Visiting Coca-Cola HQ: AI, Culture, and Innovation

Most companies say they want to be AI-first. But all they do is run pilot projects and post buzzwords. ↓ OpenAI just dropped the clearest guide yet to actually build an AI-first company. It’s not about tech — it’s about how your org thinks, moves, and leads. Here’s the 18-step playbook in 5 parts: 1️⃣ ALIGN → Get leadership in sync • Set a company-wide vision • Define measurable goals • Have execs model real AI usage 2️⃣ ACTIVATE → Get teams using AI daily • Launch role-specific training • Build a team of internal AI champions • Link AI usage to performance reviews 3️⃣ AMPLIFY → Share and scale what works • Centralize wins in a shared AI hub • Celebrate success in team meetings • Create peer-to-peer learning groups 4️⃣ ACCELERATE → Move at AI speed • Unblock tool + data access • Streamline how ideas get built • Stand up fast-response AI councils 5️⃣ GOVERN → Light rules, clear guardrails • Define what’s “safe to try” • Run lightweight audits, not bottlenecks AI-first isn’t a title. It’s how your company operates every day. I share my learning journey here. Join me and let's grow together. Enjoy this? Repost it to your network and follow Dibya Jyoti Datta for more

OpenAI just validated everything I've been teaching for 2 years. Their new report says companies need 5 things to stay ahead: ▶️ Align. ▶️ Activate. ▶️ Amplify. ▶️ Accelerate. ▶️ Govern. Sound familiar? Here's what I've seen actually work in 50+ workshops: ALIGN = AI Council from Day 1 OpenAI says "get leadership buy-in." I say: Form a council with Sales, Marketing, HR, Finance, and Operations. ACTIVATE = Hands-On, Not Theory OpenAI says "structured training programs." I say: Your tools, your workflows, your use cases. One marketing director went from 0% AI use to managing 30-40 campaigns. 70% efficiency gains. AMPLIFY = Share What Works OpenAI says "build knowledge hubs." I teach teams to document wins immediately. A packaging client from using AI for content generation: One LinkedIn post → 1M impressions → New business conversations. ACCELERATE = Break Down by Tasks OpenAI recommends "remove friction." My approach: Analyze tasks, not jobs. Result? 6-8 hours saved weekly per person that applies these principles. GOVERN = Start Secure OpenAI talks "lightweight guidelines." I insist: Company AI accounts from day one. No personal ChatGPT for client data. The report mentions early adopters growing revenue 1.5x faster than peers. That tracks with what I'm seeing: ▶️ One client: 5x discovery calls, 30% pipeline lift in 2 weeks ▶️ Every client: 20-30% efficiency in first 90 days Here's what OpenAI didn't mention: The best time to implement? During your existing company events. Sales kickoffs. All-hands meetings. Team offsites. 73 out of 74 employees showed up when we added AI training to a manufacturing company's event. By 2027, there will be three kinds of companies. AI emergent. AI native. Or out of business. OpenAI's report confirms it. The question isn't IF you should adopt AI. It's whether you'll lead the change or be left behind. What's your biggest challenge with AI adoption right now? P.S. - If you're planning a 2025 team event and want to add practical AI training, let's talk. I bring the exercises, you bring the team. #CorporateAI #AIWorkshops #AITransformation #Leadership #WorkforceDevelopment

