📋 What's Inside This Week: Discover the 3 AI moves that set top executives apart, with real-world cases from Goldman Sachs, Google, and Zoom. Get the VELOCITY Framework, 5 low-cost pilot ideas, and curated AI leadership resources.
Hello Visionaries and Leaders,
You know that moment when you realize everyone else seems to "get" something you don't?
That's how most executives feel about AI right now. You've approved the budgets, hired the data scientists, maybe even launched a few "AI initiatives." But if someone asked you what decisions you're making differently because of AI... would you have a good answer?
Here's what's happening: most leaders are treating AI like outsourced consulting - write the check, wait for the magic to happen, wonder why nothing changed.
Meanwhile, there's a small group of executives who seem to have unlocked something different. They're not spending exponentially more or hiring bigger teams. They're just approaching AI in three fundamentally different ways.
And once you see what separates them, everything clicks...
🎯 The 3 Moves That Separate AI-Forward Executives from the Pack
MOVE #1: They Build Their AI Situation Room (Not Just Dashboards)
Look, we've all seen those beautiful PowerBI dashboards that someone updates once a month. The winners? They're checking their AI pulse multiple times a day. Think war room, not conference room.
MOVE #2: They Lead AI Experiments Personally (Not Delegate Them)
This one surprised me at first. The most successful leaders I work with don't just write checks - they're in there testing ChatGPT for their own workflows, sitting through Zoom calls about model performance, asking "dumb" questions that turn out to be brilliant.
MOVE #3: They Treat AI as a Leadership Skill (Not a Tech Problem)
Here's the shift that changes everything: instead of hiring someone to "handle the AI stuff," they make it part of how leadership thinks and operates. It's like making spreadsheet literacy a requirement 20 years ago.
Here's the framework that makes it all work:
THE VELOCITY FRAMEWORK
The Challenge: Most of us treat AI like that exercise bike in the garage - we know it's important, we paid for it, but somehow it never quite becomes part of our daily routine.
The Solution:
Visibility: Set up your AI situation room with real-time dashboards
Experimentation: Launch 3-5 small AI pilots monthly
Learning: Dedicate 2 hours weekly to hands-on AI tool testing
Orchestration: Connect AI initiatives across departments
Culture: Make AI fluency a leadership competency
Investment: Allocate budget for rapid iteration, not perfection
Talent: Hire AI-curious minds, not just AI experts
Yield: Measure business impact, not just technical metrics
Your Action Step 🥊
Block 2 hours this week to personally test three AI tools for your actual executive work. Try ChatGPT for summarizing board materials, Claude for competitive analysis, and Perplexity for market research.
Document what works, what doesn't, and share your findings with your leadership team. Companies that start with executive hands-on testing see 40% faster AI adoption rates across their organizations.¹
🌟 Spotlight: Companies Who Made Bold AI Moves
Goldman Sachs — Firm-wide rollout of GS AI Assistant: Goldman moved from pilots to a company-level rollout of an internal generative AI assistant (GS AI Assistant), expanding access beyond initial teams to thousands of employees as part of a rapid scale plan. This was accompanied by senior hires into AI engineering to support it.²
Google / Alphabet — Product/AI leadership reorg: Google promoted and reorganized senior AI product leadership to speed integration of DeepMind and product teams (a notable 2025 move appointing a senior DeepMind leader to a product/AI role). This is a clear, documented executive decision to accelerate product-grade AI.³
Zoom — Company rebrand and AI-first strategy announcement: Zoom's leadership publicly shifted the company toward an "AI-first" posture and launched built-in AI features (meeting summarization, assistants) as a strategic pivot — a visible, executive-level push to make AI central to product identity.⁴
📊 BY THE NUMBERS
Here's the stat that made me rethink everything: 87% of executives say their AI initiatives stall because leadership isn't engaged enough. Companies where the CEO drives AI strategy? They're 3.2x more likely to see ROI within 12 months.¹
Makes you think, doesn't it?
