How to Reduce Barriers to Entry in AI

We hear all about the amazing progress of AI BUT, enterprises are still struggling with AI deployments - latest stats say 78% of AI deployments get stall or canceled - sounds like we’re still buying tools and expect transformation. But those that have succeeded? They don’t just license AI, they redesign work around them. Because adoption isn’t about the tool. It’s about the people who use it. Let’s break this down: 😖 Buying AI tools just adds to your tech stack. Nothing more, nothing less! Stat you can’t ignore: 81% of enterprise AI tools go unused after purchase. (Source: IBM, 2024) 🙌🏼 But adoption, adoption requires new workflows, new roles, and new routines - this means redesigning org charts, updating SOPs, and rethinking “a day in the life.” Why? Because AI should empower decisions—not just automate tasks. It should amplify human strengths—not quietly sideline them. That’s where the 65/35 Rule comes in! 65% of a successful AI deployment is redesigning business processes and preparing the workforce. Only 35% is tools and infrastructure. But most companies still do the reverse. They invest 90% in tech and 10% in training… and wonder why they’re stuck in “perpetual POC purgatory” (my term for things that never make production. It’s like buying a Formula 1 car and expecting your team to win races—without ever learning to drive. Here’s the better way: Step 1: Start with the “day in the life” Map how work actually gets done today. Not hypothetically. Not aspirationally. Just reality. Step 2: Identify friction points Where do delays, errors, or bad decisions happen? Step 3: Redesign with intent Now—and only now—do you introduce AI. Not to replace the human. But to support and strengthen them. Recommendation #1: Design AI solutions with your workforce, not just for them. Co-create roles, rituals, and reviews. Recommendation #2: Adopt the 65/35 Rule as your north star. If your AI strategy doesn’t spend more time on people and process than tools and tech… it’s not ready. ⸻ AI doesn’t fail because it’s flawed. It fails because the org using it is unprepared. #AI #FutureOfWork #DigitalTransformation #Leadership #OrgDesign #HumanInTheLoop #AIAdoption #DataDrivenDecisions #Innovation >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> Sol Rashidi was the 1st “Chief AI Officer” for Enterprise (appointed back in 2016). 10 patents. Best-Selling Author of “Your AI Survival Guide”. FORBES “AI Maverick & Visionary of the 21st Century”. 3x TEDx Speaker

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

🎯 The CIO's Organizational Playbook for the AI Era... I recently spoke with a CIO friend about how IT teams are changing. Our discussion made me think about what sets apart IT teams that succeed with AI from those that don’t. I looked over my research and reviewed my interviews with other leaders. This information is too valuable not to share: ✓ Build AI-Ready Capabilities 🟢 Establish continuous learning programs focused on practical AI applications 🟢 Implement cross-functional training to bridge technical/business gaps 🟢 Prioritize hands-on AI workshops over theoretical certifications ✓ Master AI Risk Management 🟢 Develop processes to identify and mitigate technical failures early 🟢 Create a strategic AI roadmap with clear risk contingency protocols 🟢 Align all AI initiatives with broader business objectives ✓ Drive Stakeholder Engagement 🟢 Build a cross-functional AI coalition (executives, HR, business units) 🟢 Communicate AI initiatives with transparency to reduce resistance 🟢 Document tangible benefits to secure continued buy-in ✓ Implement with Agility 🟢 Replace waterfall approaches with iterative AI development 🟢 Focus on quick prototyping and real-world testing 🟢 Ensure infrastructure scalability supports AI growth ✓ Lead with AI Ethics 🟢 Train teams on bias identification and mitigation techniques 🟢 Establish clear governance frameworks with accountability 🟢 Make responsible AI deployment non-negotiable ✓ Transform Your Talent Strategy 🟢 Enhance IT roles to integrate AI responsibilities 🟢 Create peer mentoring programs pairing AI experts with domain specialists 🟢 Cultivate an AI-positive culture through early wins ✓ Measure What Matters 🟢 Set specific AI KPIs that link directly to business outcomes 🟢 Implement continuous feedback loops for ongoing refinement 🟢 Track both technical metrics and organizational adoption rates The organizations mastering these elements aren't just surviving the AI transition—they're thriving because of it. #digitaltransformation #changemanagement #leadership #CIO

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?

