Adapting to the Intelligence Age

Once upon a time, the workplace looked like this: 🔺 A wide base of operators ⬛ A middle of managers 🔝 A small circle of execs at the top making “strategic” decisions And each layer was dependent on the prior layers knowledge and context. But that is no longer the case - AI is cracking that structure apart and now #1 question I get asked is “Where Should AI sit?” I have an entire framework for that, based on trail and error and over 60+ different structures and outcomes across a variety of industries, but to keep it super duper simple, the new mental model is: The Upside Down Pyramid. 🔻 Bottom layer: Automated out. Replaced by RPA, bots, agents. (FYI … Deloitte reports that intelligent automation has led to zero net growth in administrative headcount in over 65% of enterprises) 🧍🏻Middle layer: Thinned out, middle-management pruning some say - as real-time insights and AI copilots give execs direct access to context. They are no longer the widest & thickest structure. 🔝 Top layer: Amplified, not eliminated, with a new diverse set of players at the top. AI translators and cross-functional builders who know tech and business (fyi, Harvard Business Review reported that 42% of managers’ tasks are now deemed automatable—and that number is climbing) In summary: We’re not watching a job extinction event, we’re witnessing an extreme skills migration. 🤯 RECOMMENDATIONS: 1. Redefine your middle. If you’re a middle manager, become the bridge—not the bottleneck. Strategic orchestration beats tactical supervision. 2. Train your top. Your leaders need fluency in AI—not prompt tokens. Nothing is a silver bullet. Invest in simulation-based leadership programs. The new org chart favors the thinkers, the builders, the doers—with AI as their multiplier. Are you adapting to the new shape of work? #FutureOfWork #AITransformation #Leadership #OrgDesign #WorkforceShift #DigitalStrategy #CareerAdvice #DataLeadership >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> Worlds 1st Chief AI Officer for Enterprise, 10 patents, former Amazon & C-Suite Exec (5x), best-selling author, FORBES “AI Maverick & Visionary of the 21st Century” , Top 100 AI Thought Leaders, helped IBM launch Watson My 2nd #TEDx talk will be released in 2 weeks!

Nobody is telling the truth about how disruptive this is going to be. Maybe since I’m ‘unaffiliated’ for now, I can. 👀 AI isn’t just coming for workflows. It’s coming for the foundations of knowledge work — and for the identities built on it. For CMOs and marketing leaders, this hits hard. For years, we’ve found meaning in our playbooks and how we execute. Now, much of that is being automated, flattened, or redefined in real time. And here’s the part we’re not talking about enough: This isn’t just a professional disruption. It’s a personal one. To survive it — let alone lead through it and flourish — we can’t keep pushing at the same velocity, hoping to outrun the change. We need to slow down. Reground. Rebuild. That means investing differently: Mind – Slowing down to build emotional resilience in a time of accelerated everything. Learning to lead from clarity, not reaction. Body – Remembering we’re not brains on a stick. Stewarding our embodied experience through sleep, movement, and nourishment — so we can actually sustain the work. Soul – Recognizing that our sense of identity is often wrapped up in our work — and that AI will inevitably challenge how we define purpose and value. This season demands we examine those foundations, and do so in community, not isolation. This is the real work of leadership in the Intelligence Age. Not just learning to prompt better. But learning to stay human — when everything else is speeding up.

In this latest Forbes article, I draw a compelling line from Ada Lovelace’s 19th-century foresight to today’s AI-driven enterprise transformations. Lovelace envisioned machines augmenting human creativity—a vision now realized as #generativeAI reshapes industries. Accenture's experience with over 2,000 gen AI projects reveals that only 13% of companies achieve significant enterprise-wide value, while 36% are scaling AI for industry-specific solutions. Success in this new era hinges on more than just technology investment. Companies must also invest in their people, prioritize industry-specific AI applications, and embed responsible AI practices from the outset. Organizations adopting agentic architecture - digital teams comprising orchestrator, super, and utility agents—are 4.5 times more likely to realize enterprise-level value. Here are five key lessons we’ve learned: 1. Lead with value from the top: Executive sponsorship is crucial. Companies with CEO sponsorship achieve 2.5 times higher ROI from their #AI investments.  2. Invest in people, not just technology: Empower your workforce with the skills to harness AI. Organizations excelling in AI transformation invest in broad AI upskilling, adopt dynamic workforce models, and enable human + agent collaboration.  3. Prioritize industry-specific AI solutions: Tailor AI applications to your sector’s unique needs. Companies creating enterprise-level value are 2.9 times more likely to have a comprehensive data strategy to support their AI efforts.  4. Design and embed AI responsibly from the start: Ensure ethical and effective AI integration. Organizations creating enterprise-level value are 2.7 times more likely to have responsible AI principles and governance in place across the AI lifecycle.  5. Reinvent continuously: Stay adaptable in the face of ongoing change. Companies with advanced change capabilities are 2.1 times more likely to achieve successful transformations. These lessons should serve as a practical playbook for navigating the complexities of #AI integration and achieving sustainable growth. Please read the full article to explore how Lovelace’s visionary ideas are shaping the future of business through #generativeAI. https://lnkd.in/gEVzQeRA

