Tag: AI Strategy
-
Generative AI, Agentic AI, and AI Agents: The Boardroom Distinction That Matters

Generative AI creates content. Agentic AI pursues goals. AI agents are the workers that combine models, tools, rules, and workflow context to execute an approved job.
-
OpenAI’s Enterprise Agents Do Not Eliminate AI Services. They Prove Why They Matter.

Enterprise AI platforms do not make implementation optional. They increase the need for workflow redesign, trusted data, governance, adoption, and accountable execution.
-
Forward Deployed Engineers Prove AI Adoption Is an Organizational Change Problem

Forward deployed engineers are a sign that AI products are not self-implementing. Real enterprise AI value requires technical depth, business strategy, workflow redesign, governance, adoption, and organizational change.
-
AI’s Biggest Fear Is Not Unemployment. It Is Irrelevance.

The deeper fear around AI is not only job loss. It is role absence: the loss of responsibility, usefulness, identity, and purpose as intelligence becomes abundant.
-
The PocketOS Database Deletion Was Not an AI Failure

The PocketOS incident is not a reason to stop using AI agents. It is a warning that agentic AI needs real governance: least-privilege access, approval gates, audit logs, rollback plans, and guardrails built into the operating model.
-
AI Is a Skill, Not a Feature

Giving everyone AI tools is not enough. Real productivity gains come from training people how to use AI, redesigning workflows, and building organizational learning capability.


