How to Upskill Your Workforce for AI

Work is changing faster than your org chart—and that’s not a prediction; it’s what I’ve witnessed doing AI-based deployments for 15+ years across Fortune 100's. Did you know that by 2030, AI is expected to automate 45% of current work activities? That sounds terrifying—until you realize that nearly every role I’ve led has changed completely every 2–3 years anyway 🤯 . 🛍️ Let me take you inside a retailer you know. They adopted AI to optimize their supply chain: predictive restocking, dynamic pricing, and warehouse robotics. Yes, automation changed the roles - but it didn’t eliminate them! 💡 The planners became simulation analysts. 💡 The merchandisers became AI auditors. 💡 And those freed from manual grunt work? They started tackling the backlog of work that had been pilin gup. AI didn’t reduce the workforce — it redefined it, and with redefinition comes opportunity – if we choose to take it! (topic of my 3rd #TEDx talk, releasing in May) Here’s the funny, slightly tragic truth: One executive told me they were “fully embracing AI.” When I asked how, he proudly said: “We bought 200 ChatGPT licenses.” That’s like preparing for a tsunami with a kiddie pool. 🤯 The companies winning in this next era aren’t just using AI — they’re training their people to thrive with it. Operative phrase: “training their people” So here’s how to prepare your workforce for what’s next: 🚀 Assess the now. Map roles and skills most likely to be disrupted or augmented. 🚀 Invest in reskilling. Don’t wait for the job to vanish. Train ahead of the curve. 🚀 Foster a learning culture. Create space (and incentives!) to experiment, fail, and evolve. Use AI responsibly. Don’t just optimize. Humanize. Ethics are part of your product now. One last thought: We’re not competing with AI. We’re competing with people who know how to use AI better than us. What steps are you taking to prepare your team? Share below. #FutureOfWork #AI #Leadership #DigitalTransformation #WorkplaceInnovation #SkillDevelopment #EthicalAI #SolRashidi #TEDx

Every customer and government leader I meet is asking, “How can we make AI a force for good for our people, and not a threat?” 92% of jobs are expected to undergo some level of transformation due to advancements in AI. The work begins with identifying and enabling the new skills and training needed for AI preparedness. That’s why I’m honored to share the insights from the AI-Enabled ICT Workforce Consortium's inaugural report, “The Transformational Opportunity of AI on ICT Jobs.” This report examines the impact of AI on 47 ICT job roles and offers tailored training recommendations. It's a unique guide to the skills needed for the AI future, with recommendations that couldn't be clearer, timelier, or more urgent. Here are some of the top takeaways: - 92% of ICT jobs will undergo high or moderate transformation due to AI. - 40% of mid-level and 37% of entry-level ICT positions will see high levels of transformation. - Skills like AI ethics, responsible AI, prompt engineering, and AI literacy will become crucial. - Foundational skills such as AI literacy and data analytics are essential across all ICT roles. Read the full report here: https://lnkd.in/gWfPc8WT The risks associated with an under-skilled, unprepared workforce are global in scale, ranging from economic wage gaps to trade imbalances, technological stagnation, social and ethical issues, and national security threats. This creates a pressing need for a coordinated effort to reskill and upskill employees around the world. By investing in a long-term roadmap for an inclusive and skilled workforce, we can help all populations participate and thrive in the era of AI. Led by Cisco and joined by industry giants like Accenture, Eightfold, Google, IBM, Indeed, Intel Corporation, Microsoft, and SAP the Consortium will train and upskill 95 million people over the next 10 years through their individual organizations' commitments.

Most companies I speak to are quietly anxious about AI. Not because they don’t know what AI is. But because they don’t know how their teams are actually using it. A few people are experimenting. A few are secretly very good. Most are stuck copying prompts from instagram and hoping it helps. Leadership thinks, “We’ve rolled out ChatGPT access, that should be enough.” It isn’t. The real gap is not tools. It’s workforce readiness. Who in your team: >> Knows how to use AI beyond writing emails? >> Can redesign their own workflows using AI? >> Is confident enough to rely on AI for decisions, research, and planning? Most companies don’t have answers to this. They only find out when execution slows down or competitors move faster. This is why “AI upskilling” cannot be a one-day workshop or a generic course. It needs: >> Benchmarking, so you know where your workforce actually stands >> Role-based upskilling, not one-size-fits-all sessions >> Workflow redesign, so AI shows up inside real work >> Ongoing support, so adoption doesn’t drop after excitement fades If your team feels overwhelmed, confused, or uneven in AI usage, that’s normal. What’s risky is ignoring it. We’ve been helping leadership teams and workforces move from AI curiosity to AI-powered execution. If this is something you’re thinking about for your company, lets talk!