Talked to a friend last week, working in the supply chain management industry, and they've been trying to implement AI for over 8 months. Still no production deployments. Or even marginal gains. Meanwhile, he knows some of his competitors are already reaping the benefits of AI. 8 months. Multiple pilots. Zero production systems. Leadership is losing faith. Here's what actually happened: they built a custom solution without proper planning (and loads of FOMO). Poor implementation. No user training. Results were unreliable. The team lost trust. Now, they aren't using even the dozens of Claude Enterprise licenses the company bought and paid for the year. Here's what we recommended to save it: Step 1: Rebuild trust with what actually works. Stop talking about the failed custom solution. Get people using those Claude Enterprise licenses properly. Give them proper training on prompt engineering, what data is safe to share with Claude, etc. Step 2: Start small and succeed. Pick one team. Their original custom solution scope was way too broad, too many people to please, too many workflows to try and "solve" at once. Step 3: Listen before building. Focused on that team, run a discovery process to understand what people actually need and how they are currently performing the tasks. This is a crucial step to further increase the team's trust not only in AI but also in whatever we ultimately build. Step 4: Build the solution. Once teams believe AI can help them, then rebuild that custom solution—correctly this time. After years of building products and AI systems, I can tell you: you get one shot at user trust. The good news? Trust can be rebuilt. But it happens one successful product, feature, or implementation at a time, not through grand strategies or fancier pilots. Stop building blindly. Start succeeding. #AI #DigitalTransformation #Leadership

[Bookmark this 🔖] AI isn’t just for tech experts—it’s a shortcut to faster thinking, smarter decisions, and better results. Whether you're learning something new, making an important decision, or looking to stand out at work, these AI prompts will give you an edge: --- 1. Get Instant, High-Quality Feedback on Your Work "Review my [email, report, presentation] and suggest improvements in clarity, impact, and professionalism." 🔹 Why it matters: Polishes your work and makes you look like a pro in any setting. --- 2. Learn Any Skill 10x Faster "Create a 30-day learning plan for [insert skill] that breaks it down into daily actions. Include key resources and exercises to apply what I learn." 🔹 Why it matters: Turns overwhelming goals into a clear, doable roadmap. --- 3. Make Faster, Smarter Decisions "For [insert decision], list the pros and cons based on best practices and real-world examples. Recommend the best course of action and why." 🔹 Why it matters: Helps cut through uncertainty and move forward with confidence. --- 4. Break Down Complex Topics in Minutes "Explain [insert topic] in simple, clear terms that a beginner can understand." 🔹 Why it matters: Saves hours of research and helps you grasp new ideas instantly. --- 5. Summarize Anything in Seconds Summarize this [article, report, book] into a short, actionable list of key takeaways. 🔹 Why it matters: Extracts the insights that matter—no fluff, no wasted time. --- 🔥 Which AI prompt do you use the most? Drop it in the comments. ♻️ Repost this because the best leaders bring others along. ➕ Follow Joselle Deocampo-Gautam (https://buff.ly/qZvTKix) for more. 📩 Subscribe to On Point and join a growing community of decision-makers shaping the future of business & technology. https://buff.ly/TdE2PbV #ArtificialIntelligence #AIPrompts #LeadershipDevelopment #ProductivityHacks #LearningAndDevelopment #DecisionMaking #InnovationStrategy #ExecutiveMindset #TechForLeaders #SmartWork #AIAssistants #BusinessTransformation #LifelongLearning #OnPoint #BeRightOnPoint

