Small Business Big AI

Kim Lewis Howard
  • 5.0 (6)
  • Entrepreneurship
  • Updated Weekly

Small Business Big AI explores how artificial intelligence is transforming the entrepreneurial landscape. Hosted by Kim Lewis Howard, we provide actionable insights and practical strategies for small business owners looking to leverage AI and stay ahead in today’s competitive world.

  1. 3d ago

    Behind on AI After 99 Episodes: He Came Home with a Plan. I Came Home with a Question.

    Ninety-nine episodes of telling business owners to build theengine. Then we got on a plane. Kim and Hal spent three days in Venice Beach, California with a group of engineers and mathematicians who build AI-native operating systems for a living. They sat in the same rooms, watched the same demonstrations, and flew home on the same red-eye. He came home with a task list. She came home with a question. At dinner one night, a mathematician mentioned that his AIagent was building something on Kim's laptop, back in the hotel room, right then. She went back and opened it. Same desktop. Same icons. Nothing running. Not even a spinning circle. Hal heard that same sentence and it was the greatest news of the trip. This is the honest version of the hundredth episode, including the part where Kim names the title she promised on episode 98 and could not keep. It ends where Hal accidentally started it: with a job description, one page per person, free, and available Monday morning. In this Episode The hotel room, the laptop, and the completelyordinary explanation for why nothing was on the screen.Why Kim was watching the screen and Hal waswatching the people, and what he saw that she missed.Context rot, front matter, and why the unglamorous thing turned out to be the foundation.Hal's admission: I didn't understand anything. I just kept going with it. Ready to Take Action Watch what an AI-native agency looks like from the inside: https://AskLewisHoward.comSmall Business Big AI:https://smallbusinessbigai.com/Kim Lewis Howard on LinkedIn:https://www.linkedin.com/in/kim-lewis-howard/Hal Howard on LinkedIn:https://www.linkedin.com/in/halhoward/---Q: Where should a small business start with AI? A: Not with a tool. Start by writing a one-page job descriptionfor every person in the business, describing what they actually do all day rather than what the org chart says. Put four questions on the page: what this person touches every single day, what they do once a week and dread, what only they know how to do that nobody else could pick up tomorrow morning, and what they get asked over and over that they wish they never got asked again. That last one is usually where the money is. This costs nothing, requires no software, and can start Monday with a legal pad. It matters because you cannothand an AI system a knowledge base, a context graph, or a set of instructions until somebody has written down what actually happens inside your business. The documentation is not a prerequisite to the AI project. It is the AI project's first deliverable. --- MUSIC & SOUND CREDITS Music: "I Am with You" by Dream Cave; Epidemic Sound via iStock.com Sound Effects: https://pixabay.com/sound-effects/

    Behind on AI After 99 Episodes: He Came Home with a Plan. I Came Home with a Question.

  2. Jul 28

    If Clients Knew AI Did 80% of the Work, Would They Still Pay You?

