The Hidden Cost of AI Tools for Small Businesses

AI tools promise massive productivity gains for small businesses, but there is a cost most people never see. In this episode of Weeks Ahead AI, the team breaks down how AI token pricing works, why many software platforms mark up AI usage by 10x to 100x, and how business owners can avoid overpaying.

If your team is using AI features inside platforms like CRMs, SaaS tools, or coding tools, you may already be paying far more than you realize. Understanding tokens, API access, and efficient AI usage can help you save thousands of dollars while still benefiting from AI automation.

This conversation explains the real economics behind AI tools and what every small business owner should know before rolling AI out across their team.

In This Episode

• What AI tokens are and why they determine your AI costs
• Why many software companies mark up token usage 10x–100x
• Real examples of hidden AI costs inside SaaS tools
• How inefficient prompting and long chat threads burn tokens
• Why businesses should bring their own API keys to control costs
• A simple strategy for testing AI tools before rolling them out company-wide

Timestamps

00:00 – Introduction to Weeks Ahead AI
The team introduces the episode and explains why understanding AI costs is becoming critical for business owners.

00:22 – What AI Tokens Actually Are
Breaking down the concept of tokens and why they are the unit of cost behind most AI tools.

02:00 – The Hidden Costs Inside SaaS AI Features
A real example of how a CRM AI feature consumed an entire monthly credit budget in minutes.

03:30 – The Massive Markup on AI Usage
How some platforms charge dramatically higher token prices compared to direct API access.

04:30 – Why Software Companies Are Raising AI Prices
How SaaS companies use AI features to drive revenue growth and increase customer spend.

06:00 – How Tokens Are Consumed in AI Conversations
Why uploads, attachments, and long chat threads dramatically increase token usage.

08:30 – Building Tools with Your Own API Keys
How controlling your own AI infrastructure can reduce costs from hundreds of dollars to pennies.

10:00 – The Idea of “Token Budgets” for Employees
Why some companies now treat AI usage like another operating expense.

12:00 – How Inefficient AI Usage Burns Tokens
Why continuing long chat threads can multiply costs without users realizing it.

14:30 – Why Short Responses Don’t Always Save Tokens
How AI models may still generate long answers internally before summarizing them.

16:00 – Real Examples of Expensive AI Platforms
Discussion around CRM and coding platforms that charge hundreds per user per month for AI features.

18:00 – Why AI Costs Are Tied to Energy and Compute
Exploring the link between token pricing, electricity usage, and data center demand.

19:30 – Efficient AI Strategies for Small Businesses
How to reduce token costs by choosing the right models and controlling API usage.

21:00 – A Smart Way to Test AI in Your Company
Why businesses should start with a few AI seats before rolling it out company-wide.

22:00 – Questions Business Owners Should Ask Their Vendors
How to review SaaS invoices and understand what you’re actually paying for AI.

If this episode made you curious about how much your business is spending on AI, take a few minutes to review your software invoices and AI usage.

And if you discover surprising token costs or hidden AI charges, share them with us at weeksahead.ai. We may feature them in a future episode.

How does AI actually help a construction contractor? In this episode of Weeks Ahead AI, Tim Hicks (T.W. Hicks, Inc.) breaks down how AI unlocked faster estimating, better communication, and scalable growth for a service based construction business.

In This Episode

• What “industrial flooring” really is and why specs are more complex than most people realize
• The first AI win that changed everything: estimating speed (hours to minutes)
• How AI helped a 60–80 person contractor support 50%+ growth without hiring a bullpen
• The “foundation first” approach to AI adoption in a real business
• How Slack, Otter AI, Monday.com, and daily reporting create operational visibility
• Why small businesses can move faster than enterprise, and win

