How to Drive AI Adoption

SMBs are facing a critical challenge: how to maximize efficiency, connectivity, and communication without massive resources. The answer? Strategic AI implementation. Many small business owners tell me they're intimidated by AI. But the truth is you don't need to overhaul your entire operation overnight. The most successful AI adoptions I've seen follow these six straightforward steps: 1️⃣ Identify Immediate Needs: Look for quick wins where AI can make an immediate impact. Customer response automation is often the perfect starting point because it delivers instant value while freeing your team for higher-value work. 2️⃣ Choose User-Friendly Tools: The best AI solutions integrate seamlessly with your existing technology stack. Don't force your team to learn entirely new systems. Find tools that enhance what you're already using. 3️⃣ Start Small, Scale Gradually: Begin with focused implementations in 1-2 key areas. This builds confidence, demonstrates value, and creates organizational momentum before expanding. 4️⃣ Measure and Adjust Continuously: Set clear KPIs from the start. Monitor performance religiously and be ready to refine your AI configurations to optimize results. 5️⃣ Invest in Team Education: The most overlooked success factor? Proper training. When your team understands both the "how" and "why" behind AI tools, adoption rates soar. 6️⃣ Look Beyond Automation: While efficiency gains are valuable, the real competitive advantage comes from AI-driven insights. Let the technology reveal patterns in your business processes and customer behaviors that inform better strategic decisions. The bottom line: AI adoption doesn't require disruption. The most effective approaches complement your existing workflows, enabling incremental improvements that compound over time. What's been your experience implementing AI in your business? I'd love to hear what's working (or not) for you in the comments below. #SmallBusiness #AI #BusinessStrategy #DigitalTransformation

Most companies aren’t failing at AI adoption because of the tech. They’re failing because employees are afraid to use it. Tools are rolling out fast. But usage? Still stuck in pilot mode. 52% of employees using AI are afraid to admit it. And when managers don’t model usage themselves, team adoption stalls. One thing is clear: AI adoption doesn’t just happen. You have to design for it. Here are 10 strategies that actually work: 1. Track adoption and set goals. Measure usage patterns and benchmark performance across teams. Make AI part of your performance conversations, like Shopify does. 2. Engage managers. If they use AI, their teams are 2 to 5x more likely to follow. Enable them, train them, and let them lead by example. 3. Normalize usage. More than half of AI users hide it. Reframe the narrative. AI isn’t cheating, it’s table stakes. 4. Clarify policies. Without clear guidelines, people freeze. Spell out what’s allowed and what’s not. 5. Promote early wins. A great prompt that saves hours? Share it. Celebrate it. Build momentum. 6. Share best practices. Run prompt-a-thons. Create internal libraries. Make experimentation part of the culture. 7. Deploy AI agents strategically. Use ONA to spot high-friction workflows. Insert agents where they’ll have the biggest impact. 8. Balance experimentation with safe tooling. Watch what tools employees are adopting organically. Then invest in enterprise-grade tools your teams already want. 9. Customize by role and domain. Sales, HR, engineering, each needs a tailored strategy. Design workflows that reflect the reality of each team. 10. Benchmark yourself. How does your AI usage compare to peers? Track maturity, share progress, and stay competitive. From our work at Worklytics, these are the tactics that move organizations from pilot mode to performance. You can find the full AI Adoption report in the comments below. Which of these 10 is your org already doing and what’s next on your roadmap? #FutureOfWork #PeopleAnalytics #AI #Leadership #WorkplaceInnovation

