AI leaders have 1.6x higher EBIT margins than businesses that have not moved yet on this.

Not 1.1x. Not a rounding error. One point six times the margin. That gap compounds every quarter, and the research says it is widening, not narrowing.

Here is what is important to understand: BCG is not talking about tech companies or Fortune 500 giants. The pattern holds across sectors. The businesses pulling ahead are not smarter or better capitalized. They are just running leaner.

So what are they actually doing differently?

They closed three specific overhead leaks that most owners are still ignoring.

Leak 1: Administrative time.

The average small business owner spends 15 to 30 hours per week on administrative tasks. Scheduling. Email triage. Document prep. Data entry. That is nearly a full-time job worth of output, and none of it is billable or strategic.

One fix: an AI system that monitors your inbox, categorizes each message by urgency, and drafts appropriate responses. For a team of five, that one change alone saves 8 to 12 hours per week. More than a full workday per person, every single week, handed back to the work that actually grows the business.

Leak 2: Customer service capacity.

AI handles up to 80% of common customer queries without a human involved. For service businesses running support, that translates to $80,000 to $200,000 per year in avoided cost at the mid-market level.

For smaller businesses, the math still works. Even at one-tenth the scale, that is $8,000 to $20,000 back annually. And response times go from hours to seconds, which tends to improve retention on its own.

Leak 3: Finance and back-office operations.

Invoicing, collections, reconciliation, report generation. Businesses automating these workflows are cutting finance overhead by 40 to 60 percent. Not by cutting staff. By removing the manual steps that sit between work getting done and money coming in.

Time-to-payment shrinks. Errors disappear. The finance function starts running itself in the background while you focus on clients and revenue.

The cost to get started is not what people expect.

For a business doing $500,000 in annual revenue, a proper AI toolkit runs $1,000 to $1,500 per year. That is roughly what some businesses spend on office supplies.

The average ROI from AI in business operations lands between 3x and 5x within the first 12 to 18 months. For businesses that move quickly and implement correctly, payback typically hits somewhere between month three and month six.

The businesses on the wrong side of that BCG margin gap are not falling behind because of talent or product quality. They are falling behind because they are paying people to do things AI handles better and faster, and the cost of not changing is now visible in their P&Ls.

Here is the honest question to sit with this weekend:

How many hours did you or your team spend this week on work you wish you could hand off?

If the answer is more than 10, you are looking at a solvable problem. And the solution costs less than most business owners assume.

At Mudd Ventures, the first thing I do with a new client is run an overhead audit. We identify the three or four workflows where AI creates the fastest payback, then we build them out without a tech team or an enterprise budget.

If you want to know where your overhead leaks are, reply to this email and tell me what you are spending the most manual time on each week. I read every response and I will tell you honestly whether AI can fix it.

To a leaner operation,

Andrew

p.s. If someone in your network would benefit from this, forward it to them. Takes three seconds. Might save them a lot more than that.

Here is what it does in plain English. You define what you want an AI agent to do. You tell it what tools it has access to. Anthropic runs it for you in a secure container on their servers. You do not need to set up infrastructure. You do not need a DevOps team. You do not need to figure out how to keep a long-running AI process alive and monitored.

Before yesterday, if you wanted to build an AI agent that could actually do work on its own, you needed engineers. You needed to handle sandboxing, error recovery, credential management, logging, and about a dozen other problems that have nothing to do with the actual task the agent performs.

That barrier just got a lot lower.

What this looks like in practice

Notion is using it to let their users ship code and build presentations from inside their workspace. Rakuten stood up enterprise agents across sales, marketing, finance, and HR in a week per department. Sentry paired it with their debugging tools so a flagged bug flows straight to a reviewable code fix.

These are not startups experimenting. These are production deployments at companies with millions of users.

The pattern is the same every time. Define the agent. Give it the right tools. Let it run. Monitor the results.

Why this matters if you run a small business

Right now, the small business version of an AI agent is a Zapier automation or a Make workflow. Those are useful. I recommend them constantly. But they are rigid. They follow a fixed path. If something unexpected happens, the automation breaks.

What changes with managed agents is the reasoning layer. An agent can look at a problem, decide what steps to take, try something, check if it worked, and adjust. That is closer to what a human employee does. Except this one costs $0.08 per session-hour of runtime plus standard token pricing.

The gap between what a Fortune 500 company can deploy and what a five-person business can deploy just got smaller. Not because the technology is simpler. Because the infrastructure overhead disappeared.

What this costs

The runtime fee is $0.08 per agent session-hour. That is eight cents. You are charged in milliseconds of active time. Idle time does not count. Web search is $10 per 1,000 searches. Token pricing is the same as the standard Claude API.

For comparison, a marketing agency charges $75 to $400 per hour for a human to do work that an agent can increasingly handle. A virtual assistant costs $15 to $35 per hour. An AI agent doing focused, well-defined work costs pennies per hour.