Timestamps

• 00:00 Weeks Ahead AI intro and Tim Hicks introduction
• 03:00 Tim’s background and 26 years of T.W. Hicks
• 06:00 What industrial flooring is, and why it is “hidden” but critical
• 09:00 Specs vs reality: intent, budgets, and choosing what actually works
• 12:00 Tim’s AI journey begins: forward thinking and the Denton dinner
• 15:00 First AI problem solved: estimating, bottlenecks, and standardization
• 18:00 The breakthrough moment: an AI button in existing software
• 21:00 From 8–10 hours to minutes and what that did to the pipeline
• 24:00 Company wide AI workflows: Slack reporting, Otter AI notes, Monday content flow
• 27:00 50%+ growth and why AI made scaling easier
• 30:00 Job fears vs reality: craftsmanship, Meta glasses, and field visibility
• 33:00 Robotics in plants and what Tim is seeing coming next
• 36:00 “ChatGPT is yesterday’s news” and why business owners must build structure
• 39:00 How to get started: ChatGPT as a thought partner and bottleneck finder
• 42:00 Hiring an AI strategist and why owners still must understand their business
• 45:00 Small business advantage: “we’re ninjas,” where to find Tim, and closing

Links and Resources Mentioned

• T.W. Hicks, Inc.: twhicksinc.com
• Weeks Ahead AI: weeksahead.ai
• Tools discussed: ChatGPT, Slack, Otter AI, Monday.com, Plaud, Meta smart glasses

If you are a business owner thinking, “AI cannot help my industry,” this episode is your proof. Start with one bottleneck, one workflow, and one tool. If you want help mapping AI into your business, reach out at weeksahead.ai.

In this episode of Weeks Ahead AI, we sit down with entrepreneur Jake Gannon to talk about how AI is changing what it means to start and scale a small business. From building companies with 60+ employees to launching a profitable venture solo using AI tools, Jake breaks down how founders can move faster, operate leaner, and eliminate unnecessary friction.

If you're a small business owner wondering where to start with AI or how to scale without bloating your payroll, this conversation is for you.

🔑 In This Episode

• Why founders must start with objectives and key results before using AI
• How AI replaces gaps traditionally filled by business partners
• The power of operational AI over marketing AI
• How Jake launched Polarity Parking in 6 months using ChatGPT
• Why discernment matters more than tool loyalty
• The biggest risk of ignoring AI in your industry

⏱️ Timestamps

00:00 – Welcome to Weeks Ahead AI
AI for business owners who want to save time, cut costs, and stay weeks ahead.

02:00 – Meet Jake Gannon
Founder of Polarity Parking and 1116. Previously scaled and exited an edtech startup.

04:00 – Where Business Owners Should Start with AI
Start with goals, objectives, and key results before jumping into tools.

06:30 – AI as a Replacement for Business Gaps
How AI accelerates learning curves and fills skill gaps traditionally handled by partners.

09:00 – Why ChatGPT Is Enough for Most Businesses
Why general AI tools are sufficient for 90% of small business use cases.

11:00 – Operations First, Revenue Second
Why improving operational consistency creates bigger long term gains than flashy marketing automation.

14:30 – From 62 Employees to Solo Founder
How Jake scaled his first company with a full team and built his next one lean using AI.

17:30 – The Fear Factor and AI Adoption
Why waiting for certainty is the biggest risk to your business.

20:00 – How Fast Can You Get Caught Up?
The AI learning curve is shorter than most people think.

23:00 – AI Is Not a Fad
Why AI adoption is like early cell phone adoption. Ignore it and get left behind.

26:00 – Inside Relay Hub
How centralized AI collaboration creates consistency across teams.

29:00 – The Story Behind Polarity Parking
From a cold walk in Chicago to a revenue generating AI built business in six months.

32:00 – Launch Faster with AI
How AI compresses product development timelines dramatically.

34:00 – Final Advice for Founders
If you’re afraid to try AI, that’s exactly why you should.

🔗 Links & Resources Mentioned

• 1116 Consulting
• Polarity Parking – Parking monetization platform
• Relay Hub – AI collaboration and workflow platform

🚀 Call to Action

If you want to build leaner, move faster, and make smarter decisions using AI, visit weeksahead.ai to learn more about Relay Hub and how to stay weeks ahead.

Are you a business owner frustrated with AI giving you made-up answers? You're not alone. In this episode of Weeks Ahead AI, we dive deep into why ChatGPT and other AI tools sometimes fail small business owners, and what you can do about it. Whether you run a construction company, HVAC business, plumbing operation, or any business, understanding the limitations of AI tools is crucial before you stake important business decisions on their output.

