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While Silicon Valley chases the next billion-dollar SaaS unicorn, a massive arbitrage opportunity exists in applying AI to "boring businesses" – traditional service companies that generate steady cash flow but haven't adopted modern technology. This issue of the AIE focuses on what I think is a hugely overlooked opportunity. Businesses that aren’t immune but are resistant to the near-term AI boom while still able to benefit.
The Opportunity: The U.S. home services and trades are a great example. The U.S. HVAC, plumbing and electrical services industries generate about US $318 billion in service revenue. These markets remain highly fragmented. That fragmentation, plus a largely paper‑based operating model, underscores how little digital adoption has occurred.
The AI Gap: While 78% of all companies now use AI (up from 55% in 2023), traditional trades lag significantly. Small businesses that have adopted AI report saving 20+ hours monthly and $500-$2,000 in costs, with a 3.7x ROI on AI investments. Tools like Eagleview's drone AI can reduce quote time from 2 hours to 10 minutes while increasing close rates by 30-40%.
The Valuation Arbitrage: Small service businesses currently trade at just 2.2-3.8x EBITDA. Adding AI automation that increases margins by 20% can boost valuations to 5-7x EBITDA – an immediate value creation opportunity. Constellation Software has proven this model, generating 30%+ annual returns since 2006 by rolling up and optimizing vertical market software companies.
The entrepreneurs who win the next decade won't just be building AI – they'll be deploying commodity AI into industries where "machine learning" still sounds like science fiction. The future belongs to those who use AI to make human workers superhuman, not replace them.
🎙️ AI Confidential Podcast - Are LLMs Dead?
🔮 AI Lesson - The 90-Minute Presentation System
🎯 The AI Marketing Advantage - When AI Chats Become Targeting Data: The New Meta Playbook for Marketers
💡 AI CIO - Audit Can Not Keep Up With AI
📚 AIOS - This is an evolving project. I started with a 14-day free AI email course to get smart on AI. But the next evolution will be a ChatGPT Super-user Course and a course on How to Build AI Agents.
Join me and my friends Greg Boone and Marc Sirkin for AI for Go‑To‑Market (GTM)—a hands-on workshop where marketing, sales, product, and RevOps leaders learn to actually implement AI, not just talk about it.
You'll walk away with:
A strategic and practical overview of how to use AI in your business today.
Practical techniques to accelerate your pipeline
Real templates and prompts you can deploy Monday morning
Why this matters now: Every day you wait to implement AI in your GTM motion is another day your competitors pull ahead. This isn't about the future—it's about what's working TODAY.
Limited-Time: 50% off the regular price
We keep these sessions interactive so you get your specific questions answered—no theory, no fluff—just practical implementation.
The Unsexy AI Revolution
How Traditional Businesses Are Quietly Building AI-Powered Empires While Everyone Else Chases Unicorns
I have always wanted to be an entrepreneur. I admired the likes of Walt Disney, Henry Ford, John D. Rockefeller, and, more recently, folks like Brian Chesky of Airbnb and Tony Hsieh, founder of Zappos. My favorite podcast is My First Million – where Sam Parr and Shaan Puri dissect business opportunities with the enthusiasm of kids trading baseball cards – and Codie Sanchez's Contrarian Thinking newsletter, which champions buying boring businesses that print money. I love how they find an edge in a business and exploit it for profit.
That’s why I think a largely overlooked opportunity—before we get more capable AI and robots—is to take boring businesses that are great at generating cash flow but lack the efficiency benefits of AI. While Silicon Valley chases the next GPT wrapper, the real arbitrage opportunity is sitting in plain sight: the plumber who still uses paper invoices, the landscaper juggling schedules on a whiteboard, the HVAC company drowning in service calls.
Growing up in a farming community, I've watched this transformation happen firsthand. Our local farmer switched from human navigation to GPS-guided tractors that can plant with sub-inch precision. He's not a tech guy, but he understood immediately that precision agriculture could increase his yields by up to 30%. If farmers in rural America can embrace AI-powered tools, what's stopping your local service business?