 🔥 #KeepLearning — Your Greatest Asset as a #GenX Leader in the AI Era is the combination of AGE + ADAPTABILITY.💡 In today’s AI-driven world of work, adaptability isn’t just a nice-to-have... 👉🏾 It’s a superpower. And for many seasoned and mid-career professionals, thriving in this age of AI isn’t really about mastering all of the latest tech skills. It’s more about learning and leaning into what we’ve always done best: ✅ Navigating change with resilience. ✅ Applying wisdom to new challenges. ✅ Evolving with purpose and intention. While AI may feel like uncharted territory, you’ve actually been here before. Whether it was adopting and adapting to the rise of the internet (remember Netscape?), the advent of social media, smartphones, and many other workplace shifts… We’ve always embraced a level of resilience and reinvention. The difference now? The pace of change has accelerated. 👉🏾 But that’s when the magic happens. Not just in learning new tools, but in embracing a mindset that amplifies leadership and fuels behavior change. Here are a few key tips to activate your adaptability superpower in the AI era: 1️⃣ Adopt a Growth and Beginner’s MINDSET: Approach AI with curiosity, not caution. You don’t need to be an expert—you just need to be open. 2️⃣ Embrace Your Unique HUMAN INGENUITY: Communication, critical thinking, and emotional intelligence aren’t just important—they’re AI amplifiers. These superpowers give you an edge when it comes to maximizing prompts and context window conversations. 3️⃣ Embrace BEHAVIOR CHANGE: It’s not enough to know that AI is here—you have to shift how you work, make decisions, and solve problems. Small, intentional changes in your daily habits create long-term transformation. 4️⃣ Learn Through MUTUAL MENTORING: Partner with colleagues across all generations to explore AI tools, while also offering your experienced strategic and leadership insights in return. Remember… You’ve been adapting and adopting your entire life.  Don’t stop now. Let’s go. 🚀 #AI #leadership #MidCareerMastery #MasteryMap

AI is reshaping industries, but making the leap can be daunting. My CEO Nigel Vaz, recently shared key strategies for navigating this transformation with Forbes. Here are my top 7 takeaways: 1) Reimagine, Don't Just Upgrade: AI isn't about porting legacy systems to new tech—it's about rethinking your entire business model to fully leverage digital capabilities. 2) Break Down Silos: Success with AI requires a unified approach across departments. The lines between sales, marketing, and customer service are blurring, necessitating collaboration. 3) Start with Data: Good AI starts with good data. Build strong data foundations before diving into AI to ensure meaningful, scalable outcomes. 4) Move Beyond Proof-of-Concepts: Many companies get stuck at the proof-of-concept stage. Instead, focus on developing use cases that can scale across the organization. 5) Ethics Matter: Addressing bias and ethical concerns in AI is crucial. Consider the broader implications of your AI models and the data they use. 6) Commit to Continuous Learning: The AI landscape is evolving rapidly. Companies (and individuals) must embrace a culture of continuous learning, unlearning, and relearning. 7) Think Big, Act Small: Balance innovation with practicality. Test AI in ways that demonstrate immediate value, but always with an eye on broader organizational impact. Invaluable insights for any organization looking to transform successfully. 🌟 Publicis Sapient https://lnkd.in/gq9pfNtu

AI: A Paradigm Shift, Not Just a Plugin In my interactions, I encounter many organizations that are risking potential competitive advantage by relying on an incremental AI approach, allowing external, enterprise platforms to shape their strategies and adoption. While AI-enabled tools offer valuable enhancements, they were primarily designed for operational efficiency, not for driving transformative intelligence. The challenge is clear: relying solely on vendor-driven integrations optimizes processes of the past without fully capitalizing on AI’s potential to define the competitive edge of tomorrow. What’s needed is a shift in leadership perspective. Implementing AI requires more than passive adoption; it demands a proactive, tailored approach built upon: - Strategic use cases that focus on value creation over convenience - Robust data governance to ensure integrity and long-term resilience - Cross-functional alignment, encompassing technology, ethics, risk management, and human capital - Visionary thinking that explores how AI can fundamentally redefine organizational capabilities rather than simply enhance them This is a conversation for the C-suite and boardroom, not just another checkbox in your technology stack. For executives, the core question becomes: Are we allowing tools to dictate our strategic direction, or are we steering our AI approach with purpose, insight, and foresight to unlock its competitive advantage? The answer is a crucial one for your firm's near-term future. If you are seeking support in navigating this important moment, let's chat.