    If your clients discovered that artificial intelligence did 80 percent of the work you charged them for... would they still pay you? Kim asked Hal for the honest answer. She got it: “Some of them wouldn't.” And clients are already asking the dangerous little question — “If AI helped you do this faster, why am I still paying the same price?” — challenging billable hours, questioning research charges, even writing AI clauses into contracts. Sooner or later, that question is coming for your invoice. ---Q: Should I tell my clients that I use AI to do their work?A: Yes — but as positioning, not confession. Transparencydoes not mean walking clients through your software stack; it means clearly stating where the value comes from: “We have developed a process that allows us to complete this faster, identify problems earlier, and create a more consistent result. The technology increases our speed. Our expertise determines what should happen next.” Clients will discover the machinery exists — from a competitor's demo, a video, or their own employee's lunch-break experiment. You don't get to choose whether they discover it; you only get to influence what the discovery means. Businesses that hide automation risk the client finding out last, which is what turns a process change into a felt betrayal. Q: What is the AI discount, and how should a service business respond?A: The AI discount is the growing client expectation that ifartificial intelligence compressed the work, the client should receive the savings — showing up as fee challenges, questioned research charges, and contract language returning “AI economics” to the buyer. The exposure comesfrom hourly pricing: if your invoice says the client is buying twelve hours and the work now takes forty-five minutes, the invoice becomes “a confession waiting to be read.” The response is not to hide the tooling but to stop selling hours: price the outcome, and build a credible explanation of what the client is actually paying for — judgment, accountability, licensed expertise, and someone who recognizes when the machine is confidently wrong — before the demand arrives. Q: How do I price my services when AI does most of the work?A: Price the outcome, not the effort. Clients were nevertruly buying hours — hours were simply the easiest thing to count. They are buying avoided mistakes, better decisions, protection, speed without recklessness, and someone credible standing beside the result. Practical sequence from the episode: rewrite one proposal this week with the hoursremoved and the outcome priced, and see what breaks — if you struggle to explain the outcome, that is useful information. Then understand your own engine before scaling the change: what it actually costs to deliver, where human time goes, where technology saves money, and where it creates new risk. You cannot price an outcome intelligently if you do not understand your own cost to produce it. Ready to Take Action Website: https://smallbusinessbigai.com/Kim Lewis Howard on LinkedIn:https://www.linkedin.com/in/kim-lewis-howard/Hal Howard on LinkedIn:https://www.linkedin.com/in/halhoward/Insurance for builders, built by builders —Lewis Howard Insurance Group opens August 2026: https://AskLewisHoward.com ---MUSIC & SOUND CREDITS Music: "I Am with You" by Dream Cave; Epidemic Sound via iStock.com Sound Effects: https://pixabay.com/sound-effects/

  3. Jul 21

    The SaaS-pocalypse Is Here: Who Gets Rich and Who Gets Erased

    Right now, all over the internet, people are celebrating.Canceling software. Screenshotting the receipts. Posting them like trophies — while the headline floats overhead: “$285 billion in software value... gone.” Everybody thinks that’s the story. It isn’t. The money didn’t disappear. It moved. And there’s a line being drawn through every small business right now:one side gets erased, the other side gets rich. In this Operator’s Playbook, Kim and Hal break down whatactually broke (per-seat pricing, not the software — an AI agent never logs in, so the seat became a tax), where the value went (down the stack, to the owned data layer and the agent loops on top of it), and the new shape of companyalready walking around: under five employees, seven-figure revenue, 60–80% margins. The dashboard was never the asset. The stuff underneath it was. Then the dividing line. Hal defends the cutters — cancelingsix unused tools is real money, this month, no consultant. Kim isn’t against the cutting; she’s against the stopping. Savings isn’t a moat. Nobody ever out-saved a competitor who out-built them. The episode turns on one question:is your business built to sell human hours that software is actively compressing, or positioned to own the automated engine of execution? The playbook lands in three moves — the Seat-to-Token audit,one owned semantic vault (last week the Archivist filled it; this week the engine runs on it), and Zero-Based Process Redesign on a single workflow. And then Kim slows down: everything she just described, she’s about to go build. This episode airs while she and Hal are on the ground in California with Science Stanley, constructing exactly this engine for their own agency — guardrails poured with the foundation, live runtime telemetry from day one. It powersLewis Howard Insurance Group, AI-native from the first policy, opening August 2026 at AskLewisHoward.com. In this Episode What the $285B headline gets wrong — value moved, it didn’t vanishWhy per-seat pricing collapsed: agents don’t log inDown the stack: the data layer and agent loops where the value landedThe new shape of company: under five people, seven figures, 60–80% marginsCutters vs. builders — and why Hal defends the cutters"Savings isn’t a moat” — the one moment wheredefense losesAgent sprawl: six agents with no shared truth is chaos on autopilotThree moves: Seat-to-Token audit · one semantic vault · redesign one workflow from zeroThe California build: Kim and Hal fly out to construct their own engine — it airs while they’re on the groundLewis Howard Insurance Group: insurance for builders, built by builders — opens August 2026--- Q: What is the Saaspocalypse?A: The Saaspocalypse is the ongoing correction in thesoftware-as-a-service industry — roughly $285 billion in SaaS market value lost as per-seat subscription pricing collapses. The cause is AI agents: an agent doesn’t log in, so paying per human seat became an inefficiency tax. SaaS multiples compressed to around 23x earnings, legacy vendor growth decelerated toward 10% a year, and buyers began demanding usage- and outcome-based pricing. But the value didn’t vanish — it moved down the stack, from rented dashboardsto the owned data layer and the agent loops that run on it. For small businesses, that makes the Saaspocalypse a construction event, not a cancellation event. --- MUSIC & SOUND CREDITS Music: "I Am with You" by Dream Cave; Epidemic Sound via iStock.com Sound Effects: https://pixabay.com/sound-effects/

