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How to Accelerate AI Sense of Urgency — 45 re-usable ideas to inspire, deepen, and expand action
💡 A few weeks ago, I was asked to help plan how 9,000 employees in a global organization could optimize
Winning the Race — AMERICA’S AI ACTION PLAN – July 2025
The White House unveiled America’s AI Action Plan:
a strategic roadmap to strengthen U.S. leadership in AI through innovation,
AI First CEOs — Ask These Habit-Forming Questions
What does it mean to be an AI-First CEO? It stems from the “First Principles Approach” popularized by Peter Thiel.
CEO Guide – Five Steps for AI Use
Source: MindLi Motivation: AI is Here and Now The AI age is here—CEOs of every firm, in every industry or
Marketing, Sales, and Service in The Age of AI
BCG’s latest research underscores that AI—particularly generative AI—is poised to transform B2B marketing, sales, and service. But many first movers
3 Ways to Spark AI Adoption at Work
From a managerial perspective, AI adoption at Microsoft underscores the importance of achieving widespread organizational engagement to drive true business
6 Blind Spots for AI Leaders
The IBM report titled “2024 Technology Leader Study: 6 Blind Spots Tech Leaders Must Reveal” highlights critical areas where technology
How 3 companies are using AI to empower innovation
In 2024, generative AI is making significant strides, with a dramatic increase in adoption among organizations. McKinsey & Company reports
AI Data Drop: 5 Innovative Ways To Work With Copilot
Microsoft asked people across professions for their most innovative and helpful uses of Copilot, with examples of prompts.
When Not to Use Generative AI
Gartner’s podcast episode examines situations when generative AI use is inappropriate and explores other impactful AI techniques.
McKinsey on The Race to Deploy AI
McKinsey’s report highlights the race to maximize AI benefits through significant job transitions and skill upgrades in the work field.
Lessons From McDonald’s AI Ordering System Failure
McDonald’s AI ordering failure highlights the need for thorough testing, proper support, and cautious implementation in AI projects.