The $100K AI Arbitrage in Boring Businesses
Here's what the tech elite don't understand: A local roofing company doing $5M in revenue doesn't need AGI. They need AI that can:
Instantly quote jobs from drone footage – Companies like Eagleview provide AI-powered drone measurement tools that analyze aerial photos with 98.77% accuracy, cutting quote time from 2 hours to 10 minutes. Contractors using these tools report close rates jumping 30-40% because they're first to respond.
Predict equipment failures before they happen – ServiceTitan's Titan Intelligence helps HVAC companies predict which units are likely to fail based on service history and manufacturer data. One HVAC company reduced downtime by 30% and saved significantly on emergency repairs. They call customers proactively, turning emergency calls into scheduled maintenance at 3x the margin.
Turn every technician into your best technician – Streem provides AR-powered remote assistance that overlays repair instructions on live camera feeds. Plumbing and electrical companies report that junior techs can now handle complex jobs that used to require 20-year veterans. The technology reduced callbacks by 20% and improved first-time fix rates to over 90%.
The Boring Business AI Playbook
Here’s the opportunity I think applies to so many of those out of work in tech, and that they can bring to less technically adept industries. For most of us who worked in tech, we found a golden ticket. But in 2024, there were over 150,000 tech layoffs, and this year we’ve seen over one million from the likes of Amazon, Intel, and Google.
However, while high tech was the opportunity, the bigger opportunity is for these workers to apply their tech skills to companies with strong cash flow but that lack growth opportunities that could be sparked by tech. Here are some examples, but they are just a small sample of what’s possible.
Pool Cleaning Services: Companies are deploying route optimization AI that factors in chemical levels, weather patterns, and customer preferences. Pool Brain helps pool service companies reduce windshield time by up to 30% while increasing customer retention by handling problems before customers notice them. One Texas operation added 15 new routes without hiring additional technicians.
Pest Control: Rentokil Initial's PestConnect uses AI image recognition to identify pest species from customer photos, automatically generating treatment plans and compliance documentation. No more "I'll have to come look at it first" – quote and schedule in one interaction. The system has reduced inspection time by 50% and improved treatment accuracy.
Local Moving Companies: Yembo's AI-powered inventory system estimates box counts and truck sizes from video walkthroughs with 95% accuracy. Combine with dynamic pricing based on demand patterns, and you've got Uber surge pricing for moving day. Moving companies report 25% fewer trucks arriving under-equipped and 40% reduction in quote time.
Auto Repair Shops: Kukui's DRIVE platform includes voice-to-text AI that captures mechanic observations during inspections, automatically generates estimates, orders parts, and schedules follow-ups. Mechanics fix cars; AI handles everything else. Shops using the platform see average repair order values increase by 23%.
Landscaping Services: Companies like Aspire Software offer AI-driven job costing and crew management. One landscaping company in Ohio used predictive analytics to identify which contracts were unprofitable, adjusted pricing, and increased margins by 18% without losing a single customer.
Why This Won't Be Disrupted (Yet)
In the long term, we'll have more robots. But here's what the "everything will be automated" crowd misses: We'll still need skilled welders for highly precise work, HVAC technicians for complex diagnostics, and landscapers who understand local flora and aesthetics that an AI just doesn’t have.
We'll likely have robots to mow the yard, but will they have the knowledge to plan drought-resistant plantings for your specific soil type, microclimate, and planting zone? Will they trim your Japanese maple into the artful sculpture your HOA demands? Will they know that Mrs. Henderson wants her roses pruned just so because her late husband planted them?
Just like those GPS-guided tractors on the farm I grew up near – they plant with perfect precision, but you still need the farmer's expertise to know when to plant, what varieties match the soil, and how to hedge against the weather patterns that no satellite can predict. John Deere's autonomous tractors can till a field, but they can't decide whether this year's unusual rainfall means switching from corn to soybeans. This still requires decades of experience.
