{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"EP 262 Women, AI, and the Invisible Load (with Heather Cannings)","description":"Why are women adopting AI at lower rates than men - and what\u2019s really going on underneath the stats? In this episode, host Susan Diaz and Heather Cannings, Women Entrepreneurship Program Lead at InVenture and producer of StrikeUP Canada, dig into time poverty, \u201ccheating\u201d fears, late-night upskilling, and what real support for women entrepreneurs needs to look like in an AI-forward world. Episode summary Susan is joined by Heather Cannings, who leads women\u2019s entrepreneurship programs at InVenture and runs StrikeUP, a national digital conference that reaches thousands of women entrepreneurs across Canada and beyond. Heather shares what she\u2019s seeing on the ground: huge curiosity about AI, mixed with pressure, fatigue, and a sense that it\u2019s \u201cone more thing\u201d women are expected to learn on their own time. Many of the women she serves are juggling multiple roles - business owner, employee, caregiver - then experimenting with AI at 10-11 pm after the workday and bedtime routines are done. They unpack the emotional layer too: why AI still feels like \u201ccheating\u201d or being an imposter for many women the question of whether you have to disclose using AI how to reconcile charging premium prices while using AI behind the scenes Susan and Heather link lower AI adoption rates among women to a wider pattern: another version of the wage gap and systemic inequities in who has time, safety, and support to skill up. The conversation then turns to: Practical, real-world use cases women are already using AI for (grant writing, content, summarizing long docs). What good support systems actually look like for time-strapped entrepreneurs (designing for constraints, not fantasy calendars). How small, scrappy businesses and large organizations can learn from each other on speed, governance, and risk. The uncomfortable reality that many roles most at risk of AI automation - admin, entry-level comms, research - are heavily female. They close with a hopeful lens: how women can use AI to increase their value and control over time and income, why this moment is a genuine opportunity for democratization, and how Heather\u2019s StrikeUP event is trying to meet women exactly where they are. Key takeaways AI doesn\u2019t feel neutral for women - it feels like another test. Many women entrepreneurs are curious about AI but also feel judged, worried about \u201cdoing it wrong,\u201d or like they\u2019re cheating if they use it. Imposter syndrome shows up as: \u201cIs this really my work if AI helped?\u201d Time poverty is the real barrier, not lack of interest. Heather sees women using AI at 10-11 pm after full workdays and caregiving, trying to finish newsletters, social posts, or grant drafts. They are upskilling - just in stolen moments, not spacious strategy sessions. Support systems must be designed for real constraints. Don\u2019t assume people have: unlimited time teams strong internet quiet workspaces Many women join digital events from cars, back rooms, or storage areas between tasks. Training and support must be consumable, flexible, and realistic. One-off AI webinars aren\u2019t enough. A single 60-minute \u201cintro to AI\u201d often just generates an overwhelming to-do list. What works better: smaller, workshop-style sessions hands-on guidance on a specific task or tool practical, \u201cdo it in the room\u201d support so women leave with something done, not just inspired. Women are already using AI for practical, high-impact tasks. Common use cases include: writing and improving copy content planning and social media summarizing long documents drafting grants and pitches The focus is on time savings, staying within tight budgets, and safely getting more done\u2014not chasing cutting-edge AI for its own sake. Enterprise and small business can - and should - learn from each other. Big firms: bring resources, governance, and policy thinking. Small businesses: bring speed, scrappiness, and the ability to implement immediately. Ecosystem players (non-profits, funders, educators) can translate between the two and help find a healthy middle ground. There\u2019s a gendered risk in AI-driven job change. Roles often flagged as \u201cat risk\u201d - admin, entry-level comms, research - are heavily staffed by women. Without intentional upskilling and redeployment, AI could quietly deepen existing inequities. There\u2019s also real opportunity. AI can be a \u201cquiet force in the background\u201d that removes 5-10 hours of repetitive work a week - enough to change a woman\u2019s lifestyle, income, and capacity. It can help women move up the ladder, redesign roles, or reshape their businesses around higher-value work. Designing AI with women\u2019s realities in mind matters. Women shouldn\u2019t just be users; they should help shape how tools are designed, so AI reflects real constraints like caregiving, part-time work, and patchy access - rather than assuming a mythical founder with unlimited time and support. Episode highlights [00:01] Susan sets the scene: 30 episodes in 30 days and how Heather fits into the series. [00:57] Heather introduces InVenture and her role as Women Entrepreneurship Program Lead, plus the StrikeUP conference. [01:55] Why AI remains a hot topic for StrikeUP\u2019s audience of women entrepreneurs. [02:57] AI as a catch-22: it can save time, but learning it feels like \u201cone more thing.\u201d [03:56] \u201cIs this cheating?\u201d \u2013 women\u2019s fears about using AI and being judged. [05:09] AI, transparency, pricing, and the complexity of \u201cshould I tell clients I used AI?\u201d [05:39] How this ties to stats showing women adopting AI 25% less than men\u2014and why Susan sees it as another version of the wage gap. [07:07] Draft vs final: why treating AI output as a first draft, not finished work, is crucial. [08:33] The problem with generic, AI-generated content about \u201cwomen in AI\u201d that sounds impressive but says very little. [09:20] Real-world use cases Heather sees among small business owners. [10:22] The 11 pm pattern: women learning AI in stolen, exhausted moments. [12:06] Why women are resilient and experimenting\u2014but lack daytime access to deep learning and setup time. [13:27] Designing support systems that don\u2019t assume unlimited time, teams, or bandwidth. [14:24] Making training consumable, recorded, and accessible from phones, cars, and storage rooms. [15:34] Why one-off webinars don\u2019t work\u2014and the case for small, workshop-style sessions. [18:09] What big firms can learn from scrappy entrepreneurs (and vice versa). [20:10] The myth that corporates \u201chave it all figured out\u201d on AI. [22:19] AI and job loss: the gendered impact on admin, entry-level comms, and research roles. [23:20] Reframing: how women can use AI to increase their value and move up. [25:16] Adaptation over doom: calculators, the internet, and why we\u2019ll adjust again. [27:04] Heather\u2019s vision: AI as a quiet force helping women gain more control over time and income. [28:41] StrikeUP 2025 details: date, format, giveaways, and on-demand access. If you support or are a woman entrepreneur, use this episode as a prompt to ask: Where are women in your world already using AI - in stolen moments - and how could you meet them there with better support? How can you design AI training and tools that assume real constraints, not fantasy calendars? What\u2019s one concrete way you can help a woman in your ecosystem use AI to increase her value and control, instead of feeling like she\u2019s at risk of being automated away? Connect with Susan Diaz on LinkedIn to get a conversation started.   Agile teams move fast. Grab our 10 AI Deep Research Prompts to see how proven frameworks can unlock clarity in hours, not months. Find the prompt pack here. You can learn more about StrikeUP and register for the free digital conference at strikeup.ca and connect with Heather Cannings on LinkedIn. ","author_name":"AI Literacy for Entrepreneurs","author_url":"http:\/\/4amreport.libsyn.com\/website","html":"