I am not saying agents replace people. I have said this before and I will keep saying it. But for repetitive, structured work with clear inputs and outputs, the cost math is getting hard to ignore.

What you should actually do with this information

You do not need to go build a managed agent tomorrow. This is still early. It launched yesterday. It is in beta.

But here is what I would do. Look at your current workflow automations. The Zapier zaps. The Make scenarios. The manual processes your team runs every week. Ask one question: which of these would work better if the automation could think and adapt instead of just following a script?

That list is where agents are headed. Not next year. Now.

The businesses that figure out which tasks to hand to agents early are going to have a structural cost advantage that compounds every month. Not because they are smarter. Because they paid attention when the infrastructure barrier came down.

Andrew Mudd
Mudd Ventures

P.S. If you want to talk through where agents fit in your specific business, that is exactly what the consulting call is for. Book one at muddventures.com/book

The average small business pays between $2,500 and $8,000 per month for a marketing retainer. That is $30,000 to $96,000 a year. For most small businesses, that is one of the biggest line items in the budget.

What does that actually buy you?

Usually, four to eight social media posts per month. Two or three emails to your list. Maybe a blog post. A monthly check-in call where you review a report full of impressions and reach numbers that do not pay your rent.

I am not saying every agency is bad. I am saying the math has changed dramatically. And most agencies have not told you.

What the same work actually costs today

Last month, a business owner documented replacing a $2,069 per month software stack with seven AI tools for a combined $35 a month. That is a $24,000 annual savings. Same output. Faster delivery.

Those tools now handle writing and editing, design, presentations, video editing, research, voice and audio, and workflow automation. All replaced with free-tier or near-free AI tools that would have cost thousands a month just two years ago.

The story is the same on the marketing execution side.

AI-powered marketing tools are delivering 25 to 45 percent higher ROI compared to traditional agency approaches. Campaign launch time has compressed from the industry standard of two to six weeks down to same-day or three days. AI-based lead scoring is improving conversion efficiency by 31 percent on average.

And the monthly cost to access these tools? About $49 to $99.

Compare that to the $3,000 to $10,000 monthly retainer many agencies charge for the same content production, the same email campaigns, the same SEO execution work.

This is not an argument to fire everyone

Here is where I want to be straight with you, because this matters.

Agencies do things AI cannot do. They can develop a brand strategy from scratch. They can manage relationships with media contacts and distribution partners. They provide accountability and experienced human judgment when a campaign goes sideways in ways that an AI tool cannot diagnose or fix on its own.

If your agency is doing those things, and you have data that proves it is working, keep paying for it.

But if your agency is primarily responsible for production work, posting content, writing emails, managing your ad account at 15 percent of ad spend, and you have been paying that invoice on autopilot for years, it is time for an audit.

The marketing benchmark most advisors use is 7 to 12 percent of gross revenue. At $1 million in annual revenue, that is $70,000 to $120,000 a year. If most of that is going to agency fees for commodity production work that AI can now handle in an afternoon, you are funding someone else’s business instead of growing your own.

A 30-minute audit you can run right now

Pull up your last three months of marketing invoices. List every deliverable you actually received. Then answer one question honestly: could an AI tool, with clear direction from you or a part-time contractor, produce that same output?

For most business owners, the answer for the majority of deliverables is yes.

For the tasks that require strategy, creative judgment, media relationships, or genuine expertise, the answer is no.

The split between those two lists is your roadmap.

The commodity work moves to AI tools. The strategic work stays with experienced humans, and you can afford to pay those humans better once the production budget stops eating everything else.

The number that puts this in perspective

For every dollar invested in marketing automation, businesses are seeing an average of $5.44 in return. The businesses making this shift are also reporting that 63 percent of them outperform their competitors after the switch.

You do not need to blow up your marketing operation to capture some of that. You need a clear-eyed look at what you are paying for versus what you are actually getting.

Audit the invoice. Separate strategy from production. Price them separately.

Most business owners who do this exercise find they are paying agency rates for work that should be costing them a fraction of what they spend today.

That is Real Talk.

Andrew Mudd

Mudd Ventures

P.S. If this was useful, forward it to one business owner who is still signing the same marketing retainer they signed in 2022. They need to see this math.

The average small business loses $126,000 a year to missed calls.

Not to bad service. Not to slow fulfillment. To the phone ringing and nobody picking up.

The study goes further. 85% of callers who do not reach you on the first try will never call back. 62% of them go straight to a competitor. So every time your phone rings at 7 PM on a Thursday and you are in the middle of something, you are not just losing that call. You are losing that customer, probably forever.

I have talked to enough business owners at this point to know that most of them do not think of missed calls as a revenue problem. They think of it as an inconvenience. That framing is expensive.