𝗬𝗼𝘂𝗿 𝗔𝗜 𝗶𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝘃𝗲𝘀 𝗮𝗿𝗲 𝗳𝗮𝗶𝗹𝗶𝗻𝗴. 𝗔𝗻𝗱 𝗶𝘁'𝘀 𝗻𝗼𝘁 𝗯𝗲𝗰𝗮𝘂𝘀𝗲 𝗼𝗳 𝘆𝗼𝘂𝗿 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆. 70-85% of AI projects fail to deliver value. But here's the thing: → Your algorithms work fine → Your data is clean   → Your APIs connect perfectly So why are you still stuck? 𝗕𝗲𝗰𝗮𝘂𝘀𝗲 𝘆𝗼𝘂'𝗿𝗲 𝘁𝗿𝘆𝗶𝗻𝗴 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 𝗮 𝗽𝗲𝗼𝗽𝗹𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝘄𝗶𝘁𝗵 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆. The real blocker isn't your tech stack. It's your culture. 𝗧𝗵𝗲 3 𝘀𝗶𝗹𝗲𝗻𝘁 𝗸𝗶𝗹𝗹𝗲𝗿𝘀 𝗼𝗳 𝗔𝗜 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻: 𝗧𝗵𝗲 𝗘𝘅𝗶𝘀𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝗧𝗵𝗿𝗲𝗮𝘁 "If AI can do my job, what happens to me?" (Employees resist what they can't control) 𝗧𝗵𝗲 𝗠𝗶𝗱𝗱𝗹𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗿 𝗦𝗾𝘂𝗲𝗲𝘇𝗲 You're asking them to implement tech that threatens their role (While still judging them by old metrics) 𝗧𝗵𝗲 𝗜𝗻𝗰𝗲𝗻𝘁𝗶𝘃𝗲 𝗠𝗶𝘀𝗺𝗮𝘁𝗰𝗵 Your AI recommends preventative shutdowns Your managers get rewarded for uptime (Guess which one wins?) 𝗪𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘄𝗼𝗿𝗸𝘀: • Elevate people, don't eliminate them • Create safe-to-fail zones for experimentation   • Put domain experts in control of AI implementation • Align incentives with AI-enhanced productivity • Address career anxieties with concrete transition plans 𝗧𝗵𝗲 𝗯𝗼𝘁𝘁𝗼𝗺 𝗹𝗶𝗻𝗲: - Technical advantages last weeks. - Cultural advantages last years. Your competitors can copy your algorithms. They can't copy your culture. 𝗪𝗵𝗮𝘁'𝘀 𝗵𝗮𝗿𝗱𝗲𝗿 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Building a chatbot or getting people to actually use it? Your answer says it all. I just published a deep dive on this in The AI Journal: "The Hidden Barrier to AI Success: Organizational Culture" It breaks down exactly how to build a culture that makes AI adoption inevitable (not just possible). 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗮𝗿𝘁𝗶𝗰𝗹𝗲→ 𝗵𝘁𝘁𝗽𝘀://𝗮𝗶𝗷𝗼𝘂𝗿𝗻.𝗰𝗼𝗺/𝘁𝗵𝗲-𝗵𝗶𝗱𝗱𝗲𝗻-𝗯𝗮𝗿𝗿𝗶𝗲𝗿-𝘁𝗼-𝗮𝗶-𝘀𝘂𝗰𝗰𝗲𝘀𝘀-𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝗮𝗹-𝗰𝘂𝗹𝘁𝘂𝗿𝗲/ Want more insights on the human side of AI transformation? 🔔 𝗙𝗼𝗹𝗹𝗼𝘄 𝗺𝗲 for weekly posts on AI + organizational psychology 📧 Join other informed leaders getting my "AI + Human Edge" newsletter for frameworks like this 𝘞𝘩𝘢𝘵'𝘴 𝘣𝘦𝘦𝘯 𝘺𝘰𝘶𝘳 𝘣𝘪𝘨𝘨𝘦𝘴𝘵 𝘣𝘢𝘳𝘳𝘪𝘦𝘳 𝘵𝘰 𝘈𝘐 𝘢𝘥𝘰𝘱𝘵𝘪𝘰𝘯? 𝘛𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺 𝘰𝘳 𝘱𝘦𝘰𝘱𝘭𝘦? 𝘋𝘳𝘰𝘱 𝘢 𝘤𝘰𝘮𝘮𝘦𝘯𝘵 𝘣𝘦𝘭𝘰𝘸 👇