The businesses that win won't be the ones that try to replace humans with robots. They'll be the ones using AI to make their humans superhuman, and in industries that typically don't leverage information technology to gain leverage.
Here's the kicker that should make every private equity firm salivate: According to BizBuySell's Q3 2024 report, small service businesses typically trade at 2.2-3.8x EBITDA. Add basic AI automation that increases margins by 20%, and you're looking at an immediate valuation bump to 5-7x. That's not venture math – that's real money, absolute returns, minimal risk.
Constellation Software has proven this model works. The company rolls up vertical market software companies and has generated over 30% annual returns since 2006. Now imagine applying that same playbook to Main Street businesses with AI as the catalyst.
Take the example of Electric Sheep Robotics (ESR), which has refined a bold roll-up strategy—acquiring traditional landscaping firms to build a data-rich, AI-driven platform—and is now making its next leap via an acquisition by Oso Electric Equipment.
Electric Sheep’s model is sophisticated yet direct: buy well-run lawn-care and landscaping companies with existing cash flows, then overlay its AI platform and robotics (e.g., the “Ram” autonomous mower) to gradually replace manual labor, collect operational data, and improve efficiency. The goal: develop a large-world model for outdoor spaces and scale a robotics-augmented services business.
In October 2025, Oso Electric Equipment—an industrial electric power-equipment OEM—announced its acquisition of Electric Sheep Robotics, uniting Oso’s electric powertrain hardware with ESR’s autonomous-robotics software stack.
This isn’t the latest AI unicorn growing at all costs with profits in mind for the future. It’s bringing AI into the non-tech world. It’s taking a pervasive pedestrian problem like mowing the lawn and applying high-tech solutions.
Your Move
The entrepreneurs who win the next decade won't be the ones building AI alone. They'll be the ones who figure out how to deploy commodity AI into industries where "machine learning" still sounds like science fiction.
Find a boring business. One that's been run the same way since 1987. One where the owner still keeps customer records in a Rolodex. One that generates predictable cash flow but runs on duct tape and determination.
That's your opportunity. Not because you'll revolutionize the industry, but because you'll evolutionize it – 10% improvement here, 15% efficiency there, until suddenly you're running the most profitable septic cleaning operation in the Southeast.
The future isn't about replacing the trades. It's about giving them superpowers.
And right now, they don't even know those superpowers exist.
The total addressable market? There are over 600,000 plumbing, HVAC, and electrical businesses in the US alone, generating over $600 billion in annual revenue. Less than 15% have adopted any form of AI or advanced automation. That's a $500 billion opportunity hiding in plain sight.
This version of the AIE was getting a little long, and it sometimes gets clipped in webmail platforms like Gmail, so I put this week’s AI Toolbox and my killer AI as a reviewer prompt on the website to save your inbox.
Robotics is moving from experimental tech to practical utility. These systems can help large enterprises streamline operations, but they’re equally useful for organizations without deep technical teams. The common thread is simple: they reduce manual work, improve safety, and provide predictable results.
DJI Dock 2 + Matrice 3D/3TD - A fully autonomous drone-in-a-box that handles perimeter checks, inspections, and site monitoring. It gives teams reliable data without sending people into the field for routine tasks.
Boston Dynamics Spot - A mobile robot built for inspection rounds in plants, utilities, and large facilities. It catches issues earlier and keeps people out of hazardous or hard-to-reach areas.
Locus Robotics AMRs - Autonomous mobile robots that improve picking and replenishment without redesigning a warehouse. They scale fast and give operations teams a straightforward path to higher throughput.
Figure Humanoid Robot - A humanoid robot aimed at repetitive manufacturing and material-handling work. Early pilots show promise for tasks that benefit from mobility and human-like reach.
Tesla Optimus - A general-purpose humanoid still in early development but backed by serious investment and engineering talent. Long-term, it could provide a flexible automation option for a wide range of businesses.
