Gemini Babla

Generative AI can produce polished ideas quickly, making it easier for anyone to sound like an expert. As a result, credibility increasingly depends on real experience, original insight, and practical knowledge. Authentic expertise helps organizations separate meaningful ideas from automated commentary. Read more: https://lnkd.in/gehqzBYQ #ThoughtLeadership #AIinBusiness #LeadershipInsights #BusinessStrategy #InnovationLeadership #DigitalTransformation #ExecutiveLeadership #FutureOfWork

6

1 Comment

Visiting the Bay Area for the first time, I was blown away. Not just by the scale or the pace of innovation, but by something else. The networking culture there is next level. Every event, every conversation, I heard the same questions: ➡️ Who are you? ➡️ What do you do? ➡️ What are you all about? ➡️ How can we potentially work together? ➡️ How can we help each other? That mindset really stood out. So I asked Ryan Baird, who is third generation Silicon Valley, if it has always been this way. Ryan told me the relationship-first approach is at the core of how things work here. While other places can feel more transactional, Silicon Valley has always been about building through relationships. That is actually why he started Baird Augustine, to bring relationship culture back to investment banking. Ryan’s family goes way back with the Valley. His grandfather worked at Lockheed Martin. Both parents were at Hewlett Packard Enterprise. He grew up with the HP Way. That mindset shaped not just HP, but Apple and basically every major tech company that followed. It all comes back to this. Build relationships first and you can accomplish big things together. Here is a short clip from our conversation. To hear this full conversation, just tap "View my newsletter" at the top of this post. 👆🎬

5

Day 1 at MIT Professional Education Today’s session was an inspiring deep dive into the art and science of driving innovation. The discussions centered on methodologies for problem framing, the importance of challenging assumptions, and fostering collaboration to unlock creative potential. Here are the key takeaways: → Main Themes and Insights: 1. The Power of Questioning: Innovation begins with challenging the status quo. Asking "Why?" is not just a habit but a mindset that must permeate all aspects of work. Defining the right problem is often more impactful than rushing to solve it. 2. Structured Methodologies for Innovation: Tools such as the Double Diamond framework and Human-Centered Design were highlighted as essential for uncovering genuine needs and creating meaningful solutions. A clear focus on desirability, feasibility, and viability ensures sustainable success. 3. Collaboration and Multidisciplinary Teams: Diverse perspectives lead to more robust solutions. Building intelligent teams with complementary skills amplifies creativity and drives superior outcomes. 4. Risk and Creativity: Embracing risk and breaking established thinking patterns is crucial for innovation, especially in leveraging new technologies like AI. Playful experimentation often leads to groundbreaking ideas. 5. User-Centric Problem Framing: A deep understanding of user needs—explicit, unmet, and latent—was emphasized as a foundational step. Techniques like interviews, direct observation, and "How-Why" diagrams are invaluable for uncovering hidden opportunities. → Actionable Next Steps: - Dedicate more time to defining problems using structured tools like the Double Diamond and "How-Why" diagrams. - Foster regular sessions to question processes and challenge assumptions. - Build multidisciplinary teams that combine diverse expertise and perspectives. - Evaluate projects based on their alignment with real user needs and their potential for creating value. - Explore how AI can be applied to solve previously intractable challenges while carefully assessing its impact and potential. → Key Questions to Explore Further: - Are we spending enough time framing problems before jumping to solutions? - How can we ensure our teams remain aligned and collaborative across disciplines? - What untapped potential exists in leveraging AI for meaningful innovation? This session was a powerful reminder that innovation is not just about inventing—it’s about creating value. By focusing on asking the right questions, building the right teams, and applying thoughtful methodologies, we can unlock new possibilities and drive impactful change. What are the challenges you face in driving innovation within your organization? Let’s keep the conversation going! #MITDigitalPlusPrograms #MITOnCampus Blade Kotelly

29

A new global BCG study shows that only 5% of companies are truly succeeding with AI. Read the study: https://lnkd.in/gJixhFk6 Those 'future-built' firms are achieving revenue gains and cost savings that are up to five and three times higher than those of other companies, respectively. What is their secret? They’re not just using AI to automate tasks; they’re rebuilding how their business operates with the help of agentic AI, which works like digital employees. The result is faster growth, smarter workflows and an ever-widening gap between the few leaders and the many laggers. The message is clear: move now or risk being left behind.

2

Quick video (Harvard Business Review the one on IG is better) highlighting the crux of the AI impact on jobs debate. While Dan Schulman’s view is pragmatic and honest, Brad Smith is leadership-driven, inspiring and equally within reach. Where I think the difference lies is our willingness to intentionally select and invest in the future we want for ourselves. I.e. If we let machines do the work for us (sit back, do nothing), or use machines to improve how we do the work (which requires effort)…. So our choice. So curious what others are seeing/experiencing that tip the predictions one way or the other. https://lnkd.in/eEXtduAH

11

Large enterprise CMOs are facing a critical challenge: Drive AI transformation while doing right by the teams that built your organization. The C-suite wants AI transformation yesterday. Their teams—many with decades of institutional knowledge—are skeptical, exhausted, or both. Here's what I keep hearing: "I know we need to move fast. But I can't just blow up my team in the process." These leaders aren't stuck because they don't understand AI. They're stuck because they understand people. They need a plan for that first and foremost when the org gets to a certain size. They know that legacy expertise is still valuable and long-tenured employees deserve honesty about what's coming, not false promises. Transformation that breaks trust isn't really transformation—it's just chaos with better tech. This is the real leadership challenge of AI transformation - navigating the human complexity of change in organizations where relationships, tenure, and culture run deep.

18

2 Comments