32 Female Founders, One Room, and What Actually Happens When You Teach AI to People Who Need It
32 Female Founders, One Room, and What Actually Happens When You Teach AI to People Who Need It
Lebanon, 2024. The Women Economic Network. Thirty-two female-run small businesses in one room.
I've spoken about AI at tech conferences. I've pitched enterprise clients on automation. But nothing recalibrated my thinking on AI adoption faster than standing in front of 32 women who run actual businesses — bakeries, boutiques, service agencies, tutoring practices — and being asked to make AI useful for them.
This is that story.
The Setup
The Women Economic Network (WEN) is a Lebanon-based organization focused on economic empowerment for women. In 2024 they brought me in to design and deliver a digital marketing and AI curriculum for a cohort of 32 female business owners.
The brief: practical, not theoretical. Build something they could actually use the next day.
The challenge: these weren't tech people. They were operators. Busy, resourceful, skeptical of anything that adds complexity instead of removing it.
That was the right kind of skepticism.
What Most AI Training Gets Wrong
Most AI training is designed for people who are already comfortable with technology. The structure is: here's the tool, here's the interface, here are the features.
That model doesn't work for a business owner who has 11 things to do before noon and a Wi-Fi connection that drops twice an hour.
So I built the curriculum around jobs to be done, not tools:
- I need to write product descriptions for 40 items — fast
- I need to respond to customer messages without spending 2 hours on it
- I need to create content for Instagram without hiring someone
- I need to understand what my competitors are doing
Every AI tool we covered was anchored to one of those jobs. The technology was secondary. The outcome was primary.
The Sessions
We ran four sessions across the cohort:
Session 1 — Digital Presence Audit Before introducing any AI, we audited what they had. Google Business Profiles. Instagram accounts. WhatsApp Business setups. Most were either incomplete or completely missing. We fixed the fundamentals first.
AI has no leverage on a broken foundation.
Session 2 — Content Without a Team This was the one that landed hardest. I showed them how to turn a photo of their product, a voice note describing it, and a two-line brief into a full week of Instagram captions using Claude and ChatGPT.
One participant — a woman running a handmade soap business out of her kitchen — wrote her first month of content in 45 minutes. She cried. I'm not going to pretend that wasn't significant.
Session 3 — Customer Communication Systems WhatsApp is the primary business communication channel in Lebanon. We built response templates, FAQ frameworks, and auto-response flows. Not bots — frameworks that made their human responses faster and more consistent.
Session 4 — Competitive Intelligence and Pricing Using AI to research competitors, understand market positioning, and pressure-test pricing. Basic for a growth strategist. Revelatory for a business owner who had never had access to research tools.
What Actually Landed
The tools that got used after the workshop:
- ChatGPT for content — every single participant. Sticky because the output was immediately visible.
- Canva AI features — 80% adoption. Low barrier, visual output.
- Google Gemini for search — mixed. Still required a behavior change.
- WhatsApp Business automation — 60% adoption. Those who set it up loved it.
The tools that didn't stick:
- Anything requiring API access or technical setup
- Tools with English-only interfaces (Arabic is the working language)
- Platforms with complex onboarding
The pattern: adoption follows friction. The lower the setup cost, the higher the retention.
What Changed My Thinking
Before this workshop I thought the AI adoption gap was about awareness. Teach people the tools exist and they'll use them.
That's wrong.
The gap is about relevance framing. Until someone can see their specific problem solved by AI in under 60 seconds, it stays abstract. The moment it becomes concrete — the moment the soap maker gets her caption — the barrier collapses.
The other thing that changed: I started taking the "human element" of AI adoption seriously as a design constraint. Not as a feel-good consideration, but as a technical one.
If the workflow isn't designed around how humans actually behave — under pressure, with limited time, in their actual language — the tool fails regardless of how powerful it is.
The Bigger Picture
Lebanon has one of the highest rates of female entrepreneurship in the MENA region, driven partly by economic necessity. These are not hobbyists. They are survival builders.
They are also exactly the demographic that gets overlooked in the AI conversation — which skews toward English-speaking, tech-adjacent, well-funded operators.
The tools exist. The access increasingly exists. What's missing is curriculum designed for their reality.
That's a gap worth closing.
The Women Economic Network operates in Lebanon supporting women's economic empowerment. If you're building AI literacy programs for underserved markets, I'm open to collaborating — reach out.
Read more founder stories on the blog or explore Torch99's work.
About the Author
Liwaa Beaini is the founder of Torch99 and co-founder of Virtual Minds — an AI product studio registered under ADGM (Abu Dhabi Global Market), UAE. He is an AI strategist and product builder operating from Lebanon, specialising in GEO (Generative Engine Optimization), mobile app growth, and AI-first systems. He has grown 40+ mobile apps, advised enterprise clients across MENA, and built products across AI visibility, local intelligence, and digital transformation.
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Founder, Torch99 · Co-Founder, Virtual Minds (ADGM, UAE)
AI strategist and product builder operating from Lebanon. Founder of Torch99 and co-founder of Virtual Minds. Building 99Visibility — the GEO audit platform for the AI search era.