The Feature You Need Is Always "Coming Soon"
I sat in a meeting last month where a business owner showed me his AI platform's product roadmap. "See? They're adding the integration we need in Q3."
Q3. Six months away. For a feature that might or might not work the way he needs. Built by engineers who have never seen his business, don't understand his workflow, and are serving 10,000 other customers with competing priorities.
He was planning his business around a vendor's promise. And vendors are very good at making promises.
This isn't a knock on AI vendors. They build great products. But their roadmap serves their business — growing their user base, reducing their support costs, expanding their market. Your business needs are one input among thousands.
The Three Kinds of AI Tool Dependency
Not all vendor dependency is bad. The key is understanding which kind you're in.
1. Commodity Dependency (Low Risk)
You use an AI tool for tasks that every business does the same way: email drafting, meeting notes, document summarization. If this vendor disappears tomorrow, you could switch to a competitor in a week. The switching cost is low and the work isn't strategic.
Example: Using Microsoft Copilot for meeting summaries. If Copilot went away, Google Gemini or another tool could fill the gap quickly. No competitive advantage lost.
2. Workflow Dependency (Medium Risk)
You've built processes around a specific tool's features. Your team has trained on it, your workflows reference it, and switching would mean retraining and process redesign. But the underlying work isn't unique to your business.
Example: Using an AI-powered CRM that auto-generates follow-up emails. Your sales process depends on it, but the follow-up workflow itself isn't proprietary. You could rebuild it on another platform with effort.
3. Strategic Dependency (High Risk)
Your competitive advantage is tied to a vendor's platform. Your unique process, the thing that differentiates you from competitors, runs on someone else's infrastructure and is constrained by someone else's feature decisions.
Example: A construction company that built its entire estimation workflow on a vertical AI platform. Their pricing accuracy — their biggest competitive advantage — depends on features that platform may or may not prioritize.
This is where businesses get hurt. When your differentiation lives inside someone else's product, you've outsourced your competitive strategy.
The Price Increase Problem
Every AI subscription starts cheap. That's the playbook: acquire users at low margins, build dependency, then raise prices.
Microsoft raised M365 pricing $3 per user per month in January 2025. That doesn't sound like much — until you have 50 users and the math is $1,800 more per year. And that was just the first increase.
When you own the IP, your costs are predictable. Infrastructure costs trend down over time as compute gets cheaper. When you rent someone else's AI, your costs trend up as they monetize their user base.
This is basic business math that gets lost in the excitement of "we can be live by Friday."
The Integration Tax
Off-the-shelf AI tools work great in isolation. The problems start when you need them to work together.
A typical small business might use:
- A CRM for customer management
- An accounting system for financials
- A project management tool for operations
- An email platform for communications
- A scheduling tool for appointments
Now add an AI tool that needs data from all five systems. The vendor offers integrations with three of them. The other two require Zapier workarounds, CSV exports, or manual data entry. The "seamless AI solution" now has two seams — and those seams are where errors, delays, and missed data live.
Custom solutions don't have this problem because they're designed for your specific stack from day one. They connect to your systems directly, handle your edge cases natively, and don't depend on a vendor building an integration that serves their broader market.
I've written more about evaluating these trade-offs in the AI Vendor Selection Checklist.
When Vendor Roadmaps Work Fine
I'm not anti-vendor. I'm a Microsoft Certified Trainer. I teach Copilot every week. Off-the-shelf AI tools are the right answer for a lot of businesses.
A vendor roadmap works fine when:
- The tool solves a commodity problem — email, documents, scheduling, basic analysis
- Your needs align with the mass market — what's good for most customers is good for you
- Switching costs are low — you could change tools without rebuilding your business
- The tool isn't touching your competitive advantage — it makes you more efficient, but your edge comes from elsewhere
Most businesses should use off-the-shelf AI for 70-80% of their AI needs. The question is what you do with the other 20-30% — the strategic workflows where generic isn't good enough.
Building Your Own Roadmap
The alternative to depending on a vendor's roadmap is building your own. Here's what that looks like in practice:
Step 1: Map Your Competitive Workflows
Identify the 3-5 workflows that directly create your competitive advantage. For a dental office, it might be patient acquisition and retention. For a construction company, estimation accuracy. For a coaching business, client engagement and progress tracking.
These are the workflows that deserve custom solutions. Everything else can be off-the-shelf.
Step 2: Own the Strategic, Rent the Commodity
Build custom AI for your competitive workflows. Use off-the-shelf tools for everything else. This gives you the best of both worlds: speed and low cost where it doesn't matter, and differentiation where it does.
This is exactly the approach we discussed in Buy or Build AI? The Cost Comparison Most Teams Skip.
Step 3: Maintain Exit Strategies
For every AI tool you depend on, answer this question: "If this vendor doubles their price or shuts down, what's our plan?" If the answer is "we'd be in serious trouble," you have a dependency problem that needs addressing — either by reducing the dependency or by owning the critical components yourself.
Step 4: Own Your Data
The most important asset in any AI system isn't the model — it's the data. Make sure you can export your data from any vendor at any time, in a format you can use elsewhere. If a vendor makes data export difficult, that's a red flag about their long-term intentions.
The Ownership Model
When we build custom AI solutions for clients, they own the intellectual property. Not us. If they want to take the code and walk away, they can. If they want to hire their own team to maintain it, they can.
What most clients choose instead: we handle hosting, monitoring, updates, and support for a monthly managed service fee. They get the ownership benefits without the maintenance burden. They control the roadmap. We keep the lights on.
It's the difference between renting an apartment (vendor SaaS) and owning a house with a property manager (custom + managed). Both work. But only one builds equity.
Questions to Ask Your AI Vendor
Next time a vendor shows you their roadmap, ask these questions:
- "What happens to my data if I leave?" — Full export in a standard format, or are you locked in?
- "How many customers requested this feature before you built it?" — Are they building for you or for their average customer?
- "What's your pricing history over the last 3 years?" — Trends tell you more than current prices.
- "Can I access the API directly?" — If you need to build around them, is that possible? Or are you trapped in their UI?
- "What integrations have you deprecated?" — This tells you what they consider low priority. If your system is on that list next, what's your plan?
These aren't adversarial questions. They're due diligence. Any vendor worth working with will answer them clearly.
The Bottom Line
Your AI vendor is building a product for their market. Your business needs a solution for your market. Sometimes those align perfectly. Sometimes they don't.
The businesses that get AI right don't outsource their strategy to a vendor's roadmap. They own the pieces that matter, rent the pieces that don't, and always have a plan for what happens when the roadmap changes.
Because the roadmap always changes. The only question is whether you're driving — or riding in the back seat.