Every CEO I know is trying to figure out AI. But here’s the real challenge—adoption takes time. Just getting Microsoft Copilot or ChatGPT Premium isn’t the solution. The biggest struggle? Mindset. You can’t apply the same approach to everyone, and shifting the way people work takes effort. Recently, Akshata Alornekar (HR Manager) and Lidya Fernandes (Assistant Finance Manager)—who have a combined 30 years at SJI visiting NYC as part of our company policy to bring employees into different offices, helping them understand our culture and way of working. But what happened? → Every conversation turned into an AI hackathon. Spending time with us, we focused on showing them how @Shahera and I actively use AI in our daily work, not just talking about it, but demonstrating its impact. Seeing this firsthand shifted their perspective. “Before coming here, we were seeing AI from a 60 degree angle. But watching how you and the NYC team use it , it’s a full 180 degree shift!” This is why exposure and experience drive AI adoption. But many companies struggle because they treat AI like a tech upgrade. It’s not. AI adoption is a behavioral shift. How Companies Can Drive AI Adoption Effectively: → Lead from the Front AI is Not Just an IT Project C-level executives need to actively use AI in their own workflows. If leadership treats AI as an “IT tool” instead of a core business function, adoption will stall. Employees follow what leaders do, not just what they say. → Make AI a Part of Daily Workflows, Not Extra Work Employees resist AI when they see it as something “extra.” The best way to drive adoption? Embed AI into existing tasks automate reports, summarize meetings, or assist in decision-making. AI should feel like a time-saver, not another tool to manage. → Create AI Champions Inside the Organization Identify team members who are curious about AI and empower them to guide others. These AI champions can test new use cases, train colleagues, and help build momentum. AI adoption is easier when it spreads peer-to-peer, not just top-down. → Focus on Habit-Building, Not Just Training One-off AI workshops don’t work. AI adoption happens when employees use it consistently. Introduce small, daily challenges to get them comfortable just like Akshata and Lidya experienced in NYC. Seeing AI in action changed their perspective. → Repeat, Repeat, Repeat! AI adoption isn’t a one-time rollout—it’s a continuous process. Companies that embed AI into their culture, not just their technology, will be the ones that thrive. The companies that embrace AI culturally, not just technologically, will win. Are you leading AI adoption the right way? What’s been your biggest challenge? Let’s discuss.

With all the posts on "vibe-coding", "AI-prototyping", and "look at how I use Cursor as a PM" it can feel like you're behind. But most folks are just getting started. The people posting who appear to be experts? They only got started months ago ◡̈. Take it from my 63 year old father. He's a seasoned executive - WAY smarter than I am (he'll beat AI at virtually any math problem). We've been meeting regularly so I can teach him AI. This video is from our 1st session and it proved to me just how early we are on the AI adoption curve. I've learned several key lessons about AI adoption from my dad and from trying to spearhead adoption at work: 1️⃣ Change is really hard, even more so in enterprise organizations. There are two keys to combating change: 1) You have to show folks why/how AI makes their job better. The best way to do that is to find a champion in each org who can serve as an advocate and build use cases tailored to that orgs specific role. 2) Create programming to build the habit! Consider challenges, 30/60/90 day plans, and even incentives like leaderboards and gamification. 2️⃣ There's a lot of red tape for the more advanced AI usages. Connect GPT to company email? Lengthy IT/Security approval process. Zapier agent? Every connected app requires API access. The only way to make this less cumbersome is to get the entire leadership team to prioritize AI adoption, so that Legal and IT teams are bought in and aligned. 3️⃣ Start with what you can control. While you're waiting for those enterprise approvals, focus on the AI tools you already have access to. Use ChatGPT, Gemini, or Claude for critiques on your first drafts, analyzing competitor messaging, and just plain ideating (use voice mode!). Download spreadsheets / CSVs and then upload them and ask for insights. These wins build your confidence AND give you concrete examples to share when you're ready to propose bigger changes. 4️⃣ Document what works (and what doesn't). Keep a running list of prompts that actually save you time e.g. the ones you find yourself using again and again. If you aren't happy with the output, tweak the prompt, not the output. These prompts become your internal products. Once you nail a prompt for a specific need save it and make it easily reusable via a custom GPT, Gemini Gem, or project. Share these "AI recipes" with your team. You'll quickly become the person others turn to for AI advice. 5️⃣ [More advanced] Think about your company's tribal knowledge. What are the areas where something is blocked or unanswered until a very specific role or person takes a look at it? For ex: RFP gap analysis, FAQs that come up about your product (is this supported or not?). These can be streamlined via a project, custom GPT, etc, freeing up that person for higher order thinking. The gap between AI beginners and experts is smaller than it appears. Most of us are just figuring it out as we go! Start where you are, with what you have access to, and build from there ◡̈.

