Importance of Training for Genai Success

“Hey Drew, I can’t keep up with all the AI stuff; it’s just overwhelming,” shared a CMO at a $450mil tech company. The other Huddlers were relieved to hear they weren’t alone. A fascinating discussion ensued as these CMOs shared what they know, what they don’t, and how they’re sorting through the myriad of options. Here are some of their questions and an aggregation of the best answers. How are B2B CMOs using GenAI right now? Most CMOs admit they are still in the early days of GenAI adoption. Most don’t have a GenAI strategy. Most are creating content more efficiently. For example, those creating podcasts are doing so 5-10x faster by recording, editing, and publishing with just one person using Descript. How do we get beyond the “go play” and “dabbling” stage? Strategy before tools. This means identifying the problems you want to solve, which, when solved, would have the most significant impact on the business. For example, you may need to translate and route hundreds of digital ads into fifty different languages multiple times per year for multiple ad platforms. That’s a lot of variations and the perfect labor-intensive task at which GenAI excels. Benchmark your time sucks. Ideally, your team will be able to benchmark the current workflows for the most time-consuming projects. Some of these projects can be streamlined easily with one or more existing tools (like the podcast example). Focus on a few of these initially to record some quick wins. Isolate the big wins: Others may require more complex solutions with API integrations – stuff that you used to have to get IT help with but can now solve with the guidance of AI. You’ll want to create a matrix (potential value, time to solution, complexity of solution) to help shape your priorities. Training before licenses. Getting licenses for everyone on your team sounds like a great idea until you realize adoption is not universal. Giving them the tool alone does not improve productivity. Training your team together with some specific usage expectations will move things forward. Then, gather monthly to share problems solved and unsolved. Given the speed at which these tools evolve, expect to do training 2-3x per year. (Ping me for a list of trainers). How important is it that CMOs use these tools themselves? It’s imperative. First, every leader should have a folder on their phone's home page with at least 3 LLMs (I have the paid versions of ChatGPT and Claude and the free version of Perplexity). There’s no reason you shouldn’t use these tools multiple times a day to prepare for meetings, think through your ideas, and investigate something personal. Learn the basics of prompting. Better yet, become a master prompter. Jeff Morgan, CMO of Elements, uses this prompt engineering framework: S = Specifications P = Process     A = Authenticity R = Rules & Regulation K = KPIs See comments for the link to the CMO Huddles Studio episode in which Jeff details SPARK. How are you keeping up?

I think about this old Sam Altman tweet all the time - it changed how I teach AI. I now start with leadership, no exceptions. If leaders don't understand how AI works, talent evaluation gets skewed - like picking Olympic sprinters without realizing the fastest runners are stuck in ski boots. Here's the challenge, and how I deal with it:    1.  Domain Expertise is Gold Your organization’s domain experts are GOLD . AI should NEVER replace their expertise - it has to amplify it! When you have different people using genAI in different ways, you end up rewarding someone just because they're better at using AI, not because they're better at their job. Your experienced people with deep domain knowledge are your greatest assets in the AI era. Full stop. But if you're not teaching them generative AI, they're your Olympic sprinters that you've equipped with ski boots instead of the best shoes, training, nutrition, etc.    2.  Leadership Has to Set New Benchmarks Team leaders need to understand that genAI will fundamentally change how their people work. The 8-hour workday looks completely different now. Line managers across departments need to grasp what productivity means when it's augmented by AI, because THEY are the ones who will define expectations and shape how teams actually use these tools.    3.  Train Everyone When you train your entire organization in AI, you capture the full value of your people's expertise. Again, this is NOT about replacing skills - it's about amplifying what everyone already does well. This creates a strategic advantage that's hard to match. WHAT TO DO: 1. Get senior leadership hands-on experience with genAI - not just conceptual understanding 2. Ensure line managers truly grasp how AI changes daily work and productivity metrics 3. Invest in comprehensive AI training across your organization - it's the key to unlocking your team's full potential ++++++++++++++++++++++++++ When you're ready, we have a powerful digital course tailored to enterprise that levels up everyone - not by teaching tools, but by changing behavior. It's extremely effective, I promise. If you're interested, learn more on our website or shoot me a DM.

My top 5 highlights from Slack's 10,000-worker GenAI survey: 1️⃣ 81% of AI users report productivity gains, along with higher engagement and employee experience. 2️⃣ Workers who receive AI training report up to 19x higher productivity gains. 3️⃣ Companies with established AI policies see 6x higher adoption rates. 4️⃣ And yet, only 15% of those surveyed felt they had the training to use AI effectively, and 40% of companies lack company guidelines. 5️⃣ Diversity insights: Hispanic/Latinx (43%), Black (42%), and Asian American (36%) workers embrace AI at higher rates than white colleagues (29%). Also, there's a gender gap - Gen Z men adopt AI 25% more than Gen Z women. Given that trained employees are significantly more likely to effectively use AI and be more engaged, companies clearly need to prioritize AI training. This may also help address diversity gaps. I'm proud to have contributed to our company's AI principles, our generative AI policy, and our online training on the safe and effective use of generative AI. I've also developed a live, experiential GenAI workshop that can be customized to any end user, and I'm currently working on a train-the-trainer program to enable others to lead practical, hands-on GenAI workshops. If you're interested in learning more about the safe and effective use of generative AI, please ping me. 🙏 Check out the full report here: https://lnkd.in/e9xh3YNx