Here is the problem in plain numbers.

If you run a home services business and your average job is worth $400, you only need to miss 25 jobs a year for missed calls to cost you $10,000. Miss 100 and you are at $40,000. Most owner-operated service businesses are missing far more than that, especially outside business hours, during peak periods when the team is stretched, and on weekends.

This is a solvable problem. And it is cheaper to solve than most people think.

What the tools actually cost

There are three tiers here. I will walk through all of them because the right answer depends on what you actually need.

Tier 1: Turnkey AI answering services. $29 to $199 per month.

These are plug-and-play. You set up a phone number, you train the AI on what your business does, and it answers calls, handles common questions, takes messages, and in many cases books appointments directly into your calendar. No developers needed.

Dialzara starts at $29 per month and handles inbound calls, takes messages, and sends you a summary. My AI Front Desk is $199 per month with unlimited calls, custom scripting, and direct calendar booking. NextPhone runs in the same range at $199 for unlimited.

These are not sophisticated. They will not replace a nuanced conversation. But for a plumber who misses 40% of evening calls? This solves the problem.

Tier 2: Build your own with Vapi. $50 to $300 per month depending on volume.

This is the option I use and recommend to clients who want more control. Vapi is the voice AI layer. You pair it with Deepgram for transcription, ElevenLabs or Cartesia for natural voice output, and a language model of your choice, Claude or GPT-4o, for the actual conversation logic. You connect it to your CRM, your calendar, your follow-up workflows.

The headline rate for Vapi is $0.05 per minute. Real all-in cost with all the component services runs $0.20 to $0.30 per minute. For a business getting 300 minutes of AI-handled calls per month, that is $60 to $90 in usage. Add a phone number and your base subscriptions and you are in the $100 to $200 per month range for a genuinely capable, custom-scripted AI voice system.

This path requires some setup time. It is not a 30-minute project. But once it is running, it handles your call flows exactly the way you want them handled, integrates with everything else in your stack, and costs a fraction of the alternative.

Tier 3: An agency builds and manages it for you. $2,000 to $8,000 per month.

This is the tier most of you have been quoted if you have explored this at all. The setup fee alone is typically $1,500 to $5,000. Then the retainer.

What are they building for you? In most cases, it is Vapi on the backend. Sometimes a white-labeled version of one of the turnkey tools I just described. Wrapped in a dashboard they own and a monthly management fee for doing almost nothing once the initial configuration is done.

The tools are the same. The price is not.

How to think about which tier is right for you

If your call volume is low, you are not technical, and you just need to stop missing after-hours leads, start with a turnkey service. Dialzara at $29 per month is worth trying for a month just to see how many conversations you were previously missing.

If you want a system that feels like part of your business and connects to your CRM, your booking calendar, and your follow-up sequences, build it with Vapi. It takes a few hours to set up properly the first time. After that, it runs.

If you have specific compliance requirements, you are in healthcare or legal, or your call flows are genuinely complex, you might need professional setup help. The key word there is setup help, not a $5,000-per-month management retainer in perpetuity for a system that does not change.

One thing to be honest about

AI voice is not perfect yet. If a caller asks something genuinely off-script, the system will either escalate to a human, take a message, or sound awkward, depending on how it is configured. That is fine. Most of the value from an AI phone system comes from the 80% of calls that are routine: hours, directions, pricing questions, appointment requests. The edge cases can still go to a human.

A well-configured AI phone system does not eliminate the human from your business. It makes sure the human in your business is only spending time on the conversations that actually require them.

That is the shift. Not less human contact. Better human contact.

If you are sitting on a phone setup that sends callers to voicemail and you have never run the math on what that costs you, now is a good time to do it.

The tools to fix it are listed above. They are not expensive. The question is just how you want to set them up.

If you want to talk through which option fits your business, that is exactly what the AI Clarity Call is for. Book one at muddventures.com.

See you tomorrow.

Andrew

Durable, a platform that has helped over three million service-based businesses launch and run their operations, released a new tool on April 1st called Discoverability. It tracks how your business shows up across ChatGPT, Gemini, Claude, Perplexity, and Grok when someone asks those platforms for a recommendation in your category.

The reason they built it: more than 50% of consumers are now using AI models to search for local business recommendations. Not Google. ChatGPT. Gemini. Perplexity.

And as Durable’s founder James Clift put it: “Most businesses have no idea how they’re showing up.”

That is the thing I want to talk about today.

The Channel That Opened Without an Announcement

In December 2025, Shopify launched Agentic Storefronts as part of their Winter ‘26 Edition. One setup in your admin and your products are automatically discoverable inside ChatGPT, Perplexity, and Microsoft Copilot. Customers can find your products, get accurate information, and in some cases complete a purchase without ever leaving the AI conversation.

Over 150 product updates shipped in that edition. This one got a press release. Most small business owners missed it entirely.