I'm thrilled to share The Human Side of #AI: A Leader's Guide to Successful #AIAdoption - our first Prosci Catalyst Report (a 10-page, punchy "research derivative product" designed to delivery engaging and critical insights in a digestible and tasty package). This first Catalyst Report is derived from findings in our recent Enterprise AI Adoption research highlighting four takeaways: 1. Leadership and Cultural Foundations: The Heart of Success 📊 Research Insight: Organizations with strong AI leadership support score +1.65 on a -2 to +2 scale, compared to -1.50 in struggling organizations. 🔑 What this means: AI adoption isn’t just about deploying tools - it’s about leaders modeling adoption and fostering an AI-ready culture. Without visible, engaged leadership, AI remains a side project rather than a strategic transformation. ✅ Operationalize it: Equip leaders with the skills and language to champion AI, define a compelling AI vision, and (perhaps most importantly) use the tools themselves. 2. Balanced Strategic Control: Ambitious Yet Managed 📊 Research Insight: Successful AI implementations balance strong centralized control (+0.82) with bold transformation goals (+1.01). Struggling organizations hesitate, favoring small, incremental steps (-1.86). 🔑 What this means: Overly cautious AI strategies create friction. Organizations that set clear governance structures while embracing big-picture transformation make the most progress. ✅ Operationalize it: Define who owns AI strategy, create a decision framework for AI investments, and ensure AI ambitions extend beyond short-term efficiency gains. 3. External Alignment: Market-Aware Implementation 📊 Research Insight: AI leaders stay ahead by aligning their strategy with industry influence (+1.29) and competitive awareness (+1.11). Struggling organizations report little external orientation (-0.14, -1.17). 🔑 What this means: AI success isn’t just about internal readiness - it’s about understanding the forces shaping AI adoption across industries, competitors, and regulations. ✅ Operationalize it: Build an AI sensing function - regularly track market trends, competitive moves, and regulatory shifts to guide AI strategy. 4. The Critical Role of Change Management 📊 Research Insight: While only 17% of executives cite technical challenges, 56% say workforce capability and organizational change are the biggest barriers to AI adoption. 🔑 What this means: AI adoption depends on human readiness. Without structured change support, even the most powerful AI tools will sit unused. ✅ Operationalize it: Invest in AI change enablement - train teams in AI fluency, upskill employees, and integrate AI adoption into enterprise change frameworks. Big shout out to Scott Anderson, PhD from research and Jasmine Nicol from marketing for the collaboration on the catalyst report product. Enjoy! Share! And reach out to Prosci for AI Adoption research, support, and capability.

I love it when AI works out, because when it does - it’s magic. Here is my personal 5-step readiness checklist so you succeed with it. 𝗦𝘁𝗲𝗽 𝟭: 𝗔𝘂𝗱𝗶𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 Before any AI conversation, ask: "Is our data clean, accessible, and flowing properly?" - Map your current data sources and quality. - Identify gaps between systems. - Ensure data governance policies are in place 𝗦𝘁𝗲𝗽 𝟮: 𝗔𝘀𝘀𝗲𝘀𝘀 𝗬𝗼𝘂𝗿 𝗧𝗲𝗮𝗺'𝘀 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗖𝗼𝗺𝗳𝗼𝗿𝘁 𝗭𝗼𝗻𝗲 Meet your people where they are, not where you want them to be. - Evaluate current tool proficiency (Are they Excel natives? Advanced analytics users?) - Identify the skills gap between current state and AI requirements. - Plan bridge training programs. 𝗦𝘁𝗲𝗽 𝟯: 𝗕𝘂𝗶𝗹𝗱 𝗔𝗜 𝗟𝗶𝘁𝗲𝗿𝗮𝗰𝘆 𝗔𝗰𝗿𝗼𝘀𝘀 𝗬𝗼𝘂𝗿 𝗢𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻 Create understanding before implementation. - Run AI awareness sessions for leadership and end-users. - Define AI terminology and use cases relevant to your industry. - Address concerns and misconceptions upfront. 𝗦𝘁𝗲𝗽 𝟰: 𝗦𝘁𝗮𝗿𝘁 𝗦𝗺𝗮𝗹𝗹 𝘄𝗶𝘁𝗵 𝗣𝗶𝗹𝗼𝘁 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝘀 Test the waters before diving in. - Choose one high-impact, low-risk use case. - Select a team that's excited about innovation. - Measure adoption rates, not just performance metrics 𝗦𝘁𝗲𝗽 𝟱: 𝗘𝘀𝘁𝗮𝗯𝗹𝗶𝘀𝗵 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗮𝗻𝗱 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗟𝗼𝗼𝗽𝘀 Define what winning looks like. - Set clear ROI expectations. - Create channels for user feedback and iteration. - Plan for scaling successful pilots Organizations that complete this readiness checklist see 3x higher adoption rates and significantly better long-term ROI. AI implementation isn't a sprint, it's a strategic marathon. Where is your organization in this readiness journey? What step are you focusing on right now?