  4. Jul 14

    The Archivist: The New Job AI Just Created Inside Your Small Business

    AI didn’t delete the work. It relocated it — andthe new address is inside your head.95% of AI projects fail. Not because the modelis dumb — because nobody did the capture work first.Enterprises went from 11% to 56% in two years.Small business has the same need and no name for it. Here’s the name. For two years, small business owners have heard one storyabout AI: it’s here to take the jobs. Kim and Hal open this Operator’s Playbook by taking that fear seriously — and then flipping it. The same force deleting jobs has quietly created one, and it’s already sitting inside your company. They name it: the Small Business Systems Archivist, the role that converts a founder’s in-their-head knowledge into clean, agent-ready context. It’s the most important hire you’ll never post. The episode is built on a number. Research out of MIT — theNANDA report — found that roughly 95% of companies deploying generative AI saw no measurable impact on the bottom line. The instinct is to blame the tool. Kim and Hal argue that’s the wrong diagnosis. The projects didn’t fail because the model was weak; they failed because the founder’s judgment never left the founder’s head. The AI was sitting there, ready to work, running on nothing. If your AI feels like a needy intern, it isn’t the model — it’s the model runningblind, because nobody gave it the context to run on. Hal grounds the argument in lived P&L. He ran a multi-million-dollar car franchise dealership for years, and his sharpest salesmanager kept every deal in his head — until the Friday he didn’t come in, and eight people couldn’t do a job that was never written down. That’s the 95% problem in one story: the business depended on a person, not a system. The fix is the archivist, who captures four things — decisions (and the why behind them), SOPs, customer judgment, and your voice — not with a new system, but with a weekly habit. The peak lands when Kim makes it personal and live. She’s ona plane to California to sit with Stanley and a group of engineers and build a context graph — archiving her own decisions, patterns, judgment, and voice so an AI-native agency can run on it. She’s doing the exact work she’s askingoperators to do. As Hal puts it, an AI can generate a podcast that sounds like this one — but it cannot get on the plane. That’s the human part, and it’s the whole game. From there the hosts make the strategic turn: capturedcontext isn’t just operational, it’s a moat and it’s equity. As AI models become a commodity, the engine stops being the advantage — the fuel does. Your decisions, your customer history, your judgment are the one thing a competitor can’t download. As the AI-native counter-example, Kim points to Lewis Howard Insurance Group, opening August 3, 2026, with the archivist function baked in from day one. The playbook closes with three moves for the week: name your archivist, get off the free plan, and redesign one process from zero. Thetakeaway: the archivist isn’t a threat to fear. It’s the work, relocated, waiting for you to claim it. Ready to Take Action Website: https://smallbusinessbigai.com/Kim Lewis Howard on LinkedIn:https://www.linkedin.com/in/kim-lewis-howard/Hal Howard on LinkedIn:https://www.linkedin.com/in/halhoward/ Building it AI-native from day one — Lewis Howard Insurance Group opens August 3, 2026: https://AskLewisHoward.com ---MUSIC & SOUND CREDITS Music: "I Am with You" by Dream Cave; Epidemic Sound via iStock.com Sound Effects: https://pixabay.com/sound-effects/

  5. Jul 7

    Who Really Owns Your Customer Relationship in the Age of AI?

