November 8, 2025
Welcome Back,
Hi there
Good morning! In today’s issue, we’ll dig into the all of the latest moves and highlight what they mean for you right now. Along the way, you’ll find insights you can put to work immediately
— Ryan Rincon, Founder at The Wealth Wagon Inc.
Today’s Post
🧭 Building an AI Strategy for Your Business: From Buzzword to Bottom Line
Let’s be honest — “AI strategy” gets thrown around a lot these days. Every company claims to be “AI-driven,” but when you look closer, many don’t actually know what that means or where to start.
It’s like buying a race car without knowing how to drive it. The potential is massive — but without direction, you’ll just spin your wheels.
So today, let’s talk about how to actually build a real AI strategy that moves beyond hype and creates measurable value for your business — whether you’re a startup founder, a marketer, or a Fortune 500 exec.
💡 Step 1: Start With “Why,” Not “What”
Before you invest in any AI tool or hire a data scientist, ask one simple question: “What problem am I trying to solve?”
AI shouldn’t be a shiny object. It should be a solution.
Here’s how to think about it:
Are you trying to cut costs (e.g., automating data entry or customer service)?
Do you want to boost revenue (e.g., improving lead scoring or ad targeting)?
Or are you looking to innovate faster (e.g., designing new products or predicting market shifts)?
Without a clear business goal, your AI initiative will end up as a cool experiment that never scales — something 70% of AI projects fail to do, according to Gartner.
⚙️ Step 2: Audit Your Data
AI runs on data like cars run on fuel — and without quality data, your system won’t go anywhere.
Start by assessing three key things:
Data Availability – Do you have the right data for your use case? (e.g., customer behavior logs, transaction data, or sensor data)
Data Quality – Is it accurate, clean, and up to date? AI can’t fix messy or biased inputs.
Data Access – Can your team actually use this data safely and legally?
💬 Pro tip: Think of data as an asset. Organize it, label it, and protect it. The companies winning with AI today — like Amazon and Netflix — have spent years building disciplined data ecosystems.
🧠 Step 3: Choose the Right Type of AI
Not all AI is created equal, and not every problem needs a multimillion-dollar model.
Here’s a simple breakdown of options:
Predictive AI: Forecasting trends, demand, or customer behavior (e.g., “What will my sales look like next month?”)
Generative AI: Creating new content — text, images, or code (e.g., ChatGPT, Midjourney).
Analytical AI: Finding patterns in large datasets to drive better decisions (e.g., financial risk modeling).
Automation AI: Streamlining repetitive workflows using machine learning or RPA (robotic process automation).
The key is alignment — matching the type of AI to your actual business need. Don’t use a rocket when all you need is a fast car.
🧩 Step 4: Build or Buy?
This is one of the biggest questions businesses face:
Should you build your own AI models or use existing platforms?
Here’s a quick cheat sheet:
Build your own if you have specialized data, technical talent, and long-term goals (e.g., Tesla, Google, or OpenAI).
Buy or integrate if you want speed, simplicity, and cost control. Tools like ChatGPT Enterprise, Anthropic’s Claude, or Google Vertex AI offer plug-and-play power without the overhead.
💬 As McKinsey puts it, “AI is less about replacing humans and more about augmenting them.” Focus on how it fits into your workflow rather than reinventing the wheel.
🏗️ Step 5: Pilot, Measure, Scale
Don’t go all-in from day one. The smartest AI companies start small — testing real use cases before scaling.
Follow this 3-step loop:
Pilot: Pick one narrow but high-impact problem (like automating support tickets).
Measure: Track tangible outcomes — time saved, cost reduced, or sales increased.
Scale: If it works, expand it across other departments or functions.
The secret? Always tie success back to ROI, not just “innovation.”
⚖️ Step 6: Stay Ethical and Compliant
AI success isn’t just about what’s possible — it’s about what’s responsible.
As global regulations like the EU AI Act and California’s Privacy Rights Act (CPRA) take effect, businesses must ensure their models are:
Transparent (can you explain how the AI made a decision?)
Fair (does it avoid bias or discrimination?)
Secure (is user data protected?)
Ignoring these can mean lawsuits or reputational damage — something no company can afford.
🚀 Step 7: Create a Culture of AI Adoption
The best AI strategy in the world fails if your team resists it.
Train employees on how to use AI tools, not just what they do.
Reward innovation — make it okay to experiment and fail fast.
Build cross-functional teams — pair engineers with marketers, analysts, and designers.
As Satya Nadella, Microsoft’s CEO, put it: “AI won’t replace people. But people who use AI will replace people who don’t.”
🌟 Final Thoughts
Building an AI strategy isn’t about chasing trends — it’s about aligning technology with purpose.
Start with problems that matter, use the data you trust, and scale what works. With that foundation, AI won’t just be a buzzword in your company — it’ll be a competitive advantage.
The businesses that win in the next decade won’t be the ones that adopt AI the fastest — they’ll be the ones that use it the smartest.
That’s All For Today
I hope you enjoyed today’s issue of The Wealth Wagon. If you have any questions regarding today’s issue or future issues feel free to reply to this email and we will get back to you as soon as possible. Come back tomorrow for another great post. I hope to see you. 🤙
— Ryan Rincon, CEO and Founder at The Wealth Wagon Inc.
Disclaimer: This newsletter is for informational and educational purposes only and reflects the opinions of its editors and contributors. The content provided, including but not limited to real estate tips, stock market insights, business marketing strategies, and startup advice, is shared for general guidance and does not constitute financial, investment, real estate, legal, or business advice. We do not guarantee the accuracy, completeness, or reliability of any information provided. Past performance is not indicative of future results. All investment, real estate, and business decisions involve inherent risks, and readers are encouraged to perform their own due diligence and consult with qualified professionals before taking any action. This newsletter does not establish a fiduciary, advisory, or professional relationship between the publishers and readers.