Shopify’s president Harley Finkelstein said it plainly in March: AI shopping agents are preparing to change everything about how products get discovered and purchased.

He is right. And the window where you can get ahead of it is right now, before most of your competitors have thought about it once.

What Is Actually Changing

The concept has a name. GEO: Generative Engine Optimization.

It is the next layer on top of traditional SEO. Where SEO was about ranking in a list of blue links, GEO is about being included in the answer an AI gives when someone asks it a question.

Gartner is forecasting that 25% of all web search traffic will shift away from traditional search engines to AI-powered answer engines by the end of 2026. Google AI Overviews now appear on roughly 40% of all search queries.

The mechanics of how AI search works are different from how Google works. AI systems that pull live information, like Perplexity and Google AI Overviews, are evaluating the first 200 words of your content most heavily. They want direct answers, clear structure, and trust signals. They are not counting keywords.

The good news: the basics of GEO are the same things that make your website and your business listings useful to actual humans. Clear information. Consistent name, address, and phone number across directories. Real reviews. Specific, well-organized content about what you do and who you serve.

Three Things Worth Doing This Week

First, check your business listings. Durable’s tool is free to start and shows you exactly how your business is appearing in AI search platforms right now. If you have never checked this, the answer is probably “inconsistently,” which is the main reason businesses get left out of AI recommendations. The tool is at durable.co and takes about five minutes to set up.

Second, if you sell physical products and you are on Shopify, turn on Agentic Storefronts. It is one toggle in your admin. Your products start appearing in ChatGPT and Perplexity searches. There is no additional cost and no separate integration to build. This is one of the rare cases where the platform has already done the work and you just have to flip the switch.

Third, look at your website’s homepage and your Google Business Profile with fresh eyes. Ask: if someone asked ChatGPT “find me a [your business type] in [your city],” what would it pull to describe you? Is the information accurate, specific, and current? Most business owners have not updated their profile in over a year.

The Bigger Picture

This is not the end of Google. It is not a crisis requiring immediate action. But it is a genuine shift in how a growing portion of customers are finding businesses, and it is happening fast enough that getting set up now puts you months ahead of competitors who will catch on when it becomes obvious.

The tools to take advantage of it are either free or already included in platforms you are paying for. You do not need an agency for this. You need an afternoon and a clear description of what you do.

That is exactly the kind of thing I watch for so you do not have to watch everything.

If this was useful, forward it to one person running a local business or a service-based company. They need to know about this shift too.

See you tomorrow.

Andrew

Hey there,

I want to tell you about a guy in Utah.

He used Perplexity AI the way a lot of service business owners use it: for research, for thinking through problems, for strategy work he didn’t want anyone else seeing. He typed in details about his family’s finances. His tax obligations. His investment portfolio. His personal financial strategy.

He assumed the conversation was private.

The lawsuit filed Tuesday in federal court in San Francisco says it wasn’t.

According to the complaint, Perplexity embeds tracking scripts that activate the moment you log in and transmit complete transcripts of your conversations to Meta and Google in real time. Not summaries. Not anonymized data. The full text of what you typed, going straight to the two largest advertising platforms on the internet.

The case is Doe v. Perplexity AI Inc., 3:26-cv-02803. The plaintiff is listed as John Doe. The irony is not subtle.

And here’s the kicker. Perplexity has an Incognito mode. They built it specifically to signal that they were different from surveillance-based search engines. The lawsuit alleges the trackers work right through it.

Perplexity raised over $1 billion on the positioning that it was the privacy alternative to Google. When asked about the lawsuit this week, their spokesperson said they “haven’t been served” and therefore “cannot verify its existence.” They did not deny the tracking.

Meta’s response was to point reporters to their policy page saying advertisers shouldn’t send them sensitive data. One outlet described this as a casino pointing to its responsible gambling brochure.

Google said nothing.

So why does this matter to you specifically.

The man in Utah typed financial strategy into a free AI tool. Think about what you typed into a free AI tool this week.

Client names. A pricing proposal you were workshopping. Competitive intel you wouldn’t share with your team. A vendor negotiation you were rehearsing. Your own revenue projections. A problem you’re having with a client that you worked through out loud with an AI chatbot because it felt safer than telling anyone who knows you.

Every one of those conversations exists somewhere. And if the platform running the tool has a business model built on data, which every free platform does, then “somewhere” is doing a lot of work in that sentence.

This is not a Perplexity-specific problem, even though the lawsuit is. And I want to be direct about something: free AI has been genuinely game-changing for small business owners. People who couldn’t touch this stuff two years ago are now running automations, producing content, and serving clients at a level that used to require a full team. Use it. It’s incredible.

Just know the trade. Free products run on something, and for most of them, that something is your data. You already know this from years of using Google and Facebook for free. The same deal applies here, and the only difference is that what you’re putting into AI tools is usually a lot more sensitive than your Instagram habits.

