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GenAI and Agentic AI Adoption

Moving GenAI and Agentic AI from experimentation to enterprise scale​

About this category

Practical guidance for leaders on adopting GenAI and agentic AI: choosing high-value use cases, sequencing rollout from assistants to agents, making platform decisions, and scaling successful pilots across the enterprise.

Generative AI and autonomous agents are moving from demos to real business workflows, and leaders face a fast-changing set of choices about where to apply them, how to roll them out, and how much autonomy to grant. This category is about adopting these technologies deliberately and turning early experiments into dependable, enterprise-wide capability.

What You'll Find Here​

  • Use-Case Selection: Where GenAI and agents deliver real value, and where simpler automation or traditional AI is the better fit.
  • Adoption Pathways: Moving from copilots and assistants to workflow automation and, in time, autonomous agents.
  • Platform and Technology Choices: Model selection, RAG, agent frameworks, and buy-versus-build decisions from a leadership perspective.
  • Agentic AI in Practice: Designing agents with the right level of autonomy, human oversight, and guardrails.
  • Rollout and Change Management: Pilots, phased deployment, user enablement, and driving real usage across teams.
  • Lessons and Pitfalls: Common reasons GenAI and agent initiatives stall, and how to avoid them.

What You'll Learn​

  • How to separate genuine opportunity from hype.
  • How to sequence adoption from low-risk assistants to higher-autonomy agents.
  • How to make sound platform and vendor decisions in a fast-moving market.
  • How to scale successful pilots into production with user trust and adoption.

Who It's For​

Executives, product and technology leaders, architects, and transformation teams responsible for bringing GenAI and agentic AI into the enterprise.