Struggling with Skills Gaps? It's Time to Transform Your Strategy. According to EY, nearly two-thirds (62%) of companies are struggling to fully leverage AI due to gaps between technology and talent. This challenge spans industries, threatening to leave many organizations behind. Companies face two key types of skills gaps: scaling up existing capabilities and sourcing entirely new ones. For instance, while many businesses have machine learning engineers, few possess the advanced skills required to implement retrieval-augmented generation (RAG) systems or knowledge graphs. So, how can you close these critical gaps? Here are four strategies to get started: 1️⃣ . Upskill Your Workforce for Future Needs It’s not just about addressing today’s gaps but also preparing your team for future roles and skills while making your organization agile enough to pivot through future disruptions. Investing in skills like prompt engineering, AI model integration, and collaborating with AI agents will be essential for long-term success. 2️⃣ . Leverage AI to Boost Efficiency and Job Satisfaction AI tools like Copilot can improve coding speed by 55%, freeing developers to focus on more complex, fulfilling work. This helps alleviate skill shortages while boosting employee satisfaction by automating repetitive tasks and fostering meaningful engagement. 3️⃣ . Close Gaps in Data and Infrastructure Whether you develop in-house capabilities or partner with external AI providers, preparing proprietary data and sourcing the right infrastructure is crucial for effective AI integration. Addressing these foundational elements is key to long-term AI success. 4️⃣ . Build Buy-In by Addressing Employee Concerns AI adoption isn’t just about tech—it’s about people. One of the biggest challenges is earning employee buy-in. Leaders need to emphasize that AI isn’t here to take jobs, but to empower employees. Refactoring roles to collaborate with AI and creating new, AI-enhanced positions provide growth opportunities and help retain top talent. ⏳ The time to act is now. AI is reshaping tasks and roles, and businesses that fail to address these gaps risk being left behind. By upskilling your workforce, modernizing your infrastructure, and fostering a culture of acceptance, you can bridge the talent and technology gaps and unlock the full potential of AI. If this resonates with you, let’s connect. I’d love to hear where you are in your AI journey and explore how I can help. #futureofwork #digitaltransformation #aiandhumans #skillsgap

A 12-week AI upskilling roadmap helped Amazon fill 40% of job openings internally (but most companies ignore it). Everyone panics about the AI skills crisis. The World Economic Forum data tells a different story. Skills obsolescence dropped from 57% during the pandemic to 39% projected for 2025 to 2030. The crisis is no longer accelerating. It is becoming solvable. Amazon demonstrated what a structured approach can achieve through a $1.2 billion upskilling system that delivered measurable outcomes: → 700,000 employees retrained → Apprenticeship graduates earn $21,500 more annually → 40% of internal job openings filled by reskilled employees The models that deliver results are surprisingly simple. 📌 Weeks 1 to 4: Build AI literacy. Focus on prompt engineering basics, master three to five role-specific AI tools, and complete one micro-certification. 📌 Weeks 5 to 8: Apply skills at work. Automate two to three tasks, track time saved, document quality improvements, and share learnings. 📌 Weeks 9 to 12: Build proof. Create one portfolio project, quantify impact, and position yourself for AI-adjacent roles. Technical skills now last 12 to 18 months, while digital skills decay in three. A six-month delay reduces your adaptation window by one-third. This is why the workforce is splitting. Around 48% get redeployed or upskilled. Another 11% are left behind despite employer commitments. Start now! Audit yourself against the top WEF skills such as AI, big data, cybersecurity, critical thinking, and adaptability. A score of zero to three indicates high risk. Select one high-value skill for the next 90 days and choose certifications with proven wage-premium outcomes. What is the one skill you are committed to building?