    You think you own your business. You log into the CRM, youexport the spreadsheet, you watch the follower count climb — and it feels like ownership. In this Coffee Table Conversation, Kim and Hal make the case that most of it is rented, and that AI just raised the stakes on the difference. It starts with a line Kim said to a friend that landed harder than she meant it to: you didn’t build a business, you furnished anapartment in someone else’s building. From there, the two of them work through the uncomfortable middle of the data-versus-relationship debate — Kim defending the context that makes your AI yours, Hal defending the relationship that walks out the door with you — and a cloud-provider story about one missed payment that should make every operator check whose name is really on the lease. The turn that reframes the whole thing: data and relationship don’t just differ, they fail differently — and most owners areprotecting neither. The answer isn’t to pick a side. It’s portability. Can you walk out the door with your business intact? In This Episode Why access isn’t ownership — and why that gap is now existentialThe cloud-provider story: one missed payment, everything goneData vs. relationship: two assets that fail in completely different waysOwnership as portability — the test that actually mattersChatbot vs. agent — and why owned context is thewhole moatThree light moves to start owning a portable context asset this weekReady to Take Action Website: https://smallbusinessbigai.com/Kim Lewis Howard on LinkedIn:https://www.linkedin.com/in/kim-lewis-howard/Hal Howard on LinkedIn:https://www.linkedin.com/in/halhoward/Building it AI-native from day one — LewisHoward Insurance Group opens August 3, 2026: https://AskLewisHoward.comQ: What is the difference between an AI chatbot and an AI agent?A: A chatbot answers a question; an agent takes a job — itfollows up, books the meeting, watches for the renewal, and moves the work forward. The catch is that an agent only does work nobody can copy when it runs on your context and your memory. A generic agent on generic data does genericwork. Your agent, pointed at what only your business knows, becomes a durable, owned advantage. Q: How do I know if I actually own my business assets?A: Use the portability test: if your platform disappearedtomorrow, what walks out the door with you? Ownership isn’t having the most data or the deepest relationship — it’s whether you can leave with your business intact. Three quick moves: (1) list every system holding your customer data and ask what walks with you versus what stays on their server; (2) start a portable context asset you control; (3) point one AI agent at that owned context. Q: What does it mean to "rent" your business?A: Renting your business means building your entire operation — your audience, customer data, relationships, and follow-up systems — inside platforms you don’t own, such as a CRM, social network, or cloud provider. You have access, but the platform holds the asset. The risk becomes existential when AI is built into those platforms, because they now learn fromyour data continuously. If your account is suspended or the platform changes its rules, the accumulated memory of your business can disappear overnight. --- Music: "I Am with You" by Dream Cave; Epidemic Sound via iStock.com Sound Effects: https://pixabay.com/sound-effects/

  6. Jun 30

    The 6-Hour Tax: Why AI Costs You More Than It Saves

    You bought the AI to get your life back. So why did it quietly book your weekend? There’s finally a number on it. The Glean Work AI Index (June 2026) found AI gives the average operator about 11 hours a week back — and then takes roughly 6.5 of them right back in supervision. Checking. Correcting. Re-prompting. Cleaning up. It even has a name now: botsitting. Kim calls it the six-hour tax. In this Coffee Table Conversation, Kim and Hal make the case that the tax isn’t an AI problem — it’s an architecture problem. You can’t automate a workflow you never redesigned. And the fix isn’t a six-month transformation initiative. It’s one decision, made one time, about one workflow. What they cover: ·        The Glean Work AI Index numbers — 11 hours saved, 6.5 hours of botsitting — and why the cost falls on your mostconscientious people ·        Why using AI like “an intern who never learns” keeps you fixing the same draft every week ·        The reframe that lands the episode: architecture isn’t a department — it’s a decision ·        The one question that turns a bolt-on into a redesign ·        The three moves to stop paying the tax this week: find the memory, redesign one workflow, build a context asset ·        A live case study: Lewis Howard Insurance Group, opening August 3 — built AI-native from day one Referenced in this episode: ·        Glean Work AI Index, June 2026 (11 hrs saved / 6.5 hrs supervising / heaviest “botsitters” more likely to be job-hunting) ·        Lewis Howard Insurance Group — opening August 3,2026 (AI-native case study) Learn the IMPACT Framework:https://smallbusinessbigai.com/ Kim on LinkedIn:https://www.linkedin.com/in/kim-lewis-howard/ Hal on LinkedIn:https://www.linkedin.com/in/halhoward/ Website: SmallBusinessBigAI.com Q: What is the “six-hour tax” in AI for small business? The six-hour tax is the gap between the time AI saves you and the time it takes back in supervision. According to the Glean Work AI Index (June 2026), AI gives the average operator about eleven hours a week back but consumes roughly six and a half of them in “botsitting” — checking, correcting, re-prompting, and cleaning up after the tool. The net gain is only four to five hours, and the cost falls hardest on your most conscientious people. Q: Why does AI make some small businesses busier instead of saving time? Because most operators bolt AI onto a workflow they never redesigned. They use AI like an employee they neveronboarded: the corrections never compound, so they fix the same output every week. A real hire gets cheaper to supervise over time because corrections become training; AI in an un-redesigned workflow starts at month one everymorning. The fix isn’t a better tool — it’s redesigning the workflow so learning has somewhere to live. Q: How do you redesign a workflow to be AI-native without a big transformation project? You don’t re-architect the whole business. You pick one workflow — usually the one marked by the sentence “Icould’ve just done it myself” — and ask a different question: “If AI had existed the day I built this, how would I have shaped it?” Then you build the guardrails (parameters) into the workflow itself instead of relying on a person to be the only quality check. It’s one decision about one workflow, not a six-month initiative. Q: What is a context asset and why does it matter more than the AI tool? A context asset is a living document that tells the AI how your business thinks: your tone, pricing rules, approval thresholds, customer promises, what you never say, what you alwayscheck, and examples of great and bad work. It matters more than the tool because everyone can buy the same AI subscription this afternoon — but no competitor can buy your standards, your customer history, or your judgment. Thetool isn’t the advantage. Your context is. --- Music Credit: “I Am with You” by Dream Cave; EpidemicSound via iStock.com Sound Effects: https://pixabay.com/sound-effects/