AI isn’t the future—it’s the present. HR leaders must champion AI upskilling to keep employees relevant, engaged, and competitive. Here’s why: 🔹 1. Future-Proof the Workforce 🔸 AI is transforming industries—employees need new skills to stay ahead. 🔸 Organizations that invest early gain a competitive edge in innovation and efficiency. 🔹 2. Enhance Productivity 🔸 AI automates repetitive tasks, freeing employees for higher-value work. 🔸 AI-trained teams solve problems faster and smarter. 🔹 3. Stay Competitive 🔸 Competitors are already investing in AI—your workforce should too. 🔸 AI-literate employees drive innovation and uncover new business opportunities. 🔹 4. Meet Employee Expectations 🔸 Younger generations expect cutting-edge training and career development. 🔸 AI upskilling boosts engagement, retention, and talent attraction. 🔹 5. Reduce Skill Gaps 🔸 AI is creating new roles that require specialized skills. 🔸 Upskilling ensures employees can grow into these roles, reducing hiring gaps. 🔹 6. Support Diversity & Inclusion 🔸 AI without proper training can reinforce biases—education prevents this. 🔸 A diverse, AI-proficient workforce creates fairer, more inclusive solutions. 🔹 7. Drive Cultural Change 🔸 AI adoption isn’t just about tools—it requires a mindset shift. 🔸 Upskilling fosters a culture of adaptability, innovation, and learning. 🔹 8. Improve Decision-Making 🔸 AI empowers employees with data-driven insights. 🔸 Training ensures they interpret and apply this data effectively. 🔹 9. Ensure Ethical AI Use 🔸 Employees must understand AI’s limitations and ethical concerns. 🔸 Proper training minimizes risks of bias, misuse, and unintended consequences. 🔹 10. Boost Organizational Resilience 🔸 AI-literate employees adapt faster to disruptions and change. 🔸 This agility future-proofs the organization against industry shifts. HR leaders who champion AI upskilling position their organizations for long-term success while empowering employees to thrive in the AI-driven workplace. 💬 How is your company preparing for AI adoption? Drop your thoughts below! ⬇️ ♻️ Repost to help your network prepare for the future. ➕ Follow Ricardo Cuellar for more insights on AI & HR.

𝗪𝗵𝗲𝗻 𝗜 𝘁𝗮𝗹𝗸 𝘁𝗼 𝗖-𝗦𝘂𝗶𝘁𝗲 𝗹𝗲𝗮𝗱𝗲𝗿𝘀, 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹𝗶𝘁𝘆 𝗶𝘀 𝘂𝗻𝗹𝗶𝗸𝗲 𝘄𝗵𝗮𝘁 𝘆𝗼𝘂 𝗵𝗲𝗮𝗿 𝗶𝗻𝘀𝗶𝗱𝗲 𝘁𝗵𝗲 𝗔𝗜 𝗯𝘂𝗯𝗯𝗹𝗲. Most companies are just starting to make AI training available to their employees. While some are already a bit further ahead, the majority of leaders are wondering where to start. Here are my two cents in a recent InformationWeek article: Andreas Welsch advocates starting with a “Community of Multipliers”—early tech adopters who are eager to learn about the latest technology and how to make it useful. These multipliers can teach others in their departments, helping leadership scale the training. Next, he suggests piloting training formats in one business area, gathering feedback, and iterating on the concept and delivery. Then, roll it out to the entire organization to maximize utility and impact. “Despite ChatGPT being available for two years, Generative AI tools are still a new type of application for most business users,” says Welsch. “Prompt engineering training should inspire learners to think and dream big.” He also believes different kinds of learning environments benefit different types of users. For example, cohort-based online sessions have proven successful for introductory levels of AI literacy, while executive training expands the scope from basic prompting to GenAI products. Advanced training is best conducted in a workshop because the content requires more context and interaction, and the value comes from networking with others and having access to an expert trainer. Advanced training goes deeper into the fundamentals, including LLMs, retrieval-augmented generation, vector databases, and security risks, for example. From tailored workshops to customizable curriculums, workforce enablement needs to fit your needs. Get in touch to help your workforce use AI tools effectively! #ArtificialIntelligence #GenerativeAI #IntelligenceBriefing

Questions around Enterprise AI adoption have focused almost exclusively on the technology, but a much bigger factor is the training--or rather the lack of it--that employees are receiving to properly use GenAI-powered software and services. These new tools demand different types of processes and new methods of working to leverage them to their fullest advantage. Unfortunately, most companies are completely failing to achieve the kinds of productivity gains that are possible because they aren't properly training their employees on how to use them. Without some dramatic changes, many organizations may not see much return on the enormous investments in AI that they've started to make.