How to Empower Teams With AI

I speak to 100's of HR team's a year. Here's 5 steps the best ones are doing to embed AI.   Too many HR teams are either intimidated or overwhelmed when it comes to AI, and they're falling behind.   Instead, embrace the below steps and you'll be in the top 10% of People teams using AI.   1. Create dedicated, protected time   You can't just slap AI on top of your day job, or squeeze it in between meetings (duh).   The work you're doing today will always trump the deep focus time you need to be successful.   So carve it out, choose 1 of these: - Commit 1-2 hours a day to AI, or - Give 1 day a week to AI.   If you need to drop something to make this happen, do it. This must be higher priority than at least one thing you're team does or it won't get the attention it needs.   Protect the time, remove distractions — go into deep focus and spend it doing one of the things in the next step.   2. Time box it   If you're just starting out, commit to doing a short term blitz and then work out how to embed it longer term.   Here's a format you can steal:   6x week sprint:   Weeks 1-2: Focus only on learning/immersing yourself in what's possible Weeks 3-4: Focus on testing the tools you saw in weeks 1-2 Weeks 5-6: Move from testing to actually building (what to build is covered in step 5)   3. Curate learning, don't create   There's so much free content available on using AI that you'd be crazy to spend money on it.   - Greg Isenberg - Ruben Hassid - Jeff Su These are just three (from dozens of) creators I love, who share genuinely actionable insights on embedding AI.   Spend time watching and seeing what can be done - this will get your brain subconsciously thinking about AI solutions for your team.   4. Empower your team   The key message here is: 'remove friction'   Time is a friction (tackled in step 1), but the second biggest one I see, is money.   Don't let budget be a blocker here.   If you're CEO wants you to embed AI practices (and you should to quit if they don't) — then securing a small budget is a no brainer.   There's so many tools - give your people a chance to trial a bunch of them and see what works.   Then: - Keep the ones that work - Remove the ones that don't   Don't make a big procurement process block game changing improvements.   5. Start small when building   Don't try to boil the ocean.   You won't be able to replace a HRBP in a week.   Instead, start small.   Pick the smallest workflow/process/interface under your remit, and start there.   Use your success here to build momentum and move up the value chain.   Don't let overwhelm and intimidation stop you from becoming a more effective People team.   Tell me, which step do *you* think is most important to embedding AI in People teams?

Stop Treating AI Like a Tool, Start Onboarding It Like a Teammate! 🚀 Are you struggling to get real value from AI in your team? The problem might not be the technology, but how you're integrating it. Just like a new hire, AI needs clear roles, training, and ongoing feedback to truly thrive. : * Define clear responsibilities: What specific tasks will the AI handle? * Invest in "AI literacy": Everyone on the team needs to understand AI's capabilities and limitations. * Establish communication protocols: How will the AI share its insights and when will it need help? * Provide continuous training and feedback: Help the AI learn and improve, just like you would with any team member. * Foster collaboration and trust: Encourage teamwork between humans and AI. * Iterate and adapt: Be flexible and adjust your approach as the AI evolves. * Address ethical considerations: Be mindful of bias and ensure fairness. The key takeaway? Treat AI as a partner, not just a tool. Build a collaborative environment where AI can flourish, and you'll unlock its true potential.

In a world where AI announcements seem to drop every 15 minutes (seriously, it’s so hard to keep up), I've been reflecting on what actually matters beyond the hype. As a people leader navigating this landscape, I've learned that the challenge isn't just adopting AI tools quickly—it's adopting them thoughtfully. This is especially important at HubSpot, where helping our employees move faster helps our customers win faster. I'm seeing AI reshape not just what we do, but how we make decisions and prioritize our people. Here are some approaches that have worked well for us as we continue to test and learn: 1. Expedite access to AI tools and encourage experimentation. We're experimenting with the latest versions of Claude, Gemini, ChatGPT, and more—providing teams access within hours of new releases, not weeks. This creates a culture of experimentation and keeps us ahead of the curve. 2. Foster knowledge-sharing. We've created dedicated channels where employees share their AI wins and habits. Our People team sends a weekly "MondAI" digest featuring different employee use cases that inspire others across the organization. 3. Prioritize leader enablement. We've built AI-first resources, starting with People Leaders who then cascade knowledge to their teams. This isn't just about tools—it's about developing judgment for when AI enhances human work and when human expertise should lead. 4. Seek external expertise. We regularly bring in experts from companies like Anthropic and Google to share insights with our teams. We've cultivated a culture of learn-it-alls, not know-it-alls. 5. Integrate AI into existing workflows. We're incorporating AI tools directly into team processes, focusing on high-impact, repetitive tasks first. Our AI support bot now handles over 35% of tickets while maintaining high customer satisfaction. The most exciting part? Watching our teams develop the discernment to make AI work harder for them, not the other way around. When people and technology make each other stronger—that's the sweet spot. Fellow people leaders: How are you balancing rapid AI adoption with thoughtful implementation that truly empowers your people? Other insights we can learn from?

