👋 Good morning! Today highlights AI moving into real impact. MyHair AI helps people monitor hair health and detect early signs of hair loss before it becomes visible. Model ML is transforming financial work by producing complex reports in minutes, saving time and increasing reliability. At the same time, AI is already technically capable of performing 11.7% of U.S. work, quietly reshaping routine office tasks across industries. These examples show AI becoming a partner in smarter, faster, and more data-driven decisions.
👨🦲MyHair AI - A New Tool for Detecting Hair Loss
A new startup, MyHair AI, has launched an AI-based service designed to help people track hair health and spot early signs of baldness. The app asks users to upload photos of their scalp, then uses computer-vision models trained on hundreds of thousands of images to estimate hair density, detect thinning, and predict possible hair loss.
Importantly, this isn’t a one-off snapshot. As users upload new scalp photos over time, MyHair AI tracks changes, enabling a longitudinal view: whether hair density is stable, improving or deteriorating. That lets users build a hair-care plan (or seek professional help) before visible hair loss becomes severe.
On top of that, the service aims to inject transparency into a market often filled with dubious claims. MyHair AI offers verified reviews of clinics and specialists, and guidance based on real data, rather than hype or guesswork.
Why this matters
For individuals: Hair loss often catches people off guard. Having a data-driven early-warning via AI lets you make more informed choices, lifestyle changes, preventive care, or seeking medical advice — rather than reacting only once hair thinning becomes visible.
For the hair-care & health-tech industry: This signals a shift: solutions combining computer vision + consumer accessibility could make hair-loss detection and monitoring more credible, less emotionally charged, and more data-oriented.
For product design in general: It reflects a trend where AI doesn’t just recommend products, but empowers users with insights about their own bodies, bridging a gap between cosmetic claims and measurable health signals.
Takeaway: MyHair AI shows how AI can turn a historically messy, emotionally charged problem — hair loss — into something quantifiable and trackable. It doesn’t promise miracle cures, but it offers a clearer, earlier picture of what’s really happening — which is often the first step toward better decisions.
📈 Trendlines: AI Could Already Do 11.7% of All Paid Work in the U.S.
A new MIT report breaks down something most people feel, but haven’t seen measured: how much everyday work AI could realistically do right now. The number they landed on is surprisingly big, 11.7% of all wages paid in the U.S.
Put differently:
If you took every job in the country, every task, and every dollar paid for that work, MIT estimates that AI systems today are technically capable of doing work equal to 11.7% of that total. That doesn’t mean companies have adopted AI to that level yet, just that the capability exists.
What kinds of work are we talking about?
Not dramatic stuff like robots taking over factories. The biggest exposure is in routine office tasks:
organizing information
preparing documents
scheduling
checking data
moving information between systems
These are the quiet, repetitive tasks that happen in the background of finance, HR, operations, admin, customer support, and professional services.
Why this matters
This is much bigger than what’s visible. Only about 2% of work disruption makes headlines (mostly tech jobs). The rest, the 11.7%, is almost invisible because it’s spread across hundreds of roles and industries.
It affects every state and every sector. This isn’t a “Silicon Valley” problem. The exposure is broad.
Jobs aren’t just disappearing — they’re changing. Even if people keep their roles, big chunks of what they do could shift toward oversight, judgment, problem-solving, and interpersonal work.
What it doesn’t mean
The 11.7% isn’t a prediction of layoffs. It’s simply a measure of what AI is technically capable of doing today. Whether it actually happens depends on adoption, cost, regulation, and how companies choose to use the technology.
Takeaway:
The 11.7% figure is a reality check: AI is already capable of doing a meaningful slice of the country’s day-to-day office work. The shift won’t feel like a sudden shock, it’ll show up gradually, in the quiet parts of jobs people don’t usually think about.
🤖 AI in Action: The End of Manual Financial Work?
In one of the biggest fintech Series A rounds in history, Model ML raised $75 million to scale an AI platform that aims to disrupt how banks, asset managers and consultancies produce high-stakes documents.
Model ML lets financial firms build AI-powered workflows that turn raw data into polished Word reports, Excel analyses or PowerPoint pitch decks, automatically, reliably, and in the formats these institutions require.
For decades, investment banking and consulting teams have spent untold hours aligning spreadsheets, formatting reports and double-checking slides. Model ML promises to shift that paradigm: what used to take teams days or weekends can now be done in minutes, with fewer errors and consistent formatting.
For a sector where precision, compliance and speed matter more than ever, this isn’t just about saving time. It’s about increasing reliability, freeing up talent for analysis instead of grunt work and potentially reshaping how deals are prepared and delivered.
As Model ML pushes its global expansion, backed by top-tier investors including FT Partners, Y Combinator and others, the raise sends a clear message: the future of financial services isn’t just human, it’s hybrid.
💡Quick Hits and Numbers
Industries that are adopting AI the most are seeing productivity soar, in some cases nearly quadrupling compared to the years before generative AI.
Jobs exposed to AI are evolving faster than ever, with the skills employers look for changing about two-thirds more quickly than in other roles.
Companies leveraging AI effectively are generating significantly more revenue per employee, sometimes three times as much as businesses that haven’t embraced the technology.
🧩 Closing thought
AI is not replacing humans, it is changing how work gets done and how people grow alongside technology. Spotting hair loss early, automating routine office tasks, and accelerating financial workflows are all examples of how AI is helping us work more efficiently. The key question is not what AI can do, but how we choose to collaborate with it to achieve more.