Winning AI Adoption—How Smart Leaders Make It Stick In my last post, I called out the biggest roadblocks to AI adoption: fear, the status quo stranglehold, and lack of quick wins. Now, let’s talk about what actually works—how the best leaders are getting AI adoption right. Here’s what I’ve seen move the needle: 1. Make AI Familiar Before You Make It Big One exec I worked with introduced AI without calling it AI. Instead, he embedded AI-powered tools into existing workflows—automating scheduling, summarizing reports—before making a major push. By the time AI became a formal strategy, employees were already using it. 🔹 Key takeaway: Small, seamless introductions reduce resistance. Make AI invisible before making it strategic. 2. Use a “Coalition of the Willing” AI adoption isn’t a one-leader show. You need a groundswell. Another leader I coached built a cross-functional AI task force—hand-picking open-minded employees from various teams. These early adopters became internal influencers, pulling skeptics along and proving AI’s value in real time. 🔹 Key takeaway: AI champions make AI contagious. Build a coalition, not just a case. 3. Tie AI to Personal Wins, Not Just Business Goals People don’t embrace change because it’s good for the company. They embrace it when it makes their own work easier. One leader I advised stopped pitching AI in broad business terms. Instead, he tailored the narrative: ✅ For sales? AI means faster deal insights. ✅ For finance? AI means cleaner forecasting. ✅ For HR? AI means better hiring matches. When employees saw how AI could make their specific job easier, adoption skyrocketed. 🔹 Key takeaway: Show how AI works for them—not just for the bottom line. The Leaders Who Win With AI Don’t Just Roll It Out—They Make It Irresistible. AI adoption isn’t about tech implementation. It’s about human behavior. The smartest leaders don’t just introduce AI—they shape the conditions for people to run with it. So, the real question isn’t “Is AI ready for your company?” It’s: Is your company ready for AI? Would love to hear from those leading AI adoption—what’s working for you?

The secret to 10x impact from AI is changing *what* work you do, not only how your team does that work. See AI as more than a “productivity tool.” To succeed and become executives, leaders must think of AI differently than coders, designers, PMs, and other ICs. Here is how to *lead* with AI: It can be used to do things faster or more easily, but that isn’t where the real opportunity is. The real opportunity for leaders to grow their careers using AI is by using it to create net new value for the company: new products, better margins, or systems that fundamentally reduce cost or complexity. Creating new value is what will win you new opportunities, responsibilities, and eventually, a promotion. Using AI to do this requires knowledge and experience with AI tools and applications, a clear strategy, and the leadership skill to guide the process. Here’s how I would go about gaining that knowledge, creating the strategy, and leading the change in my organization: First, I’d deeply engage with AI. I would set aside time to personally test tools, follow AI experts, attend workshops, and build a mental model of where AI can create real leverage in my organization. I would also ask my team where they are currently using AI and what sort of results they are seeing. Second, I’d craft experiments. The leaders who will stand out will ask: what can we do now that we couldn’t do before? What cost structures can we eliminate? What customer problems can we solve in a new way? I would ask these questions and create hypotheses based on what I learned playing with tools and from others. I would then test these hypotheses with funded experiments that have meaningful but manageable impact. Third, I’d lead AI adoption by shaping culture. I'd ensure clarity on the “why” behind our AI efforts and I’d create a culture where experimentation is encouraged and failure is safe. I’d set expectations that we “use AI,” identify champions, and work with those who are resistant so that they feel supported in the change but also understand that it is a new expectation and not a request. The challenge with leading AI today is that it is already in your organization. Some are using it, others are opposing it and fearing it, everyone is aware of it. If you don’t lead your team through its use, you’ll lose control of it. Teams will adopt it unevenly, causing friction and confusion. On the flip side, if you lead well, it has the ability to 10x your impact and skyrocket your career. AI is not a tech problem for most leaders. It’s a change management problem. If you are a strategic, curious, and thoughtful leader you will be able to manage this change for the benefit of your team, your business, and your career. I write more about this in today’s newsletter for paid subscribers. I designed a 30-day AI Leadership Sprint and a number of other resources you can use to lead AI adoption in your org. Read the newsletter here: https://buff.ly/QMlF266 What's missing?