Here is what I actually think you should do, right now, before you open another AI tab.

Know which tier you’re on and what it means. A $20/month subscription changes the business model. It doesn’t guarantee privacy, but it changes the company’s incentives significantly. If you’re doing sensitive client work, the paid tier of the same tool you already use is often the right answer, not a different tool entirely.

Treat free AI tools like public Wi-Fi. Use them for things you wouldn’t mind being visible. Never type client names, financial details, pricing strategy, or anything you wouldn’t want a competitor or a journalist to see. The research tab is fine. The strategy session is not.

“Incognito mode” on an AI product means almost nothing. Browser incognito hides your history from other people using your computer. It doesn’t hide you from the website. AI incognito mode in many cases means even less. Assume the platform sees what you type, full stop.

Check your AI tool’s data training policy. Most major platforms let paid enterprise users opt out of having their conversations used to train future models. Free tier users often cannot opt out. If you’re doing client work on a free tier, that conversation may be training the next version of the model. For a lot of service businesses, that is not a theoretical risk.

The lawsuit might go nowhere. That’s genuinely possible. But that’s not why I’m telling you this. I’m telling you because the behavior in the complaint is what happens when you hand sensitive information to a free product without thinking about what you actually agreed to. You’ve already figured this out with Instagram and Facebook. Your AI tools deserve the same skepticism, and the information you put in them is usually way more valuable than anything on your social feed.

A big part of what I help business owners sort through is exactly this: not just which AI tools to use, but how to use them without handing your client relationships and business strategy to platforms that have zero obligation to protect it.

If you want to talk through what your current AI stack looks like from a privacy and cost standpoint, I’m opening a small number of spots for strategy sessions in April. Or just hit reply and tell me what tools you’re actually using for client work. I read every one.

Talk soon,

Andrew

Book a 30-minute strategy call

Not because they are lazy planners or bad operators. They are actually really sharp. But they are still doing things manually that stopped making sense to do manually about two years ago.

I had a call last week with a consultant who was spending 90 minutes every Monday morning pulling data from three different tools, dropping it into a spreadsheet, and emailing a summary to her two clients. She had been doing it for 18 months.

I showed her one workflow. It took 45 minutes to set up. Now it runs on its own every Monday at 6:00 AM and the emails go out before she wakes up.

90 minutes a week times 52 weeks is 78 hours a year. That is nearly two full work weeks handed back to her, for free.

That is what automation actually is. Not robots replacing you. Not some sci-fi future. It is just getting the tedious stuff off your plate so you can do the work that actually matters.

Here are the five automations I tell every business owner to get running first. You can build all five of them this week with tools that cost less than $100 a month combined.

Automation 1: Lead Intake and CRM Logging

When someone fills out a form on your website, three things should happen automatically: the lead should land in your CRM, a personalized acknowledgment email should go out within two minutes, and the lead should be tagged and scored based on what they told you.

Most business owners are still checking their inbox for form notifications, copying contact info into a spreadsheet, and then remembering (or forgetting) to follow up.

The workflow: Typeform or Jotform captures the submission, Zapier or Make routes it into HubSpot or whatever CRM you use, and an email sequence fires immediately.

Time to build: about 1 hour.

Time saved per week: 3 to 5 hours depending on lead volume.

Bonus: Response times under 5 minutes increase lead conversion by up to 400% according to research from Harvard Business Review.

Automation 2: Invoice Creation and Payment Follow-Up

You finished the work. You should get paid. But for most service businesses, the invoicing process is a mess of manual entries, late sends, and awkward follow-up emails.

Here is the workflow: a project gets marked complete in your project management tool (ClickUp, Asana, Notion, wherever you work), a trigger fires, QuickBooks or FreshBooks auto-generates the invoice from the project details, the client receives it with a payment link, and if it is not paid in 7 days a follow-up email goes out automatically.

You never have to think about it.

Research from Versalence AI and McKinsey both show invoice processing automation reduces manual processing time by 70 to 80 percent and gets businesses paid faster because follow-up actually happens consistently.

Time to build: 1.5 to 2 hours.

Time saved per month: 4 to 8 hours for a typical service business.

Automation 3: Client Onboarding Sequence

The first week with a new client should feel polished. Most businesses deliver something closer to chaos because onboarding is genuinely complicated to do manually every time.

The workflow: client signs contract in DocuSign or PandaDoc, which triggers the automation. A Google Drive or Notion folder is created and shared. A welcome email goes out with everything they need. A Calendly link for the kickoff call is included. A task is created in your project tool. Your client intake questionnaire lands in their inbox.

All of it happens while you are doing something else entirely.

Companies that automate onboarding reduce the time to get a client fully set up by 60 to 70 percent. More importantly, clients feel like you have your act together from day one, which sets the tone for the entire relationship.