In This Episode:

• Why AI models prioritize giving an answer over giving the right answer—and the real-world consequences for your business
• The "context window" problem explained: how your AI forgets critical information mid-conversation
• Why one contractor nearly made costly financial decisions based on AI-generated "facts" that were completely fabricated
• How to test if your current AI tool is giving you biased or outdated answers
• The simple "show your work" hack that catches AI mistakes before they cost you money
• Which AI alternatives are outperforming ChatGPT for business analysis and planning

Timestamps:

[00:00] Introduction to Weeks Ahead AI – helping business owners save time and cut costs with AI

[01:04] The "gateway drug" problem: Why most business owners start with ChatGPT and never explore alternatives

[02:34] Terry's breakup story: Canceling ChatGPT after 18 months—and why it felt like a divorce

[03:20] The comfort trap: "It already knows my stuff" and why that's keeping you stuck

[05:00] When AI sounds like BS: Terry's first red flag that something was wrong

[05:48] "Great idea!" syndrome: Why your AI agrees with everything (even your worst ideas)

[07:04] The lawyer's warning: AI citing legal cases that never existed

[08:00] Financial analysis disaster: How bad AI advice could have cost thousands

[09:32] The spreadsheet nightmare: 3 days wasted trying to export 500 contacts

[11:05] Context window explained: Why your AI "forgets" important details mid-conversation

[12:14] The telephone game effect: How long chats corrupt your AI's memory

[14:35] The "show your work" hack: Making AI prove its logic before you trust it

[16:40] Memory bias problem: When AI applies wrong context to your current project

[17:24] Behind the scenes: Why some AI companies throttle performance without telling you

[18:18] Terry's current AI stack: Claude, Gemini, Grok, and Relay Hub

[19:08] Four days without ChatGPT: Did Terry notice any difference?

[20:40] ChatGPT introducing ads: What this means for users

[21:29] Final takeaway: Stay weeks ahead by pressure-testing multiple AI models

Links & Resources Mentioned:

• Episode 2 – Deep dive on exporting and transferring your ChatGPT data to other models
• Claude AI
• Google Gemini
• Grok – Available through X/Twitter
• Relay Hub – AI workflow automation platform we are building.

If you're still relying on just one AI tool for your business decisions, it's time to pressure test your options. Try running the same business question through 2-3 different AI models and compare the answers. You might be surprised at the differences.

Subscribe to Weeks Ahead AI so you never miss practical AI strategies designed specifically for blue collar business owners.

Leave a review if this episode helped you understand why your AI might be giving you bad answers!

Many businesses avoid budgeting because it feels complex, time-consuming, or intimidating.

In this episode of Weeks Ahead AI, the team walks through how business owners can use AI to build a complete annual budget using historical financials, without starting from a blank spreadsheet.

Throughout the episode, the team highlights why Claude performed best for this specific task, particularly when it comes to financial analysis, spreadsheet structure, and handling assumptions, while still acknowledging that different AI models excel at different jobs.

In This Episode

• Why many businesses still avoid annual budgeting
• Using Claude AI to turn past P&Ls into a working budget
• Why some AI models perform better at financial analysis
• Applying growth assumptions and seasonality
• Reviewing and correcting AI-generated budgets
• Running hiring and growth scenarios in real time

Episode Timeline

00:00 – Why budgeting gets delayed or skipped
Common reasons business owners avoid the process.

03:00 – Why January is not too late
Using last year’s numbers to move forward.

06:30 – Uploading historical financials into AI
How much data you actually need.

09:00 – Choosing the right AI for the job
Why Claude stood out for financial modeling.

12:30 – Building a full annual budget
Revenue, expenses, and staffing generated automatically.

15:00 – Monthly views, seasonality, and assumptions
How AI applies real-world business patterns.

18:00 – Reviewing assumptions and fixing errors
Why human oversight still matters.

21:00 – Scenario planning
Testing hires, marketing spend, and growth decisions.

25:30 – Why AI budgeting works now
How recent improvements changed what is possible.

29:00 – Managing multiple AI tools
The downside of subscription sprawl.

