New AI tools launch weekly. Every existing SaaS product is adding 'AI features.' The market is full of tools that are genuinely useful and tools that are marketing-rebranded workflows. Small businesses need a framework to evaluate quickly and avoid tool sprawl.
1. Does it solve a specific, real problem I have? If you can't name the specific recurring task it addresses and estimate how much time it currently takes, you're buying a solution in search of a problem.
2. What is the data model? Where does your data go? Is it used for training? What happens if you cancel? Can you export your data? These questions apply to any data-touching tool.
3. What is the real cost at scale? Many AI tools have free or low-cost tiers that become expensive at volume. Understand the pricing model before you've built workflows that depend on the tool.
4. What is the switching cost? If this vendor raises prices, goes out of business, or changes their product, how hard is it to switch? High switching cost (because you've built deeply around one tool) is a risk.
5. Is there a credible free trial? For SMB AI tools, a meaningful free trial period is standard. If a vendor won't let you test before committing, that's a signal.
For tools central to your operations — CRM, accounting, core communications — verify that your data can be exported in standard formats. Vendor dependency is a real operational risk, and it's higher for AI-native tools that build proprietary models on your data.
How to choose AI tools wisely — avoiding lock-in, waste, and vendor risk
New AI tools launch weekly. Every existing SaaS product is adding 'AI features.' The market is full of tools that are genuinely useful and tools that are marketing-rebranded workflows. Small businesses need a framework to evaluate quickly and avoid tool sprawl.
1. Does it solve a specific, real problem I have? If you can't name the specific recurring task it addresses and estimate how much time it currently takes, you're buying a solution in search of a problem.
2. What is the data model? Where does your data go? Is it used for training? What happens if you cancel? Can you export your data? These questions apply to any data-touching tool.
3. What is the real cost at scale? Many AI tools have free or low-cost tiers that become expensive at volume. Understand the pricing model before you've built workflows that depend on the tool.
4. What is the switching cost? If this vendor raises prices, goes out of business, or changes their product, how hard is it to switch? High switching cost (because you've built deeply around one tool) is a risk.
5. Is there a credible free trial? For SMB AI tools, a meaningful free trial period is standard. If a vendor won't let you test before committing, that's a signal.
For tools central to your operations — CRM, accounting, core communications — verify that your data can be exported in standard formats. Vendor dependency is a real operational risk, and it's higher for AI-native tools that build proprietary models on your data.