The Four C’s: Our Human Advantage in the Age of AI As Artificial Intelligence transforms industries at lightning speed, executives everywhere are asking: What truly differentiates humans from machines? It’s our uniquely human traits—what I call the Four C’s: 1. Critical Thinking Humans don’t just process data—we challenge assumptions, weigh context, and draw meaning. For example, when Nike launched its “Dream Crazy” campaign featuring Colin Kaepernick, it wasn’t simply a marketing move—it was a calculated decision that weighed cultural tension, long-term brand equity, and societal impact. AI can crunch numbers on sentiment, but it can’t evaluate risk, values, and vision the way humans can Free Course: Harvard’s Critical Thinking: Innovative Solutions to Complex Challenges https://lnkd.in/gTE47XA5 —tools to foster courageous, collaborative innovation. 2. Creativity We fuse emotion, abstraction, and experimentation. Pixar’s storytelling blends art, tech, and resonance—something no algorithm alone achieves. AI can generate imagery, but only humans imagine worlds with meaning. Free Courses: CreativeLIVE streams creative and entrepreneurial workshops https://lnkd.in/gbzqY3fc . Google Digital Garage offers “Communicate your ideas through storytelling and design.” https://lnkd.in/gApQnmf3 3. Communication AI shares facts—but humans build trust, vision, and culture. Marc Benioff drives us all at Salesforce to embody the essence of the beginner’s mind and effective communications by capturing why it’s essential for innovation: “You can have an expert’s mind, where you have few possibilities, or you can have a beginner’s mind, where you always have every possibility." Free Courses: Effective Communication on Great Learning Academy https://lnkd.in/ghDAVTaD . Microsoft’s “Improve communication skills with the 21CLD skilled communication dimension.” https://lnkd.in/gDfmp-Qx 4. Changeability (Capability) Machines update code. We adapt mindsets, reinvent roles, reshape industries. Blockbuster stalled; Netflix pivoted—and humans, not algorithms, drove it. Free Courses: Ivy League + MIT OpenCourseWare on leadership, adaptability, and strategy—all freely accessible. https://lnkd.in/gPtKids9 Why This Matters Leaders from Google, Amazon Web Services (AWS), Salesforce, NVIDIA, and consultancies like Slalom emphasize these human traits when evaluating future talent. As AI advances, the Four C’s will be the foundation of success—for careers, organizations, and cultures. Next Steps Self-audit: Rate your fluency in each C. Upskill: Take one free course this quarter (e.g., Harvard’s Creative Thinking). Apply: Host an innovation or storytelling session with your team. Share: Post your journey—invite collaboration, inspire others. By embracing Creativity, Communication, Critical Thinking, and Changeability, we’re not just future-proofing careers—we’re shaping the future.

This MIT stat has been everywhere on my feed the last few days: 95% of AI pilots fail. My first reaction? If you’re still “piloting” AI in 2025…you’re already behind. 😅 By the time your pilot concludes, the stack has already shifted. What you were testing six months ago? Obsolete. This research and findings? Probably obsolete. The orgs actually making progress are putting these 4 simple things in place: 1️⃣ Clear AI philosophy / strategy for the business 2️⃣ Accessible, democratized AI stack 3️⃣ Dedicated time for employees to build 4️⃣ Company-specific use cases with immediate impact That’s it. No endless pilots. No half-baked rollouts. Just building in the flow of work. Take Andrew Golden at RetailNext. Instead of piloting yet another vendor tool, he built his own engagement platform for $600 - tailored to his team’s philosophy and instantly actionable for leaders. That’s vibe coding in action. And it’s what separates the 5% who succeed from the 95% who stall. 👉 I broke this down further (plus a playbook for getting started) in the latest Huertanomics Field Notes newsletter. 💬 Link in comments. #AIforHR #PeopleOpsasProduct #VibeCoding #OrgDesign #FutureofWork

If you’re leading an organization, these two reads are a must for this week: OpenAI’s Staying Ahead in the Age of AI leadership guide and Andrew Ng’s newsletter reflecting on Coursera’s shift from knowledge-first to skills-first education. Put together, they read like a memo to leaders: adoption isn’t a feature race, it’s an operating-system change for your organization. What this means in practice: (1) Treat AI as a skills program, not a software rollout. Coursera’s skills tracks and “Role Play” simulations point the way: don’t just explain RAG, have people use it to solve real work. Move beyond tool demos to repeatable competencies (prompting, evals, workflow design, agent orchestration). (2) Align from the edge in. Adoption sticks when frontline teams see how AI removes their specific bottlenecks. Translate strategy into team-level intents (“reduce claim cycle time by 40%,” “cut no-show handling to <60 seconds”), then let teams choose the best tool to hit the goal. (3) Activate with credible modeling. If executives aren’t showing their own before/after workflows, the message is that AI is optional. Normalize experimentation time; make “show your working” part of weekly rituals. (4) Amplify what works in practice. Stop re-solving the same problems in silos. Stand up a lightweight hub for prompts, workflows, and guardrails; require teams to contribute back when they win. (5) Accelerate with fast lanes, not exceptions. Give teams a clear intake path, pre-approved data access patterns, and a small cross-functional council that can unblock pilots in days. (6) Govern without gridlock. Practical guardrails beat policy PDFs no one reads. Convert rules into decision trees and make them queryable (“Is this safe to try?”). If you want to move fast and keep being helpful to the markets you serve, you need to shift from “knowledge about AI” to “skills with AI,” and wire your organizations to learn in public.

