{"id":148076,"date":"2026-04-21T08:00:51","date_gmt":"2026-04-21T12:00:51","guid":{"rendered":"https:\/\/trainingindustry.com\/?post_type=articles&p=148076"},"modified":"2026-04-14T10:59:12","modified_gmt":"2026-04-14T14:59:12","slug":"how-to-tackle-inclusive-ai-capability-building","status":"publish","type":"articles","link":"https:\/\/trainingindustry.com\/articles\/diversity-equity-and-inclusion\/how-to-tackle-inclusive-ai-capability-building\/","title":{"rendered":"How to Tackle Inclusive AI Capability Building"},"author":52,"featured_media":148078,"template":"","tags":[30422,36679,3900],"class_list":["post-148076","articles","type-articles","status-publish","has-post-thumbnail","hentry","tag-ai-training","tag-ai-workforce","tag-inclusive-learning","global_topic_tax-artificial-intelligence","global_topic_tax-diversity-equity-and-inclusion"],"acf":{"sponsored":false,"gated":false,"gated_content_type":"","file_attachment":null,"gated_content":"","form_instruction_header":"To access the full article, please fill out the form below:","pardot_html_embed":"","author_override":true,"author_name":"Milena Berry","author_image":"","author_bio":"Milena Berry is the co-founder and CEO of PowerToFly, a global platform partnering with companies to build high-performing, inclusive teams across a network of over 200 million professionals. A recognized thought leader on the future of work and AI, she is also a proud immigrant, wife and mother of four \u2014 and a firm believer that the best workplaces are built for everyone; learn more at https:\/\/powertofly.com\/<\/a>.","excerpt":"Organizations that make AI training accessible and inclusive across roles will be better positioned to compete in an AI-driven future.","main_content":"Workplace inclusion has never been a simple conversation. And lately, it\u2019s gotten even more layered, with political shifts and compliance concerns taking up so much space. While the debate continues, an increasingly urgent problem is taking shape inside organizations globally: As artificial intelligence (AI) reshapes industries and day-to-day workflows at a pace that is, frankly, a little dizzying, the question of who gets access to AI skills training is too often overlooked.\r\n\r\nBeing intentional about making AI capability-building inclusive and accessible to everyone, not just tech-savvy employees, is a strategic move that ensures teams can actually compete.\r\n

AI Isn\u2019t Optional, But Access to AI Training Often Is<\/h2>\r\nNobody handed out a roadmap for the \u201cAI era.\u201d Companies have been doing their best to keep up by adopting tools, running lunch-and-learns and hoping that enthusiasm is contagious. The intention to get more people using AI to drive productivity is there. The execution, however, is where things tend to get complicated.\r\n\r\nIn practice, AI training<\/a> has largely followed the path of least resistance, landing with technical teams, leadership and employees who already work in tech. For everyone else, upskilling might look more like a YouTube playlist or a vague nudge to \u201cexplore the tools.\u201d The gap between those experiences is wider than most companies realize.\r\n\r\nProfessionals from underrepresented backgrounds and those in non-technical roles are less likely to receive structured AI training, not because anyone planned it that way, but because many programs are built with a specific learner in mind and everyone else gets \u201cthe leftovers.\u201d The downstream effects compound quickly: The employees who miss out on AI capability-building are often the same ones passed over when AI-adjacent roles open up and promotions are on the table. A simple training oversight has a way of affecting whole career trajectories.\r\n\r\nSo, what does it look like to do this differently?\r\n

Inclusive AI Capability Building<\/h2>\r\nInclusive AI capability building simply means designing training programs that actually work for the full range of people doing the work, and that starts with accessibility.\r\n\r\nNot everyone joining an AI upskilling program has a computer science degree. Some employees are learning what a large language model (LLM) is while simultaneously managing a full workload, a household and possibly a child who is also somehow already better at technology than they are (humbling, but true for many).\r\n\r\nBeyond experience level, accessibility means accounting for employees with disabilities, those working across different time zones, those without reliable access to high-end devices and those for whom English is a second language. Consider inclusive training<\/a> as a system, as opposed to a single program, designed with the full human range in mind.\r\n\r\nThat means multiple entry points: foundational AI literacy for those newer to the space, more advanced technical tracks for those ready to go deeper and role-specific framing that helps employees connect the dots to their actual day-to-day work. It also means flexible formats, asynchronous options, mobile-friendly content, captioned video and materials available in multiple languages where possible. Lastly, it means creating environments where it feels safe to not know something yet.\r\n

Common Challenges \u2014 and How to Navigate Them<\/h2>\r\nEven with the best intentions, many organizations run into the same handful of obstacles when trying to build AI skills across a full workforce:\r\n