Most companies wait until they have an urgent problem before addressing workforce capability. But the ones building competitive advantage are investing in readiness before the gap becomes a crisis. Here are four areas where organizations need to focus: 𝟭. 𝗥𝗲𝘀𝗸𝗶𝗹𝗹𝗶𝗻𝗴 𝗳𝗼𝗿 𝗿𝗼𝗹𝗲𝘀 𝘁𝗵𝗮𝘁 𝗱𝗶𝗱𝗻'𝘁 𝗲𝘅𝗶𝘀𝘁 𝗳𝗶𝘃𝗲 𝘆𝗲𝗮𝗿𝘀 𝗮𝗴𝗼 Automation specialists, data scientists, and AI integration roles require new training pathways. Companies that build apprenticeship programs and internal development tracks get ahead of skills bottlenecks before they slow growth. 𝟮. 𝗣𝗿𝗲𝗽𝗮𝗿𝗶𝗻𝗴 𝘁𝗲𝗮𝗺𝘀 𝘁𝗼 𝘄𝗼𝗿𝗸 𝗮𝗹𝗼𝗻𝗴𝘀𝗶𝗱𝗲 𝗔𝗜 It's not enough to deploy AI tools. Teams need to understand how to integrate AI into their workflows, manage AI-driven processes, and improve performance through human-AI collaboration. 𝟯. 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆𝗶𝗻𝗴 𝘀𝗸𝗶𝗹𝗹 𝗴𝗮𝗽𝘀 𝗯𝗲𝗳𝗼𝗿𝗲 𝘁𝗵𝗲𝘆 𝗮𝗳𝗳𝗲𝗰𝘁 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 Skills assessments show what people can actually do, not just what their job titles suggest. Companies that map capabilities across their workforce can redeploy talent strategically and keep people engaged in roles where they can grow. 𝟰. 𝗖𝗿𝗲𝗮𝘁𝗶𝗻𝗴 𝗽𝗮𝘁𝗵𝘄𝗮𝘆𝘀 𝗶𝗻𝘁𝗼 𝗿𝗼𝗹𝗲𝘀 𝘄𝗵𝗲𝗿𝗲 𝗽𝗲𝗼𝗽𝗹𝗲 𝗰𝗮𝗻 𝘀𝘂𝗰𝗰𝗲𝗲𝗱 Whether it's technical training, role-specific development, or management skills, companies need structured programs that prepare people for the work that's coming, not just the work that exists today. The retirement wave is gathering speed. Skills-based hiring is becoming the norm. Growth isn't waiting. What's your approach to workforce readiness right now?

🚫 STOP saying: “AI won’t replace you. A person using AI will.” It sounds more like a threat than a strategy. It shuts down the conversation instead of opening it. Because when employees express fear about AI, they don’t need clichés. They need a plan. Show you’re investing in them, not replacing them. Upskilling isn’t just about training. It’s about trust. So don’t just quote the internet. Show them where they fit in and how to grow. Here are 7 ways leaders can actually do that: 1. Start with listening ↳ Let them voice fears and skepticism ↳ Don’t respond with a TED Talk 2. Audit current roles ↳ Identify tasks that could be enhanced (not replaced) ↳ Talk openly about what AI can actually do 3. Invest in AI literacy ↳ Offer bite-sized, low-pressure workshops ↳ Demystify AI without overwhelming your team 4. Create low-stakes practice zones ↳ Let employees test tools with no deadlines ↳ Make it okay to play, learn, and even mess up 5. Celebrate progress, not perfection ↳ Highlight effort, experimentation, and curiosity ↳ Focus less on mastery, more on momentum 6. Pair learning with real work ↳ Show how AI can solve actual small problems ↳ Build skills while building solutions 7. Repeat the message ↳ “You’re part of the future.” ↳ “And we’re building it together.” No trust, no transformation. AI adoption isn’t just strategy, it’s a trust fall. 💬 What’s one step you’ll try with your team? ♻️ Repost if you’re investing in people, not just tech. 👣 Follow Janet Perez for more like this.

Everyone’s talking about AI. Companies are racing to upskill their workforce, preparing employees to “harness the power” of tools like ChatGPT, machine learning models, and automation. But there’s a question we don’t ask enough: Who can truly call themselves AI experts when the technology is evolving faster than we can keep up? This isn’t like teaching someone Excel or project management. AI is constantly changing—what’s cutting-edge today could be outdated in six months. So how do you train people on something that’s a moving target? At Growthspace, we’ve been asking ourselves the same question. Here’s the conclusion we’ve come to: it’s not about chasing static knowledge or perfecting a “one-size-fits-all” training. It’s about creating adaptive, precise skill development—training that evolves alongside the technology. Here’s how we’re tackling it: We match employees with real-world practitioners, people who are applying AI to solve business problems every day. These aren’t just theorists, they’re doers. We focus on the AI skills that are relevant to their department/function. The interesting AI applications are function-specific. You use AI in a whole different way if you are an engineer or an SDR. We expand our AI skill taxonomy every day. Unlike other skills that do not frequently change (think communications), we are actively looking at new AI-related skills that are required. The goal isn’t to make every employee an AI expert overnight. That’s not realistic. The goal is to build a workforce that can adapt, learn, and thrive as AI reshapes the world of work. AI may be a moving target, but with the right approach, we can prepare people to meet it head-on.