From Hype to Production: Voice AI in 2025
Voice AI has crossed into production. Deepgram’s 2025 State of Voice AI Report with Opus Research quantifies how 400 senior leaders - many at $100M+ enterprises - are budgeting, shipping, and measuring results.
Adoption is near-universal (97%), budgets are rising (84%), yet only 21% are very satisfied with legacy agents. And that gap is the opportunity: using human-like agents that handle real tasks, reduce wait times, and lift CSAT.
Get benchmarks to compare your roadmap, the first use cases breaking through (customer service, order capture, task automation), and the capabilities that separate leaders from laggards - latency, accuracy, tooling, and integration. Use the findings to prioritize quick wins now and build a scalable plan for 2026.
One of my favorite uses for AI chatbots is to review my work. Most of the time, it catches things I miss or provides excellent feedback, but at the end of the day, it’s up to me to give the final editorial oversight. That’s called Human-in-the-Loop.
Here’s an example of how I use Claude and ChatGPT to edit everything from contributed articles to blog posts to even this newsletter.
Copy your complete text and start a new ChatGPT or Claude conversation. Paste the entire review prompt template into ChatGPT along with your text, either by cutting and pasting or by attaching a file. Before submitting, add any relevant context, such as "This is a blog post for executives," or specific areas you want emphasized.
The review takes 30-60 seconds and provides an overall score (1-100), a detailed evaluation of the criteria, fact-checking results, and specific improvements. Check the fact-checking section first for any errors, then review the actionable improvements and line-by-line corrections. Ask follow-up questions such as "Can you elaborate?" or "How would you rewrite this section?" to clarify.
Break texts over 2,000 words into sections for more focused feedback, and customize the prompt for your genre (academic, business, or creative writing). Run multiple review rounds after making revisions to track improvement and catch new issues. Save each review to monitor progress and create a revision checklist from recurring feedback patterns.
Writing Review and Evaluation Prompt
Please act as a professional editor and fact-checker. Review the following piece of writing and provide a comprehensive evaluation based on the criteria below.
Your review should include:
1. Overall Rating (1-100)
Provide a numerical score where:
90-100: Exceptional - Publication-ready with minimal changes
80-89: Excellent - Strong writing with minor improvements needed
70-79: Good - Solid foundation but requires moderate revision
60-69: Fair - Needs significant improvement
Below 60: Needs major revision
2. Evaluation Criteria (score each area 1-10):
A. Writing Quality (40% of total score)
Clarity and coherence
Grammar, spelling, and punctuation
Sentence structure and flow
Vocabulary and word choice
Tone consistency and appropriateness
B. Factual Accuracy (30% of total score)
Verify ALL factual claims, statistics, and data points
Check dates, names, and specific details
Identify any unsupported assertions
Note any outdated information
C. Structure & Organization (20% of total score)
Logical flow of ideas
Paragraph transitions
Introduction and conclusion effectiveness
Use of headings/subheadings (if applicable)
D. Engagement & Impact (10% of total score)
Reader engagement
Persuasiveness (if applicable)
Originality and fresh perspective
3. Detailed Feedback Section:
Strengths: List 3-5 specific things the piece does well
Critical Issues: Identify any major problems that must be addressed
Fact-Check Results:
List each factual claim with verification status (✓ Verified, ✗ Incorrect, ? Unable to verify)
Provide correct information for any errors
Actionable Improvements:
[Specific suggestion with example]
[Specific suggestion with example]
[Specific suggestion with example]
(Continue as needed)
Line-by-line corrections: Point out specific sentences or paragraphs that need revision and suggest rewrites
4. Summary:
Provide a 2-3 sentence summary of your overall assessment and the most important next steps.
Pro Tip: You could codify this into a Custom GPT so all you have to do is upload an article or cut and paste it in.
I used the prompt above to improve this newsletter, note that I started with a 82/100 but I am striving for a 95/100 or better.
I appreciate your support.
Your AI Sherpa,
Mark R. Hinkle
Publisher, The AIE Network
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