32:00 – Final takeaways
How to apply this approach in your business.

Tools and Resources Mentioned

• Claude for financial modeling and spreadsheet work
• Wispr Flow for voice-to-text prompting
• Excel for reviewing and adjusting budgets

If you have been putting off building a budget, this episode shows how AI can help you get it done faster and with more clarity. Subscribe to Weeks Ahead AI for practical, real-world AI use cases.

Creating presentations used to take hours. Now you can talk for a few minutes, grab a transcript, and use Gamma to instantly build a clean, organized slide deck. In this episode of Weeks Ahead AI, Brad and Mitch walk through a real example in real time, showing how Gamma restructures messy conversations into a polished ten page presentation that can be exported to Google Slides, PowerPoint, Canva, or PDF.

They also explain practical tricks like using dashes to control slide grouping, how Gamma reorganizes content for clarity, and why this is one of the best low risk, high reward entry points for anyone using AI in their workflow.

In This Episode

• Live walkthrough of building a ten page deck in seconds with Gamma
• How transcripts from Plot or an iPhone recording can become presentations
• Why Gamma reorganizes your conversation into a clean narrative
• Exporting to PowerPoint, Google Slides, Canva, and PDF
• How to prepare board decks, proposals, and SOP slides in a fraction of the usual time
• Why presentation building is one of the easiest wins in AI adoption

Timestamps

00:00
Intro to Gamma and why Brad and Mitch use it for fast presentations

02:00
Turning a nine minute Relay Hub conversation into a ten page slide deck

04:50
How Gamma reorganizes raw conversation into a strong narrative flow

06:30
Key features like multimodal support, images, and customizable cards

08:15
Exporting the deck into Google Slides or PowerPoint for final edits

10:00
How to structure board decks by marking slide breaks in your transcript

12:45
Other AI tools like Lucidchart that use transcripts for diagrams and SOPs

14:30
Final thoughts and why this is a powerful time saver for any team

Links and Resources

Gamma: gamma.app
Plaud: Plaud Voice Recorder
Relay Hub Episode

Try taking a short voice memo, transcribing it, and dropping it into Gamma. Watch it turn into a complete presentation in seconds. Share your results with us at weeksahead.ai.

Most blue collar small businesses already sit on a gold mine of data from sensors, machines, and equipment, but barely use it. In this episode of Weeks Ahead AI, Brad, Terry, and Mitch bring back Josh Knutson, founder of Lium AI, to explain how AI can turn messy physical data into clear decisions for manufacturers, plants, and operators who live in the real world, not in spreadsheets.

In This Episode

• How a former therapist became a tech founder solving real world problems
• What it means to “ask your instruments” and talk to plant data in plain English
• Real use cases from astrophysics, oil and gas, satellites, and manufacturing
• How AI can boost throughput, quality, and food safety
• Why compute and power matter, and how smaller models change the future
• Practical steps for blue collar small businesses that want to start using AI

Timestamps

00:00 Why Josh is back and why physical world AI matters
02:10 From therapist to tech founder and the creation of Lium
04:40 Raising capital and building an AI startup around huge datasets
06:30 “Ask your instruments” explained in simple terms
07:45 Astrophysics example where months of work drop to 75 seconds
11:55 Oil, gas, and geothermal insights hidden in existing data
13:40 Why traditional AI tools choke on satellite and sensor data
15:55 Real world routing and decision making using weather and soil data
18:15 Why small and midsize manufacturers need this tech too
18:40 Extrusion and pet food manufacturing as a clear example
20:15 Point at your data, ask a question, get a recommendation
21:55 The future of autonomous agents tuning equipment in real time
25:55 Compute, power limitations, and the push for smaller models
29:25 Data centers, generators, and geothermal possibilities
31:00 CNBC predictions and where to learn more about Lium AI

Former psychotherapist turned tech founder Josh Knutson explains why every business should “use AI first.” He shares how tools like Claude and Lovable can replace $150K software builds, how to learn faster than ever, and how his new company Lium AI is transforming how humans interact with massive real-world data. From discovering a black hole in seconds to reshaping how we explore the physical world, this episode will change the way you think about time, money, and what’s possible with AI.