When I returned from Switzerland, I made a costly mistake: I resisted change. While the world raced ahead with new tech and digital transformation, I clung to "the way things were." The result? I fell behind. Hard. But here's the truth that changed everything: The rules of work aren't just changing—they're being completely rewritten. Here's what you need to know: • The divide is stark: AI-skilled workers earn up to 53% 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗽𝗲𝗲𝗿𝘀 in the same roles • The crisis deepens: 69% 𝗼𝗳 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗿𝘀 can't find AI talent while planning to eliminate traditional jobs • The threat is immediate: 375 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝘄𝗼𝗿𝗸𝗲𝗿𝘀 must switch careers by 2030 due to AI displacement But here's the good news—you can choose your path. 3 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗠𝗼𝘃𝗲𝘀 𝘁𝗼 𝗠𝗮𝗸𝗲 𝗧𝗼𝗱𝗮𝘆: 1. 𝗘𝗺𝗯𝗿𝗮𝗰𝗲 𝘁𝗵𝗲 𝗔𝗜 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲 - Stop viewing AI as competition - Start using it as your career accelerator 2. 𝗗𝗲𝘃𝗲𝗹𝗼𝗽 𝗵𝘆𝗯𝗿𝗶𝗱 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 - Combine your domain expertise with tech fluency - Create value AI alone cannot replicate 3. 𝗝𝗼𝗶𝗻 𝘁𝗵𝗲 𝗰𝗵𝗮𝗻𝗴𝗲, 𝗱𝗼𝗻'𝘁 𝗿𝗲𝘀𝗶𝘀𝘁 𝗶𝘁 - Invest in continuous learning - Build your AI literacy, even if it's uncomfortable The cost of resistance? I lived it. The reward for adaptation? I'm living it now. Don't let fear of change hold you back like it once did me. The future belongs to the adaptable. Are you ready to evolve? Want the full story?  Read my latest piece: "𝗪𝗵𝗮𝘁 𝗔𝗽𝗽𝗹𝗲'𝘀 𝗥𝗲𝗰𝗲𝗻𝘁 𝗔𝗜 𝗛𝗶𝗿𝗶𝗻𝗴 𝗦𝘂𝗿𝗴𝗲 𝗠𝗲𝗮𝗻𝘀 𝗳𝗼𝗿 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿" Follow me for daily insights on navigating the AI revolution. Repost to help others future-proof their careers.

As someone committed to driving the evolution of organizational strategies, the rise of generative AI interests me, as it represents not just an evolution in technology but a transformative opportunity for us all.   Recent research on sustainable gen AI adoption by my colleagues Dana Maor, Jan Bouly, Julie Goran, and Sandra Durth deeply resonated with me, and my experiences collaborating with institutions and leaders dedicated to embracing change. Here are four crucial takeaways I wanted to highlight –   1. Reframing Gen AI: It’s essential to view gen AI not as a replacement but as an enhancer of human potential. I often encourage teams to see how these tools can free us from mundane tasks, allowing us to focus on what truly matters: creativity, innovation, and strategic thinking. 2. Understanding Resistance: Throughout my career, I’ve learned that resistance can be a powerful catalyst for growth. By addressing concerns head-on, we create an environment where everyone feels valued and included in this journey. 3. Prioritizing Human Skills: In this age of AI, developing our human skills - adaptability, creativity, and problem-solving - is crucial. I advocate for a culture of experimentation, encouraging teams to engage with AI tools in safe, low-stakes environments. 4. Measuring Success: Lastly, we must be strategic in how we measure the impact of gen AI. Establishing metrics that reflect usage, user satisfaction, and overall business outcomes is key.   As we navigate this exciting frontier, I am reminded of the importance of human-centric leadership. After all, it’s our responsibility to champion change, empower our teams, and ensure that we harness the full potential of AI to drive sustainable growth. #AIbyMcKinsey #FutureOfWork #ChangeManagement

Andrew Ng has shaped AI's future for 20+ years, but his most important discovery is often overlooked. It's transforming how enterprises implement AI today: Andrew's journey from Stanford professor to AI pioneer revealed a critical pattern: Companies consistently fail to adopt AI for one key reason. Their ambitions exceed their capabilities too early. Through years of experience at Google Brain, Coursera, and Landing AI, he developed a systematic approach that's more relevant than ever. The framework that emerged challenges conventional wisdom: • Start small with focused pilot projects (resist the urge to transform everything) • Build hybrid teams (technical expertise alone fails) • Train leadership first (minimum 4 hours of focused AI training) • Develop strategy only after completing these steps His most groundbreaking discovery? AI solutions can work with limited datasets - implementing machine vision with hundreds of images instead of millions. This opened doors for companies previously blocked by data constraints. But there's a catch most miss: Leadership understanding determines project success more than technical capability. Organizations thrive when leaders grasp AI's potential AND limitations. This insight becomes crucial as we enter the age of autonomous AI agents. The market is shifting rapidly toward: • Multi-agent systems working in concert • Continuous learning and adaptation • Workflow optimization at scale Early adopters are seeing: • 3-5x faster process execution • 40-60% cost reductions • Enhanced operational outcomes This is why we built CrewAI - to help enterprises implement and scale AI agent systems the right way. The window for competitive advantage remains open, but narrows daily. Want to stay ahead of AI transformation? Follow me @joaomdmoura for insights on enterprise AI implementation and the future of autonomous agents. And definitely follow @AndrewYNg - his wisdom shaped how we think about AI adoption. Like/Repost if you found this valuable! 🙏