🔧 Your AI Situation Room Setup
Essential Dashboards & KPIs
Operational AI Health: Track model performance, data quality scores, and system uptime
Business Impact Metrics: Cost savings, productivity gains, revenue attribution
Innovation Pipeline: Active pilots, success rates, time-to-deployment
Team Engagement: AI tool adoption rates, training completion, capability assessments
Competitive Intelligence: Industry AI adoption trends, competitor moves
Recommended Tools:
AI Performance Monitoring & Analytics
Tableau or PowerBI: For executive-level AI impact visualization
Datadog or New Relic: For AI system monitoring and performance tracking
Project Management & Pilot Tracking
Notion AI: For tracking and managing AI pilot experiments
Monday.com with AI features: Project management with built-in AI insights
Automation & Integration
Zapier or Make.com: For no-code automation quick wins
Slack with AI apps: For real-time AI notifications and team collaboration
Personal AI Assistants & Research
Claude or GPT-4: For personal AI assistant workflows
Perplexity Pro: For real-time market intelligence and research
Microsoft Copilot: Integrated AI across your existing Office workflow
Customer Intelligence & Analytics
Salesforce Einstein Analytics: For AI-powered customer insights and predictions
🚀 5 Strategic AI Pilots to Launch This Month
The Strategic Thinking: Most executives jump into AI pilots randomly. Smart leaders choose pilots based on three criteria: high business impact, low technical risk, and fast learning potential. Here are the five pilot categories that deliver the best ROI for executive time invested:
Customer Success AI Agent (Impact: High | Risk: Low | Learning: Fast) Deploy ChatGPT or Claude to handle tier-1 support queries, escalating complex issues to humans Why this works: Immediate cost savings, measurable customer satisfaction impact, teaches you about AI limitations
Sales Intelligence Automation (Impact: High | Risk: Medium | Learning: Medium) Use AI to analyze call recordings and identify deal risks before monthly reviews Why this works: Directly impacts revenue, gives you hands-on experience with AI accuracy, shows competitive advantage
Executive Brief Generator (Impact: Medium | Risk: Low | Learning: High) Automate weekly market intelligence reports using AI to scan industry news and competitor updates Why this works: You personally benefit daily, understand AI research capabilities, low downside risk
Meeting Insights Engine (Impact: Medium | Risk: Low | Learning: Fast) Implement Otter.ai or similar to extract action items and decisions from leadership meetings Why this works: Immediate productivity gain, teaches you about AI accuracy in unstructured data, affects your daily workflow
Talent Pipeline Optimizer (Impact: High | Risk: Medium | Learning: Medium) Use AI to screen resumes and predict candidate success based on historical hiring data Why this works: Addresses critical business need, teaches you about AI bias and ethics, long-term strategic value
Pro Tip: Start embarrassingly small. Each pilot should take less than 2 weeks and cost under $5,000. You're not building the future of AI; you're learning what works in your specific business. Big difference.
📚 This Week's Intelligence
My Recommended Read: "Co-Intelligence" by Ethan Mollick⁵
Why it matters: Mollick provides the most practical framework for leaders to work alongside AI rather than being replaced by it. Key insight: "The most successful leaders in the AI age won't be those who resist the technology, but those who learn to dance with it."
My take: This book completely changed how I advise CEOs about AI adoption. Mollick gets it - this isn't about replacing humans, it's about getting really, really good at working with AI. If you read one AI book this year, make it this one. → Available on Amazon | Audiobook: 8 hours
What I'm Listening To: The AI in Business Podcast (Dan Faggella)
Dan Faggella interviews Fortune 500 executives and AI leaders about real implementations - not theoretical frameworks.
Recent episodes I've found valuable include conversations with pharmaceutical CEOs about AI in drug discovery and financial services leaders discussing AI compliance challenges. Faggella has a knack for extracting practical insights rather than buzzword-heavy discussions. Episodes are typically 25-30 minutes, perfect for commutes.