Should I buy this apple? Let’s ask the LLM. It sounds silly, but this is where we’re headed. AI is quickly becoming a default response engine for every question, every decision, every moment of hesitation. But when a tool becomes a crutch instead of a catalyst, we might lose... duh duh duh... critical thinking. So how do we ensure our human teams don’t turn into AI regurgitation machines? How do we design systems and cultures that encourage our teams to think with AI, not just through it? Here are 5 principles to guide your organization: 1. Ask questions: Don’t just optimize for efficiency. Optimize for exploration. Encourage your teams to use AI to explore different angles, test assumptions, and surface edge cases. 2. Stay skeptical: A confident AI answer isn’t the same as a correct one. Build workflows where teams interrogate the output and their own thinking. 3. Design for reflection, not reaction: AI works fast, but real insight takes time. Slow down. Create moments for deliberation, interpretation, and synthesis. Embed review cycles that go beyond checklists.  4. Value original thinking: If everyone’s using the same tools, differentiation comes from how you think with them. Encourage teams to add context, bring in their own perspectives, and challenge outputs. 5. Keep humans in charge: Systems should amplify judgment, not eliminate it. Avoid over-automating critical decisions. Make space for disagreement, deliberation, and nuance. If we’re not careful, we won’t just outsource answers to AI. We’ll outsource our agency. The ability to question, reason, and make meaning is what makes us human. We have to stay engaged, curious, skeptical, and accountable. That’s how we ensure AI serves us, not the other way around. Because the real potential of AI isn’t to replace human thought, but to push it further. #AI

Throwing AI tools at your team without a plan is like giving them a Ferrari without driving lessons. AI only drives impact if your workforce knows how to use it effectively. After: 1-defining objectives 2-assessing readiness 3-piloting use cases with a tiger team Step 4 is about empowering the broader team to leverage AI confidently. Boston Consulting Group (BCG) research and Gilbert’s Behavior Engineering Model show that high-impact AI adoption is 80% about people, 20% about tech. Here’s how to make that happen: 1️⃣ Environmental Supports: Build the Framework for Success -Clear Guidance: Define AI’s role in specific tasks. If a tool like Momentum.io automates data entry, outline how it frees up time for strategic activities. -Accessible Tools: Ensure AI tools are easy to use and well-integrated. For tools like ChatGPT create a prompt library so employees don’t have to start from scratch. -Recognition: Acknowledge team members who make measurable improvements with AI, like reducing response times or boosting engagement. Recognition fuels adoption. 2️⃣ Empower with Tiger Team Champions -Use Tiger/Pilot Team Champions: Leverage your pilot team members as champions who share workflows and real-world results. Their successes give others confidence and practical insights. -Role-Specific Training: Focus on high-impact skills for each role. Sales might use prompts for lead scoring, while support teams focus on customer inquiries. Keep it relevant and simple. -Match Tools to Skill Levels: For non-technical roles, choose tools with low-code interfaces or embedded automation. Keep adoption smooth by aligning with current abilities. 3️⃣ Continuous Feedback and Real-Time Learning -Pilot Insights: Apply findings from the pilot phase to refine processes and address any gaps. Updates based on tiger team feedback benefit the entire workforce. -Knowledge Hub: Create an evolving resource library with top prompts, troubleshooting guides, and FAQs. Let it grow as employees share tips and adjustments. -Peer Learning: Champions from the tiger team can host peer-led sessions to show AI’s real impact, making it more approachable. 4️⃣ Just in Time Enablement -On-Demand Help Channels: Offer immediate support options, like a Slack channel or help desk, to address issues as they arise. -Use AI to enable AI: Create customGPT that are task or job specific to lighten workload or learning brain load. Leverage NotebookLLM. -Troubleshooting Guide: Provide a quick-reference guide for common AI issues, empowering employees to solve small challenges independently. AI’s true power lies in your team’s ability to use it well. Step 4 is about support, practical training, and peer learning led by tiger team champions. By building confidence and competence, you’re creating an AI-enabled workforce ready to drive real impact. Step 5 coming next ;) Ps my next podcast guest, we talk about what happens when AI does a lot of what humans used to do… Stay tuned.