Time to build: 2 to 3 hours.

Time saved per new client: 1.5 to 2 hours.

Automation 4: Social Content Scheduling and Repurposing

Creating content takes time. Distributing it manually is time you can get back.

Here is the workflow: you write one piece of content in a Google Doc or Notion page. An automation pulls it, generates a shorter version for LinkedIn using an AI step (ChatGPT or Claude), drops the shorter version into a scheduling tool like Buffer or Hypefury, and files the original in your content library.

You can even set it up so that when a newsletter goes out, a LinkedIn post version is automatically queued for the same day.

The average business owner spends 6 hours a week on content distribution. This workflow cuts that to under an hour for most people.

Time to build: 1.5 to 2 hours.

Time saved per week: 3 to 5 hours.

Automation 5: Weekly Business Snapshot Report

Every Monday morning, you should know exactly where your business stands. Revenue in the door, leads in the pipeline, tasks overdue, anything that needs your attention.

Most business owners either skip this entirely or spend 45 minutes pulling it together manually.

The workflow: a scheduled trigger fires every Sunday night at 10:00 PM. It pulls data from your CRM (new leads, pipeline value), your invoicing tool (outstanding payments, monthly revenue), your project tool (tasks overdue, projects at risk), and your bank or Stripe account (cash balance). An AI step summarizes everything in plain language. The report lands in your inbox by the time you wake up Monday.

I built a version of this for a client in about 90 minutes. He told me it changed how he starts every week.

Time to build: 1.5 to 2 hours.

Time saved per week: 45 to 90 minutes, plus the mental clarity you cannot put a price on.

The Math on All Five

If you build these five automations this week, you are looking at roughly 6 to 8 hours of setup time.

In return, you get somewhere between 10 and 20 hours back per week depending on your business volume.

That is a 10 to 20x return in the first month alone.

Research published in 2026 shows businesses that implement just 10 automations saving 1 hour each per week reclaim 520 hours annually. That is 65 full working days redirected toward client work, strategy, or whatever matters to you.

And if you are worried about the tools being expensive: a Zapier starter plan is $20 a month. Make.com runs about the same or less. n8n is open source and can be self-hosted for free if you have any technical help.

The ROI math is not close.

What Tool Should You Use?

For most business owners who want to get started fast: Zapier. It connects 7,000+ apps and the interface is as simple as it gets.

If you want more flexibility and lower per-task pricing: Make.com. The same workflow that costs $50 a month on Zapier often runs for $10 to $15 on Make.

If you have a developer or want to own your infrastructure: n8n. Open source, powerful, and you control your data.

Gartner projects that by 2027, 65 percent of businesses under 100 employees will use at least one AI-powered automation workflow, up from under 20 percent in 2024. Right now you have a window to build these systems before they become table stakes for everyone.

One Honest Note

Automation does not fix a broken process. If your sales follow-up is inconsistent because the message is wrong, automating it faster will just send the wrong message faster.

Before you automate anything, make sure you are happy with how it works when you do it manually. Then hand it off to the workflow.

That is the only way automation actually compounds.

If you want help building any of these, or you want someone to look at your current stack and tell you what to prioritize, that is exactly what we do at Mudd Ventures. check out https:/muddventures.com and we can set up 45 minutes.

Otherwise, pick one automation from this list and block two hours on your calendar this week.

Not next week. This week.

You have everything you need.

See you next time,

Andrew

Mudd Ventures

And if you are worried about the tools being expensive: a Zapier starter plan is $20 a month. Make.com runs about the same or less. n8n is op

I want to talk about something I keep noticing in the businesses I work with.

When AI starts handling the routine stuff, the first thing most owners expect is a cost number. A line item that went down. A task that got cheaper.

But that is not actually what they talk about a month later.

What they talk about is the client they finally had a real conversation with. The product idea they had time to actually prototype. The team meeting that became a strategy session instead of a status update.

The ROI of getting repetitive work off your plate is not just efficiency. It is what you do with what you get back.

The Work That Only You Can Do

Every business owner I have worked with has a list of work that sits at the top of their mind but never quite makes it to the top of their week.

The deep client relationship you keep meaning to invest in. The process you know needs rethinking. The pitch you have been meaning to sharpen. The team member who deserves a real development conversation.

This work is not hard to identify. It is hard to prioritize when your day is filled with work that is important but predictable.

Following up on the same leads in the same order. Sending the invoice you already generated in your head. Answering the question your customer asked in five slightly different ways last month.

These things need to happen. They do not need to happen with your full attention.

What AI Agents Actually Do Well in 2026

The category of “agentic AI” has gotten a lot of hype, so let me be specific about where it actually earns it right now.

AI agents work best on tasks that are high-frequency, follow a clear pattern, and do not require judgment calls about relationships or context. Here is where businesses I have seen are putting them to use.

