Why You Need Accessible AI Training

My recent research, which examines the adoption of emerging technologies through a gender lens, illuminates continued disparities in women's experiences with Generative AI. Day after day we continue to hear about the ways GenAI will change how we work, the types of jobs that will be needed, and how it will enhance our productivity, but are these benefits equally accessible to everyone? My research suggests otherwise, particularly for women. 🕰️ The Time Crunch: Women, especially those juggling careers with care responsibilities, are facing a significant time deficit. Across the globe women spend up to twice as much time as men on care and household duties, resulting in women not having the luxury of time to upskill in GenAI technologies. This "second shift" at home is increasing an already wide divide. 💻 Tech Access Gap: Beyond time constraints, many women face limited access to the necessary technology to engage with GenAI effectively. This isn't just about owning a computer - it's about having consistent, uninterrupted access to high-speed internet and up-to-date hardware capable of running advanced AI tools. According to the GSMA, women in low- and middle-income countries are 20% less likely than men to own a smartphone and 49% less likely to use mobile internet. 🚀 Career Advancement Hurdles: The combination of time poverty and tech access limitations is creating a perfect storm. As GenAI skills become increasingly expected in the workplace, women risk falling further behind in career advancement opportunities and pay. This is especially an issue in tech-related fields and leadership positions. Women account for only about 25% of engineers working in AI, and less than 20% of speakers at AI conferences are women. 🔍 Applying a Gender Lens: By viewing this issue through a gender lens, we can see that the rapid advancement of GenAI threatens to exacerbate existing inequalities. It's not enough to create powerful AI tools; we must ensure equitable access and opportunity to leverage these tools. 📈 Moving Forward: To address this growing divide, we need targeted interventions: Flexible, asynchronous training programs that accommodate varied schedules Initiatives to improve tech access in underserved communities. Workplace policies that recognize and support employees with caregiving responsibilities. Mentorship programs specifically designed to support women in acquiring GenAI skills. There is great potential with GenAI, but also risk of leaving half our workforce behind. It's time for tech companies, employers, and policymakers to recognize and address these gender-specific barriers. Please share initiatives or ideas you have for making GenAI more inclusive and accessible for everyone. #GenderEquity #GenAI #WomenInTech #InclusiveAI #WorkplaceEquality

My number one priority these days is adding and helping others add AI training and skills. While I think the tech advances are a tornado of jockeying for position, there's a clear need that won't change, and that's the need for workers to add AI Skills. That's why I co-founded 𝗔𝗹𝗹 𝗧𝗵𝗶𝗻𝗴𝘀 𝗔𝗜 (𝗳𝗼𝗿𝗺𝗲𝗿𝗹𝘆 𝗔𝗹𝗹 𝗧𝗵𝗶𝗻𝗴𝘀 𝗢𝗽𝗲𝗻 𝗔𝗜) and 𝗧𝗵𝗲 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹𝗹𝘆 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗡𝗲𝘁𝘄𝗼𝗿𝗸, to provide knowledge workers the information and training they need to stay relevant. I am leading a workshop on Prompt Engineering tomorrow to help folks upskill as I see crazy demand for these skills. I already have over 600 users signed up to come to learn how to use AI better for business. (Link in comments if you want to join, it's free). Today my business partner Todd Lewis shared this article from IT Pro points to studies from 𝗪𝗿𝗶𝗸𝗲 and 𝗣𝗹𝘂𝗿𝗮𝗹𝘀𝗶𝗴𝗵𝘁 on how this is playing out. It totally reinforces my beliefs. There's a noticeable gap between perceptions of AI’s role: ⦿ Business Leaders believe AI assists with 32% of workloads. Overestimates the actual usage. ⦿ Knowledge Workers estimate AI involvement at only 14%. Showing there's a lot of opportunity. ⦿ Despite this gap, where AI is applied, 79% of workers report improved productivity. Upskilling the workforce is recognized as the most effective efficiency measure by knowledge workers. 🔹 AI Adoption vs. Workforce Readiness • 92% of companies accelerated AI projects last year, yet 90% of executives lack clarity on their team's actual AI capabilities (Pluralsight).    🔹 Skills Gaps and Productivity • 84% of business leaders cite a lack of AI skills as their biggest roadblock, causing project delays in 75% of organizations (Pluralsight). • Only about half of all workplace tasks are deemed high-impact, highlighting significant inefficiencies (Wrike).    🔹 Impact of Inefficiency • Organizations lose approximately $15,138 per employee annually due to unnecessary tasks and meetings (Wrike). • Efficiency measures reportedly increased revenues by up to 26%, yet only 9% of businesses primarily track these financial outcomes (Wrike). • Businesses report average savings of $3,046 per employee annually through efficiency measures. (Wrike)    🔹 Upskilling as a Strategic Priority: • Over 50% of companies are actively investing in AI skills training to bridge gaps and mitigate employee concerns over job displacement (Pluralsight). • Workers rank upskilling as the most effective strategy for improving workplace efficiency, satisfaction, and productivity (Wrike).    Check out the article and you can follow the links to both reports, both are good reads. https://lnkd.in/eAeDAqfG