"Data-driven" is everywhere, but most companies are still figuring out what it actually means in practice. From what I’ve seen across organisations, the winners don’t start with AI tools - they start by treating data as a business asset, building trust in its quality and matching plans to how ready people are to believe the numbers and use the tech. My framework for getting there: 1️⃣ Start with business goals → What decisions need better data?  2️⃣ Quality over quantity → Make data trustworthy before scaling tools or AI 3️⃣ Empower people → Train teams to understand and use data confidently 4️⃣ Deliver quick wins → Small successes build momentum 5️⃣ Iterate → Strategy isn’t a doc; it’s a living process 🟩 Alignment between tech + people accelerates results 🟥 It needs leadership patience - It's cultural change, not just a platform purchase 👉 Where is your organisation on this journey – just starting, scaling, or still searching for the right approach? #DataStrategy #DataDriven #AnalyticsLeadership #BusinessIntelligence #AI

OpenAI just shared 15 practical actions leaders can use to move from talk → execution. Here’s the breakdown: 1. Align → Link AI to employee skills and company goals. → Show support openly. → Measure clarity with surveys and dashboards. 2. Activate → Train people, encourage experiments. → Track usage, reviews, and promotions tied to AI. → Push prototypes into production. 3. Amplify → Share AI wins across teams. → Keep one central hub updated. → Track forum contributions. 4. Accelerate → Remove bottlenecks in infra and approvals. → Track time-to-production. → Fund and staff high-impact projects fast. 5. Govern → Clear “safe-to-try” rules. → Quarterly reviews with legal + risk. → Measure governance delays and fix them. If you’re serious about building an AI-first organization, this is your playbook. --- I share my learning journey here. Join me and let's grow together. Enjoy this? Repost it to your network and follow Karn Singh for more

Leaders have a lot of questions about AI right now... It is without doubt the biggest disruptor ever seen in the marketing world. And that understandably comes with a whole LOT of big, gnarly questions... ❓ How do I keep AI ethical, safe, and brand-aligned? ❓ How do I balance speed and competitiveness with human wellbeing? ❓ How do I move from scattergun AI to something strategic? ❓ How do I prove the real ROI of AI - beyond “we saved time”? ❓ How do I get my board on board to get budget and buy-in? ❓ How do I stop tool sprawl and pick a safe, reliable martech stack? ❓ How do I integrate AI into my teams - without - adding more work? ❓ How do I balance speed and competitiveness with human wellbeing? ❓ How do I help my team adapt and deal with resistance? ❓ How do I upskill people fast without frying their brains? And the biggest one of all... ❓ How the heck can I navigate all this... and still do my day job Over the past 8 weeks this smart lot have tackled all this and more in our AI Growth Academy "AI For Leaders" program. 12 hours. 6 live sessions. 24 frameworks. Plenty of AI arm-wrestles. Brain matter flying everywhere. And moments where the only answer was a big old lie down. What came out the other side? A tonne of AI-IQ, smart thinking and a practical roadmap: 5 Ps to find your way through something as huge and unwieldy as AI: ✅ Prep & Readiness ✅ Plan & Vision ✅ People, Culture & Change ✅ Process & Tech ✅ Perform & Scale From where do I start → to actionable things you can do today. From overwhelm → to confidence and direction. Huge congratulations to Emma Fulford, Stu Sheridan, Julie Fenwick, Kelly Monardo, Michelle Young and Rick Buscombe for carving out the time and investing in yourselves. Your teams are so lucky to have you all at the helm leading the charge 🙌 🙌 🙌 #AIForLeaders #AIGrowthAcademy #AIStrategy #AIEthics #AIMarketing #AIForCMOS #AIRoadmap #FutureofMarketing #FutureLeaders