Becoming AI-native isn't about mastering prompts. It’s about upgrading how you lead. If your AI strategy is “train everyone to prompt better,” you’ll plateau fast. The leaders winning with AI aren’t the ones who write better instructions. They’re the ones who’ve redesigned how they think, decide, and manage teams. Human ingenuity + machine intelligence = exponential value. But only if you change the habits that got you here. Think of the shift as: Adopt → Design → Scale → Sustain. Here are 8 ways to make it real: 1/ 𝗔𝗱𝗼𝗽𝘁 𝗮𝗻 𝗔𝗜-𝗙𝗶𝗿𝘀𝘁 𝗠𝗶𝗻𝗱𝘀𝗲𝘁 Start asking: “If AI was foundational, how would we design this from scratch?” → Treat AI as a co-creator in strategy, not an afterthought → Ask AI daily to challenge assumptions and surface blind spots → Audit decisions weekly: Which ones were made without AI input? 2/ 𝗕𝘂𝗶𝗹𝗱 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹 𝗙𝗹𝘂𝗲𝗻𝗰𝘆 𝗧𝗵𝗿𝗼𝘂𝗴𝗵 𝗗𝗮𝗶𝗹𝘆 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 You can’t lead AI transformation if you’re not using AI yourself. → Use AI daily for decision briefs, planning, and risk analysis → Block short, consistent time for hands-on experimentation → Share personal wins and failures publicly with your team 3/ 𝗦𝗵𝗶𝗳𝘁 𝗳𝗿𝗼𝗺 𝗖𝗼𝗺𝗺𝗮𝗻𝗱𝗲𝗿 𝘁𝗼 𝗖𝗼𝗮𝗰𝗵 AI-native leadership isn’t top-down control. → Let AI prepare drafts and recommendations; humans decide → Focus leadership energy on judgment, priorities, and ethics → Coach hybrid human–AI teams instead of managing outputs 4/ 𝗖𝗿𝗲𝗮𝘁𝗲 𝗦𝗮𝗳𝗲𝘁𝘆 𝗳𝗼𝗿 𝗘𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 Fear quietly kills AI adoption. → Frame AI as augmentation, not replacement → Create low-risk sandboxes with clear boundaries → Reward learning and early failure, not just success 5/ 𝗥𝗲𝗯𝘂𝗶𝗹𝗱 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀, 𝗗𝗼𝗻'𝘁 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗢𝗹𝗱 𝗢𝗻𝗲𝘀 Automating a broken process scales dysfunction. → Redesign high-volume workflows from first principles → Build for autonomy and handoffs, not just assistance → Prototype one AI-native workflow before scaling 6/ 𝗕𝘂𝗶𝗹𝗱 𝗔𝗜-𝗡𝗮𝘁𝗶𝘃𝗲 𝗧𝗲𝗮𝗺𝘀 Talent strategy determines AI outcomes. → Hire for curiosity, systems thinking, and judgment → Tie advancement to measurable AI-driven impact → Form small, cross-functional squads around real problems 7/ 𝗢𝘄𝗻 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗹𝘆 AI governance is a leadership responsibility. → Set clear policies for data use and agentic systems → Require explainability and human oversight for key decisions → Review risks and controls on a regular cadence 8/ 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝗢𝘂𝘁𝗰𝗼𝗺𝗲𝘀, 𝗡𝗼𝘁 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻 Usage doesn’t equal value. → Measure time saved, revenue impact, and speed to execution → Replace vanity metrics with business outcomes → Make AI impact part of performance conversations Becoming AI-native doesn’t require a bigger innovation budget. It requires a different operating system. Teams using AI as a tool get faster. Teams building with AI as infrastructure get ahead.

Most companies still don’t know how AI is really being used. So we measured it. We analyzed how AI is adopted inside real teams. Not what vendors say. What people actually do. And we found 6 clear ways to boost adoption from the inside: 1. Share success stories. AI usage climbs faster when peers share wins and tips. Spotlight team leads who are finding real impact. 2. Show the data. Display org-wide metrics to track usage over time. Set clear goals and make progress visible. 3. Focus on key teams. Sales, HR, and Marketing trail in usage. These teams need the most support and see the fastest gains. 4. Start with managers. Manager usage drives team adoption by 75%. Set expectations, track usage, and build usage norms. 5. Build AI skills. Reskill programs help lagging teams catch up. Embed AI familiarity in onboarding and hiring. 6. Lower fear. Raise clarity. Publish approved tools and clear data rules. Emphasize that using AI is innovation, not cheating. The real secret? You don’t need a shiny new tool. You need visibility, consistency, and a plan. Early adopters don’t wait for mandates. They build momentum. And the teams that get it right will win the next era of work. What are you doing to increase AI adoption on your teams?