Why it's worth your time: You'll hear from peers facing the same AI leadership challenges you are, with concrete examples of what worked (and what spectacularly didn't). → Available on all major podcast platforms
Tool I'm Recommending: Perplexity Pro⁶
What it does: AI-powered research assistant that provides sourced, real-time market intelligence.
Why leaders love it:Cut research time by 80% while improving accuracy of strategic briefings
My experience: I've been using this for six months now, and honestly, it's like having a research analyst who never sleeps. I use it for client industry research, competitive analysis, even preparing for executive presentations. Game changer. → perplexity.ai | Cost: $20/month
❓ The Ask
A common question I hear from executives: "My board is pressuring me to show AI ROI, but most of our initiatives are still experimental. How do I demonstrate value when we're still learning?"
My approach: Reframe the conversation entirely. Instead of defending experimental spend, present the cost of inaction. Create three scenarios for your board: aggressive AI adoption, maintaining status quo, and falling behind competitors. Include specific examples of companies in your industry that waited too long to embrace digital transformation. Often, the fear of competitive disadvantage motivates boards more than promises of future gains. Focus on learning velocity and strategic positioning rather than immediate financial returns.
Have a strategic challenge you're wrestling with? The patterns I see across executive teams often reveal solutions that aren't obvious when you're in the middle of it.
💭 Let's Get Real
I'm curious: What's keeping you up at night when it comes to AI leadership?
Is it the pressure to show ROI on experiments? Finding people who actually get both the business and the technology? Feeling like you're always one step behind the competition?
Reply with your biggest AI challenge - I read every email and often feature solutions in future issues. Your challenge might be exactly what another leader needs to hear about.
Before you go: I am putting together something I'm calling "The AI Executive's Quick Start Guide" - 12 frameworks and checklists for leaders who are tired of talking about AI and ready to actually do something about it.
Honestly? I probably should charge for this, but I'd rather see you succeed. Subscibe and get instant access to all 12 frameworks.
Coming next week:
"Stop Building, Start Validating: The Art of Intelligent Laziness"
Why the smartest AI leaders are the ones who do less, not more. I'll share the framework: Minimum viable validation vs. maximum viable product.
🫡See you next week with fresh insights, real challenges, and actionable motivation. Until then, stay courageous, stay visionary, and keep building the future you believe in.
Jitendra Kumar
📰 Bonus Resources: This Week in AI Leadership
Strategic Insight
"The State of AI in 2024" - McKinsey Global Institute McKinsey's annual comprehensive report on AI adoption across industries, with specific data on executive engagement and ROI metrics. → Check Out
Leadership Perspective
"AI for Everyone" Course - Andrew Ng (Coursera) Stanford professor and former Google Brain lead Andrew Ng explains AI strategy for business leaders in non-technical terms. → Check Out
Market Intelligence
"AI Index Report 2025" - Stanford HAI Stanford's Human-Centered AI Institute annual report tracking global AI progress, investment, and adoption trends. → Check Out
References & Additional Reading
McKinsey & Company. (2024). "The State of AI in 2024." Available at: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
Financial Times. (2024). "Goldman Sachs rolls out internal AI assistant to thousands of employees." Available at: https://www.ft.com/content/d570c5a6-02ad-4a28-8129-2f1a02e63603
Reuters. (2025). "Google names insider Kavukcuoglu to lead AI-powered product development." Available at: https://www.reuters.com/business/google-names-insider-kavukcuoglu-lead-ai-powered-product-development-2025-06-11/
Various technology publications covering Zoom's AI-first strategy pivot and feature launches in 2024-2025.
Mollick, E. (2024). Co-Intelligence: Living and Working with AI. Portfolio Books.
Perplexity AI Research Platform. https://perplexity.ai
MIT Sloan Management Review. (2024). "Building AI Capabilities." Available at: https://sloanreview.mit.edu
Zapier Automation Platform. https://zapier.com
Make.com Automation Platform. https://make.com
Otter.ai Meeting Intelligence. https://otter.ai
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