Enterprise AI adoption is slow because we treat AI like learning a skill instead of changing a behavior. Three easy AI behavioral changes, and why each works: 1.    INVITE CHATGPT INTO EVERY CONVERSATION Your people already have the core skill needed - conversation. The challenge isn't learning better prompts - it's breaking our "Google Search Brain" habit of instinctively treating AI like a search engine. Learning prompts is like learning the features on your treadmill – yeah, it’ll help, but not nearly as much as actually getting on the freakin’ treadmill. WHAT TO DO: • Keep ChatGPT or other LLM open in in a browser every team meeting • Treat it like another teammate, like somebody on Zoom • Insist on having it participate in brainstorming, note-taking, researching, etc. WHY IT WORKS: When ChatGPT is an open window on a browser, as if it’s somebody on Zoom, it’s easier to engage it like a teammate. That gives you the best results. 2. TRIGGER YOUR BRAIN WITH VISUAL CUES I have a "Use ChatGPT" Post-it on my desk. Even as someone who uses AI tools constantly (ChatGPT, Claude, Gemini), I need the reminder. WHAT TO DO: • Put up physical reminders where you work • Make AI visible in your workspace • Break the "out of sight, out of mind" pattern WHY IT WORKS: Our brains respond powerfully to visual cues - they help interrupt old patterns and trigger new behaviors. 3. FOCUS ON YOUR TASKS, NOT WHAT AI CAN DO Nobody wakes up thinking "how will I use the internet today?" To drive adoption, the same *must* be true for AI. WHAT TO DO: • List your actual work tasks, from major projects to daily activities • Look for ways AI can augment each one • Stop thinking about "AI use cases" - think about YOUR use cases WHY IT WORKS: This shifts focus from AI as a tool to AI as an augmentation of everything you do in your existing workflow. BONUS: Stop assuming that people who are good at using ChatGPT can teach others. It’s not like teaching somebody how to play Monopoly. It’s like trying to inspire them to do morning yoga while also showing them the best technique for morning yoga. That’s why I do what I do. I run workshops for organizations to drive adoption through behavioral change, and we have a digital course, Generative AI for Professionals, tailored for enterprise. It changes critical behaviors. It works. Let me know if this is ever of interest. Don't teach a new skill. Change an old behavior.

𝗜'𝗺 𝗵𝗲𝗮𝗿𝗶𝗻𝗴 𝘀𝘁𝗼𝗿𝗶𝗲𝘀 𝗮𝗯𝗼𝘂𝘁 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗼𝗽𝗶𝗹𝗼𝘁 𝗳𝗮𝗶𝗹𝘂𝗿𝗲𝘀. Employees are NOT using it - they don't see the value or don't know how to. And I know exactly why... All fancy AI licenses are worthless because you are: 🚫 Throwing licenses at employees 🚫 Forcing top-down adoption 🚫 Assuming people will "figure it out" 🚫 Focusing only on technology The truth? Having AI isn't enough; effective adoption is key. Here's what successful companies do differently (5Es): ✅ Educate: Show AI capabilities w/ use cases & benefits ✅ Empower: Provide proper training and support ✅ Enable: Create space for experimentation ✅ Engage: Address concerns openly ✅ Execute: Implement clear adoption strategies Here's a 3-step framework that transformed our AI/RPA Automation adoption rates 👇 Start with WHY - Connect AI/Automation to business objectives - Show Organizational & personal benefits - Address replacement fears head-on Enable through HOW - Structured training programs - Hands-on workshops - Real-world use cases Support with WHAT - Clear implementation roadmap - Regular feedback sessions - Celebration of small wins Remember: Having AI isn't enough. Success lies in your people adopting it. What do you think? ---- 🎯 Follow for Agentic AI, Gen AI & RPA trends: https://lnkd.in/gFwv7QiX #AI #innovation #technology #automation