Generative AI will transform work. But 52% of organizations aren’t ready. (Source: Harvard Business Review Analytic Services, 2024) I dug into the research. Here are the 7 biggest barriers stopping AI adoption and how to fix them. 1️⃣ Fear of Risks → Set clear rules for safe AI use + keep humans in the loop. 2️⃣ No Clear Plan → Start small → pilot → scale with feedback loops. 3️⃣ No Rules for Employees → Write simple “dos and don’ts.” Train people. Update often. 4️⃣ Skills Gap → Upskill staff, both AI fluency + change management. 5️⃣ Weak Data Foundations → Clean, connect, and secure data before scaling. 6️⃣ Unclear Business Value → Track early wins (time saved, costs cut). Share results widely. 7️⃣ Employee Pushback → Be transparent. Show how AI supports work instead of replacing it. Bottom line: AI isn’t just a technology shift. It’s a change management challenge. 👉 Swipe through the carousel for the full breakdown. 💾 Save this post for reference. 🔁 Repost to help others get AI-ready. 👤 Follow Gabriel Millien for more insights on AI, transformation, and leading change.

One in three companies are planning to invest at least $25m in AI this year, but only a quarter are seeing ROI so far. Why? I recently sat down with Megan Poinski at Forbes to discuss Boston Consulting Group (BCG)'s AI Radar reporting, our findings, and my POV.   Key takeaways below for those in a hurry. ;-)   1. Most of the companies have a data science team, a data engineering team, a center of excellence for automation, and an IT team; yet they’re not unlocking the value for three reasons:   a. For many execs, the technologies that exist today weren't around during their school years 20 years ago. As silly as it is, but there was no iPhone and for sure no AI at scale deployed at people’s fingertips.   b. It's not in the DNA of a lot of teams to rethink the processes around AI technologies, so the muscle has never really been built. This needs to be addressed and fast...   c. A lot of companies have got used to 2-3% continuous improvement on an annual basis on efficiency and productivity. Now 20-50% is expected and required to drive big changes. 2. The 10-20-70 approach to AI deployment is crucial. Building new and refining existing algorithms is 10% of the effort, 20% is making sure the right data is in the right place at the right time and that underlying infrastructure is right. And 70% of the effort goes into rethinking and then changing the workflows. 3. The most successful companies approach AI and tech with a clear focus. Instead of getting stuck on finer details, they zero in on friction points and how to create an edge. They prioritize fewer, higher-impact use cases, treating them as long-term workflow transformations rather than short-term pilots. Concentrating on core business processes is where the most value lies in moving quickly to redesign workflows end-to-end and align incentives to drive real change.   4. The biggest barrier to AI adoption isn’t incompetence; it’s organizational silos and no clear mandate to drive change and own outcomes. Too often, data science teams build AI tools in isolation, without the influence to make an impact. When the tools reach the front lines, they go unused because business incentives haven’t changed. Successful companies break this cycle by embedding business leaders, data scientists, and tech teams into cross-functional squads with the authority to rethink workflows and incentives. They create regular forums for collaboration, make progress visible to leadership, and ensure AI adoption is actively managed not just expected to happen.

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.