Lead follow-up sequences. Not replacing the sales conversation, but making sure every single prospect gets a timely, relevant touchpoint before the human picks up the relationship. Response times drop from hours to under 60 seconds. The salesperson’s first real contact is a warmer one.

Tier-1 customer support. About 80% of the questions your customers ask are some version of the same 10 questions. An agent handles those around the clock. Your team handles the 20% that actually needs a human ear and a thoughtful response. They get to do that better because they are not spending the first three hours of their day answering what time you are open.

Invoice generation and payment follow-up. The invoices that needed to go out at project milestones. The payment reminders at day 7, day 14, and day 30. These are important, time-sensitive, and completely predictable. Exactly the kind of work an agent does reliably so your team can focus on the client relationship itself.

Meeting summaries and action items. Record the meeting, transcribe it, pull out commitments, send the follow-up. Otter.ai starts free. The meeting does not get less human because the notes are automatic. It gets more human because the people in the room are actually listening to each other instead of typing.

The 90-Day Picture

Here is what the research actually shows: 73% of small and midsize businesses that adopted AI agents in 2025 reported measurable productivity gains within 90 days. The study does not say they let people go. It says the same people did more and better work.

The businesses I have seen do this well are not thinking about headcount. They are thinking about capacity. The question is not “what can AI do instead of a person?” The question is “if my best people had 10 more hours each week, what would we finally be able to do?”

That is the version of this conversation worth having.

Where Most Businesses Go Wrong

A couple of patterns that tend to undermine the whole thing.

Starting with the wrong workflow. The highest-ROI first move is almost always the one where your most capable person is spending the most time on something completely predictable. Find that. Start there.

Automating before the process works. If a workflow is inconsistent today, automating it makes it consistently inconsistent. Take two hours to map out what good looks like. Then build the agent around it.

Treating it as a set-it-and-forget-it. The businesses getting the most out of this are the ones with one person who reviews agent outputs weekly and adjusts. Think of it like onboarding any new team member. The first month matters.

Where This Is All Going

In March 2026 alone, three major model releases shipped within 23 days of each other. The Model Context Protocol, which is essentially the infrastructure that lets AI agents connect to your actual tools, crossed 97 million installations. This is becoming standard, not specialized.

The businesses that will be in the best position going forward are not the ones that treat AI as a cost-cutting exercise. They are the ones that treat it as a capability expansion. Same great people, bigger surface area. More time for the work that actually requires a human being.

At Mudd Ventures, this is what I spend most of my time on with clients: figuring out which workflows to hand off so the people in the business can spend more time doing what they are actually great at. If you are working through that question right now, hit reply. That is exactly the kind of conversation I am here for.

If this landed for you, forward it to one business owner who is spending too much of their week on work that could run without them.

And hit reply: what is the one thing you would finally have time for if your week opened up by 10 hours?

I’m going to skip the long introduction because you did not sign up for a newsletter about me. You signed up because you’re trying to figure out where AI actually fits in your business without wasting money or getting left behind.

So let’s get into it. Because something big is happening right now and most business owners I talk to have no idea it’s coming.

The SaaS Market Just Lost $2 Trillion.

Between January and March of this year, the software sector shed roughly $2 trillion in market capitalization.

Two trillion dollars in two months.

That is not a correction from a bad earnings call. That is the market pricing in something structural. AI agents are starting to do what software tools used to do, and investors can see the math.

Here is the math in plain terms: a marketing automation platform that charges $3,000 a month is being replaced by an AI agent that costs $200 a month and does more. That dynamic does not resolve well for the legacy vendor.

What Is Actually Happening to Your Software Stack

Gartner projects that 40% of small and mid-sized businesses will deploy at least one AI agent by the end of 2026. A Databricks survey found that the use of multi-agent systems spiked 327% over a four-month period.

What does that mean in practice?

It means one AI agent is now doing the work that used to require three separate subscriptions. CRM automation, email marketing, follow-up sequences, and reporting are getting consolidated into a single system that costs less and requires less human management.

Businesses that have already made this shift are reporting 30 to 70% reductions in software costs. Not over five years. Right now.

Content creation time down 50 to 70%. Customer follow-up automated. Lead nurturing running without a human touching it.

The average small business owner is spending $400 to $700 a month across 3 to 5 tools to do what one well-configured AI agent can do for $50 to $200.

The Part Nobody Is Saying Out Loud

Here is what I want to be honest with you about.

The disruption is real. But it is also being overhyped in a way that is causing people to move too fast and break things that were working.

Deloitte’s 2026 research is clear that AI agents will not fully replace core business systems this year. Probably not for another five years in most cases. The shift is directional, not overnight.

So there are two wrong moves here.