AI can be a powerful tool—but only if you feel comfortable using it. According to a recent report from the Initiative for a Competitive Inner City and Intuit, 89% of small businesses are using AI—primarily to automate routine tasks, increase productivity, and boost job satisfaction. But the data also reveals something troubling: 🔹 Men report feeling more comfortable using AI than women, nonbinary, or gender-nonconforming business owners. 🔹 Minority-owned businesses report low comfort with AI tools at nearly twice the rate of non-minority-owned businesses. As a consultant, this matters to me. The technology is here, but equity in access and confidence is not. If we want AI to empower, not divide, we need to create inclusive paths forward. Here are 3 examples of the ways we can do that: 💡Make education accessible. Think bite-sized learning: short videos, podcasts, live demos—not just long webinars or whitepapers. 💡Create safe learning spaces. Workshops, peer groups, or guided sessions led by trusted facilitators—spaces where questions are welcome and curiosity is encouraged. 💡Demystify with relevance. Don’t just talk about AI in theory, but demonstrate how it solves real problems in YOUR business. Professional communities that create amazing spaces for learning, support, and encouragement, like #SheLeadsAI Society (link in comments) for women in AI, offer great opportunities for all three idea above. AI isn’t (and shouldn’t be) about replacing people—it’s about freeing them up to do more of what they love. Will roles change and evolve? Yes. Do skills need to grow, too? YES. Every business owner, regardless of identity, should have the tools and confidence to explore what’s possible - let's ensure that reality. (Link to original article in comments.)

What worries me about AI adoption? Uneven access. 1 in 3 college students use ChatGPT, but only 1 in 4 schools offer AI training. OpenAI just published a new report, highlighting a growing divide in AI access and preparedness across the U.S.: 📊 Students are embracing AI for learning. Over one-third of 18- to 24-year-olds in the U.S. use ChatGPT, and 1 in 4 messages are education-related—from starting papers to brainstorming ideas. 🌍 Adoption varies widely by state. Students in California, Virginia, New Jersey, and New York have the highest usage, while Wyoming, Alaska, Montana, and West Virginia lag behind. These gaps could shape workforce readiness and economic mobility. 👩💻 AI skills are now a hiring advantage. Employers increasingly prioritize candidates with AI proficiency—even over more experienced applicants who lack those skills. Yet, with 3 in 4 students wanting AI training and only 1 in 4 schools providing it, many are left to figure it out on their own. AI literacy is becoming as essential a skill as writing, research, and data analysis—but access to AI training remains uneven. Some students learn in AI-integrated environments, while others are left behind, a divide that could have long-term consequences for workforce readiness. I believe that higher education should play a bigger role. It's important to understand that good AI training isn’t just about using AI—it’s about knowing when to trust it, when to challenge it, and how to use it to push thinking further. These are the skills that I feel will define the future of work. Full report in the comments. Would love to hear creative examples of how institutions are enabling AI training!