  7. Jun 23

    The AI-Native Business: Stop Chasing Tools and Build What Competitors Cannot Copy

    Every small business owner is asking the same question rightnow: “Which AI tool should I be using?” Kim Lewis Howard says it’s the wrong question. And she has a better one. In this episode, Kim and Hal make the case that the businesses winning in an AI economy are not the ones with the best tools. They are the ones who figured out what they have that AI cannot replicate for a competitor — and then used AI to protect and amplify it. What they cover: •   Why the AI tool treadmill is keeping operators busy without making them competitive •   The “blimp vs. launch platform” framework and why mostsmall businesses are building in the wrong order •   The four assets that compound in an AI economy: proprietary knowledge, earned judgment, trusted relationships, and point of view •   Why trust is becoming more scarce — and more valuable —as execution gets cheaper •    A live case study: Lewis Howard Insurance Group,opening August 3, and how AI-native architecture actually works in a local service business •    The amplification test: one question to ask before any AI tool purchase Referenced in this episode: •      Joe Procopio, “You Don’t Need AI Agents,” Inc./MSN,June 2026 •      McKinsey 2026: From AI Table Stakes to AI Advantage •      Edelman Trust Barometer 2026 •      Insurance Journal, May 2026: What AI Cannot Replicatein Insurance   Learn the IMPACT Framework: https://smallbusinessbigai.com/ Kim on LinkedIn: https://www.linkedin.com/in/kim-lewis-howard/ Hal on LinkedIn: https://www.linkedin.com/in/halhoward/ Website: SmallBusinessBigAI.com   Q: What is an AI-native business? An AI-native business is not a regular business with AI toolsadded on top. It is a business designed differently from the beginning — with different workflows, different decision-making structures, different data strategies, and clear lines between what humans should do and what machinesshould do. The distinction matters because most small businesses are building on top of weak foundations. AI amplifies what is already there. If the foundation is fragile, the amplification accelerates the problems, not the progress.   Q: Why can’t small businesses compete on AI tools? Because tools are increasingly available to everyone. By thetime you discover an AI tool worth using, your competitor can access the same model via an API call. Features get copied overnight. Workflows get replicated in weeks. Entire product categories emerge in months. McKinsey research confirms that the AI model itself is no longer a defensible competitiveadvantage — the strategic battleground has shifted to what surrounds it. Competing on tools is a temporary advantage at best, and a distraction from building real moats at worst.   Q: What are the four irreplaceable assets in an AI economy? The four assets that compound over time — and that AI canamplify but not create for a competitor — are: (1) Proprietary knowledge: your customer history, operating patterns, and institutional memory that no competitor can download. (2) Earned judgment: the scar-tissue advantage that comes from making real decisions with real consequences over years. (3) Trusted relationships: increasingly scarce and valuable as execution becomes automated, trust is the asset that keeps clients when a competitor undercuts on price. (4)Distinct point of view: the perspective that makes someone choose you specifically, not just the nearest available option.  --- Music Credit: “I Am with You” by Dream Cave; EpidemicSound via iStock.com Sound Effects: https://pixabay.com/sound-effects/