Great leaders do these 5 things. 𝗟𝗲𝗴𝗲𝗻𝗱𝗮𝗿𝘆 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 now do them with AI: Here’s how to turn timeless leadership into 𝗲𝘅𝗽𝗼𝗻𝗲𝗻𝘁𝗶𝗮𝗹 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲. I first learned these 5 practices while leading global transformation projects at Microsoft. Over the years, I learned how these timeless behaviors shaped high-performing teams— and transformed entire industries. Now with AI, they’re not just effective. 𝗧𝗵𝗲𝘆’𝗿𝗲 𝗲𝘅𝗽𝗼𝗻𝗲𝗻𝘁𝗶𝗮𝗹. Here’s how AI can empower the 𝟱 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 𝗼𝗳 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 from 𝘛𝘩𝘦 𝘓𝘦𝘢𝘥𝘦𝘳𝘴𝘩𝘪𝘱 𝘊𝘩𝘢𝘭𝘭𝘦𝘯𝘨𝘦: 1. 𝗠𝗼𝗱𝗲𝗹 𝘁𝗵𝗲 𝗪𝗮𝘆 𝘓𝘦𝘢𝘥 𝘣𝘺 𝘦𝘹𝘢𝘮𝘱𝘭𝘦—𝘤𝘰𝘯𝘴𝘪𝘴𝘵𝘦𝘯𝘵𝘭𝘺 𝘢𝘯𝘥 𝘤𝘭𝘦𝘢𝘳𝘭𝘺. • Use AI to 𝗿𝗲𝗳𝗹𝗲𝗰𝘁 𝗼𝗻 𝘆𝗼𝘂𝗿 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 𝗮𝗻𝗱 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝘀. • Run your values through AI to generate behavior examples and contradictions. • Use ChatGPT as your 𝗰𝗹𝗮𝗿𝗶𝘁𝘆 𝗺𝗶𝗿𝗿𝗼𝗿—"Am I living what I lead?"    2. 𝗜𝗻𝘀𝗽𝗶𝗿𝗲 𝗮 𝗦𝗵𝗮𝗿𝗲𝗱 𝗩𝗶𝘀𝗶𝗼𝗻 𝘚𝘦𝘦 𝘵𝘩𝘦 𝘧𝘶𝘵𝘶𝘳𝘦—𝘵𝘩𝘦𝘯 𝘦𝘯𝘭𝘪𝘴𝘵 𝘰𝘵𝘩𝘦𝘳𝘴 𝘪𝘯 𝘪𝘵. • Use AI to 𝗲𝘅𝗽𝗹𝗼𝗿𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝘀𝗰𝗲𝗻𝗮𝗿𝗶𝗼𝘀, map trends, and simulate possibilities. • Build compelling narratives with AI co-creation tools—videos, speeches, decks. • Prompt: “𝘞𝘳𝘪𝘵𝘦 𝘢 1-𝘮𝘪𝘯𝘶𝘵𝘦 𝘱𝘪𝘵𝘤𝘩 𝘵𝘩𝘢𝘵 𝘮𝘢𝘬𝘦𝘴 𝘮𝘺 𝘵𝘦𝘢𝘮 𝘦𝘹𝘤𝘪𝘵𝘦𝘥 𝘢𝘣𝘰𝘶𝘵 𝘰𝘶𝘳 𝘷𝘪𝘴𝘪𝘰𝘯.” 3. 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 𝘁𝗵𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 𝘌𝘹𝘱𝘦𝘳𝘪𝘮𝘦𝘯𝘵, 𝘵𝘢𝘬𝘦 𝘳𝘪𝘴𝘬𝘴, 𝘢𝘯𝘥 𝘭𝘦𝘢𝘳𝘯. • Use AI to generate 10X bolder ideas in minutes. • Debrief failures with AI: “𝘞𝘩𝘢𝘵 𝘥𝘪𝘥 𝘸𝘦 𝘭𝘦𝘢𝘳𝘯 𝘢𝘯𝘥 𝘩𝘰𝘸 𝘤𝘢𝘯 𝘸𝘦 𝘪𝘮𝘱𝘳𝘰𝘷𝘦?” • Use tools like Claude or ChatGPT to 𝘀𝘁𝗿𝗲𝘀𝘀 𝘁𝗲𝘀𝘁 your assumptions. • 4. 𝗘𝗻𝗮𝗯𝗹𝗲 𝗢𝘁𝗵𝗲𝗿𝘀 𝘁𝗼 𝗔𝗰𝘁 𝘉𝘶𝘪𝘭𝘥 𝘵𝘳𝘶𝘴𝘵 𝘢𝘯𝘥 𝘴𝘵𝘳𝘦𝘯𝘨𝘵𝘩𝘦𝘯 𝘰𝘵𝘩𝘦𝘳𝘴. • Use AI to create 𝘁𝗮𝗶𝗹𝗼𝗿𝗲𝗱 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗽𝗹𝗮𝗻𝘀 for each team member. • Translate complex strategies into personalized next steps. • Co-create action plans with your team—with AI as a neutral facilitator.    5. 𝗘𝗻𝗰𝗼𝘂𝗿𝗮𝗴𝗲 𝘁𝗵𝗲 𝗛𝗲𝗮𝗿𝘁 𝘙𝘦𝘤𝘰𝘨𝘯𝘪𝘻𝘦, 𝘤𝘦𝘭𝘦𝘣𝘳𝘢𝘵𝘦, 𝘢𝘯𝘥 𝘤𝘰𝘯𝘯𝘦𝘤𝘵. • Use AI to surface hidden wins across your org. • Prompt AI to write personalized celebration notes or thank-you messages. • Automate weekly wins roundup that fuels team spirit. 𝗔𝗜 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗿𝗲𝗽𝗹𝗮𝗰𝗲 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽. 𝗜𝘁 𝗮𝘂𝗴𝗺𝗲𝗻𝘁𝘀 𝘆𝗼𝘂𝗿 𝗵𝘂𝗺𝗮𝗻𝗶𝘁𝘆. The future of leadership is 𝘤𝘰-𝘪𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘤𝘦: human heart, machine augmented mind. 𝗪𝗵𝗶𝗰𝗵 𝗼𝗳 𝘁𝗵𝗲 𝟱 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 𝘄𝗶𝗹𝗹 𝗬𝗢𝗨 𝗮𝘂𝗴𝗺𝗲𝗻𝘁 𝘄𝗶𝘁𝗵 𝗔𝗜 𝘁𝗵𝗶𝘀 𝘄𝗲𝗲𝗸?