Recent research from Indeed Hiring Lab indicates that while GenAI is unlikely to fully replace human workers, it will provide significant augmentation to human capabilities. Their analysis of over 2,800 skills shows that GenAI best handles repetitive and knowledge-based tasks, allowing humans to focus on core skills requiring ingenuity, hands-on application, and interpersonal interaction. In a separate analysis, Kyla Scanlon introduces the concept of "friction" as a lens into the AI landscape. She states that while the digital world seeks to eliminate friction for the user, it often transfers that friction to the physical world (underfunded infrastructure, overworked labor). This redistribution of friction potentially devalues traditional skills and credentials. I've been digging into a concept I refer to as skills flux -- a period in which workers will use their existing skills while needing to learn new ones as their jobs change due to automation and AI. Both the Indeed research and Kyla's paper illustrate this transitional period as an opportunity to redefine the basic tenets behind "reskilling" or "upskilling" (I would love to retire those two words from our lexicon). Our focus in L&D needs to be on deeply understanding how automation and AI changes the nuances of jobs (yes, to the task level) and to then develop training that facilitates the workforce to learn new GenAI-specific skills as complementary to their existing skills. L&D's role is to drive a programmatic approach to rapidly develop the workforce while balancing the tension of this period of skills flux. If we do this right, we relieve the company from large workforce displacement and enable the metrics important to the business as the integration of automation and AI evolves -- it's expensive and time-consuming to continually buy skills. This means we change our focus from traditional "reskilling" and "upskilling" programs to enable more dynamic skills strategies. I recommend these two steps to get started: -- Identify the enterprise critical roles across the company -- Conduct a job architecture inventory in alignment with the business to excavate how automation and AI changes the jobs (and, yes, AI can be used to scale this process) This enables a strategy for L&D to be in service of the most critical aspects of business continuity. For the first time in L&D's history, we face the daunting task of simultaneously preparing the workforce to execute strategies resulting from automation and AI while preventing the instability that a skills flux brings to the business and the workforce. Here are links to these two reports: -- Indeed Hiring Lab: https://lnkd.in/grF2C2-E -- Kyla Scanlon: https://lnkd.in/gAkcj4Qi

AI writing is eating the world, and it illustrates how we're doing AI strategy wrong. Authenticity is everything. I help companies with AI strategy- it’s not about chasing better tech, it's enhancing what makes your product unique through the people who understand it. Talent Folks: Train your entire organization to use AI effectively, or watch your competitive advantage disappear. HR and Talent leads - this post is for you. I was alerted to this study by the great Ethan Mollick, one of the best AI thought leaders out there. Follow him. ++++++++++++++++++++ WHAT THE RESEARCH SHOWS: This Stanford study shows that AI-assisted writing has infiltrated business and society. - 18% of financial consumer complaint text is now LLM-assisted - 24% of corporate press release content is attributable to LLMs - 10% of job posting content in small firms is AI-generated (15% in younger firms) - 14% of UN press release content is modified by LLMs The study analyzed over 1.5 million documents and found a consistent pattern: minimal usage before ChatGPT (Nov 2022), explosive growth through mid-2023, then plateauing by late 2023. ++++++++++++++++++++ WHAT THIS MEANS FOR YOUR AI STRATEGY HR and Talent leads: You need to be leading this AI upskilling, and it doesn't start with recruiting. It starts with upskilling the best brains in your organization - those folks who don't love digital but are absolutely brilliant at what they do. These people are at risk because they may not jump on the GenAI train fast enough. But they are GOLD because AI has to augment brains, and you want it to augment the BEST brains in your org. They don't need to be techy!! They need to be able to communicate. That's it. ++++++++++++++++++++ WHAT TO DO NOW - 3 CRITICAL STEPS: 1. Upskill Your Domain Experts Your organization's domain experts are GOLD. AI must amplify their expertise, not replace it. When different people use genAI differently, you end up rewarding someone just because they're better at using AI, not because they're better at their job. 2. Require Leaders to Set New Performance Benchmarks Team leaders need to understand that genAI fundamentally changes how people work. Line managers across departments must grasp what productivity means when it's augmented by AI, because THEY define expectations and shape how teams use these tools. 3. Train Everyone - No Exceptions When you train your entire organization in AI, you capture the full value of your people's expertise. This is about amplifying what everyone already does well, creating a strategic advantage that's hard to match. ++++++++++++++++++++ WE CAN HELP. When your company is ready, we are ready to upskill your workforce at scale. Our Generative AI for Professionals course is tailored to enterprise and highly effective in driving AI adoption through a unique, proven behavioral transformation. It's pretty awesome. Check out our website or shoot me a DM.