  8. Jun 16

    The Agentic Customer and the Human Advantage We Cannot Afford to Lose

    What happens when your next customer never calls, never fills out the form, never reads your About page — becausetheir AI agent does it for them? In Episode 93, Kim Lewis Howard and Hal Howard close the Systemized or Squeezed series with the most forward-looking conversation of all four weeks. This is a Coffee Table Conversation— Kim and Hal thinking out loud at the edge of what they know, naming what theycan see and admitting what they cannot. Kim introduces the agentic customer shift and the two-interface business: one interface for intelligence that evaluates (clear, structured, machine-readable), and one for humans who feel (warm, trustworthy, emotionally present). The trap, she warns, is building a business that is machine-readable and human-forgettable. But the most surprising turn is this: the agentic shift may make the human relationship more valuable, not less. When the agent strips away the commodity layer, what remains is interpretation, judgment, and the moment a human says, "I've got you." That moment is not a break in the process. That moment is theproduct. Kim closes by admitting she doesn't fully know how to build for this yet. That honesty is the most important thingshe says in four episodes — and the right leadership posture for a shift this significant.   WHAT YOU'LL LEARN IN THIS EPISODE •  Understand the agentic customer shift — what it meanswhen your customer's AI evaluates your business before the human does • Apply the two-interface framework: one interface thatreduces confusion for machines, one that reduces anxiety for humans •  Recognize the machine-readable, human-forgettable trapbefore you build yourself into it •   Understand why the agentic shift makes the humanrelationship more valuable, not less — and what that means for service businesses •  Hear Kim's honest admission: she doesn't fully know howto build for this yet — and why that posture is the right one •  Walk away with the one question that should shape howyou build your business right now Q: What is the agentic customer shift? The agentic customer shift is the emerging pattern in which customers delegate evaluation and purchasing tasks to AI agents before making a decision themselves. The agent may review your website, compare pricing, check reviews, assess response speed, and parse your offer language — all before the human enters the conversation. For small businesses, this means the first pass of the customer relationship may bemachine-to-machine. Businesses that cannot be clearly understood and evaluated by these agents risk being eliminated before the human ever sees the shortlist. Q: What is a two-interface business? A two-interface business is designed to serve two distinct audiences: intelligence that evaluates, and humans who feel. The agent interface needs structure, clarity, and machine-readable information — your offer, response standards, proof, and differentiation. The human interface needs warmth, story, voice, and trust. One interface reduces confusion. The other reduces anxiety. Most small businessesare not yet designed for either. Q: Why does the agentic shift make the human relationship more valuable? When AI agents handle the evaluation layer — price comparisons, response time, reviews, measurable proof— the human interaction that follows becomes premium. The client already has the data. They are not coming to you for information. They are coming for interpretation, judgment, and reassurance. A machine can compare the policy. Ahuman can hear the tremble underneath the question. That human moment becomes the competitive advantage — not a cost center to be automated away.   Connect Kim Lewis Howard: linkedin.com/in/kim-lewis-howard Hal Howard: linkedin.com/in/halhoward SmallBusinessBigAI.com

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About

Small Business Big AI explores how artificial intelligence is transforming the entrepreneurial landscape. Hosted by Kim Lewis Howard, we provide actionable insights and practical strategies for small business owners looking to leverage AI and stay ahead in today’s competitive world.

Information

  • Creator
    Kim Lewis Howard
  • Years Active
    2024 - 2026
  • Episodes
    100
  • Rating
    Clean
  • Copyright
    © Kim Lewis Howard
  • Show Website
    Small Business Big AI

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