The first is doing nothing and assuming your software stack is safe. It is not safe. The economics are shifting and every vendor you pay monthly is feeling it.

The second is blowing up your tech stack based on fear. I have watched business owners cancel tools they genuinely needed because they read a headline about AI disruption, and then spent six months rebuilding what they had.

The right move is somewhere in the middle, and it starts with an honest audit.

The Audit That Takes 30 Minutes

Pull up your last card statement and find every software subscription you are paying for.

For each one, ask: Is a human making decisions inside this tool, or is this tool mostly automating a repetitive process?

If the answer is repetitive process, that is a candidate for consolidation. That is where AI agents win cleanly and immediately.

If the answer is human decision-making, judgment calls, or relationship management, those tools earn their keep for now.

Most business owners I work with have 2 to 3 tools in the first category and did not realize it until they did this exercise.

That is the starting point. Not a big transformation project. Just 30 minutes and a credit card statement.

What I’m Watching This Quarter

The businesses that are winning right now are not chasing every new AI agent release. They are picking one workflow, building it properly, and measuring before they scale.

That is the whole playbook. Define the process. Build the agent. Measure for 60-90 days. Then decide what to touch next.

I’ll be covering specific implementations, tools, and real numbers in upcoming issues. If you have a process in your business you’ve been trying to automate and haven’t figured out yet, reply to this email and tell me about it. I read every reply.

Happy Monday.

Andrew Mudd

Mudd Ventures helps business owners build AI systems that actually move the needle. If you want to walk through your current tech stack and figure out where the real opportunities are, reply to this email or book a clarity call at muddventures.com.

78% of companies are now using AI in some form. That sounds like massive adoption, right? Progress. Momentum.

And then here is the other number: 95% of those same companies report seeing no meaningful ROI from their AI investments.

Let that gap sink in for a second.

Stanford faculty put words to it in their 2026 predictions: the era of AI evangelism is giving way to an era of AI evaluation. The question is no longer “Can AI do this?” The question is now “How well, at what cost, and for whom?”

I think this is the healthiest shift the industry has ever seen. And I also think most businesses are completely unprepared for it.

The Hype Was Real. The Problem Was How the Industry Responded to It.

From 2023 to 2025, AI demos were everywhere. Every vendor had a video of an AI agent doing something impressive in a controlled environment. Every conference had a panel of executives talking about transformation.

Businesses responded by buying. By experimenting. By building pilots. That was not wrong, exactly.

The problem is that buying and experimenting became a substitute for thinking. Companies were spending money on AI tools the same way someone buys exercise equipment: full of good intentions, very little follow-through on the actual work.

Gartner now predicts that over 40% of agentic AI projects will be canceled before the end of 2027. Not because AI stopped working. Because the business problems they were mapped to were never defined clearly enough to begin with.

The Diagnostic I Use With Every Client

When someone comes to me saying AI is not working for them, I ask three questions:

First: What specific process were you trying to automate or accelerate, and how did you measure success before you introduced AI?

Second: Who owns this? Not who approved it, who owns the day-to-day success of it?

Third: What happens when it fails? Do you have a fallback, or did you design it to run without one?

If the answers are vague, that is not an AI problem. That is a strategy problem.

The 5% of companies genuinely winning with AI right now are not smarter or better-funded. They are just more disciplined about asking these questions before they spend a dollar.

What the Winners Are Actually Doing

The data is actually encouraging once you get past the noise.

Companies seeing real returns are reporting 5x to 10x ROI per dollar invested in AI agents. Healthcare systems cutting documentation time by 42%. Customer service teams cutting response times by 30% to 50%. Contract review workflows saving millions annually.

But every single one of those wins shares a pattern: they started small, they defined success in advance, and they built governance around it before they scaled.

They did not start with “how do we become an AI company.” They started with “we have a specific problem that takes 3 hours a week per person, and here is what success looks like if we cut that to 20 minutes.”

The Shift I Am Watching in Real Time

CIO Magazine is calling 2026 “the year AI ROI gets real.” IBM is telling leaders that the “learning and experimentation” excuse expires this year. Real dashboards. Real productivity metrics. Real accountability.

For businesses that did the foundational work, this is a great moment. The proof is arriving.

For businesses that treated AI as a line item to check off, the reckoning is arriving instead.

The good news is that if you are reading this, you are already in a different conversation. You are asking better questions. That is actually the whole game.

One Thing to Do This Weekend

Pick one AI tool you are currently paying for. Write down in plain language what specific outcome it is supposed to produce, how you would measure that outcome, and when you last actually checked those numbers.

If you cannot answer all three of those in under two minutes, you found your starting point.

That is it. That is the whole framework.

Happy Friday.

Andrew Mudd

Mudd Ventures helps business owners build AI systems that actually move the needle. If you want to talk through where your AI investments are and where they should be going, reply to this email or book a clarity call at muddventures.com.