforms, providing unbiased "user-perspective" insights that help you avoid costly missteps.
Stop experimenting. Start executing.
Download the GLG Agentic AI Playbook to bridge the gap between AI potential and proven business ROI.
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