How can leaders transform their teams to be AI-first? It starts with mindset. An AI-first mindset means: Seeing AI as an opportunity, not a threat. Viewing AI as a tool to augment teams, not just automate tasks. Using AI to reimagine work, not just optimize work. As leaders, it’s on us to build this mindset within our teams. Here are 5 ways we do this at HubSpot: Use AI daily: Lead by example—trust grows when teams see leaders embrace AI themselves. I use it everyday and share very specific use cases with our company on how I use it. Now every leader is doing the same with their teams. The result is that we will have almost everyone in the company use AI daily by the end of year. Apply constraints: Give clear, focused challenges. We kept headcount flat in Support while growing the customer base by 20%+. Result - the team innovated with AI and over achieved the target. Smart constraints drive innovation. Establish tiger teams: Empower small, agile groups to experiment, innovate, and teach the organization. We have AI Tiger teams in every function - they share progress in Slack channels and there is so much energy with small groups experimenting and learning. Be a learn-it-all: Foster a culture of continuous learning. Share openly about successes and failures alike. We have dedicated 2 full days to learning and scaling with AI this quarter as a company - we have lined up great speakers, ways to experiment and gamified learning. Measure progress and share it: Measure which teams are completing learning modules, using AI everyday and share that openly. A little healthy competition goes a long way in driving AI-fluency. AI isn’t just a technology shift. It’s fundamentally reshaping how work gets done—and that requires shifting our mindset first. Leaders who embrace AI now will unlock creativity, performance, and impact. Are you building an AI-first mindset with your team? #Leadership #AI #Innovation #Mindset #FutureOfWork

Adopting AI tools is easy. Reimagining how we work with them is the real transformation. Across many organizations, teams are being asked to “adopt AI” without the time, training or clarity they need to feel confident. When that happens, progress becomes fragmented—some people race ahead, others hesitate, and morale drops under the weight of confusion. Real AI transformation requires more than deploying technology. It demands deeper shifts that help people work differently and unlock value: → Change management to guide teams through new ways of working → Skilling to empower every employee to thrive in an AI-powered environment → Process understanding to ensure AI augments what matters most → Technology that’s usable, ethical and aligned with business goals As this Forbes article shares, the organizations that succeed will be the ones that treat AI adoption as a human journey, not just a technical one. When teams feel equipped, supported and included in shaping the path forward, that’s when AI truly delivers. What support are you giving your teams to learn and experiment with AI? https://lnkd.in/g2pXBtjm