When most business owners pick an AI tool, the question they're really asking is: "What if I choose wrong?" What if you build your whole workflow around ChatGPT and then a better option comes along? What if you train your team on one platform and it doubles in price next year? What if you're stuck?
It's a fair worry — and until recently, it was a real one. But something significant has shifted in the last few months, and it changes how you should be thinking about AI tool selection entirely.
The Problem With Picking a Platform
For the past few years, AI tools have been largely walled gardens. Anthropic's Claude lived in its own ecosystem. OpenAI's ChatGPT lived in its own. Google's Gemini, Microsoft Copilot, and everyone else were similarly siloed. If you wanted data to flow between them, you were writing custom code or doing a lot of manual copy-pasting.
This is the classic "vendor lock-in" problem. The more you build on one platform — the more workflows, integrations, and habits you create — the harder it becomes to switch, even if a better option emerges. It's the same reason businesses stay on clunky software long after they've outgrown it.
For small and medium businesses, this risk felt particularly sharp. You don't have a dedicated IT team to manage migrations. You don't have months to retrain staff. So you hesitate, or you go all-in on one tool and hope you picked the right horse.
What Just Changed
In December 2025, Anthropic, OpenAI, and Block (the company behind Square) did something unusual: they put their competitive interests aside and jointly launched the Agentic AI Foundation under the Linux Foundation. The goal is to create shared, open standards for how AI tools communicate with each other.
Anthropic donated its Model Context Protocol (MCP) — a standard that lets AI tools connect to external data sources and services — as a founding project. OpenAI contributed its AGENTS.md specification. These aren't marketing announcements. They're the technical plumbing that allows AI from different companies to hand off work, share context, and collaborate on tasks.
Then in February 2026, NIST (the US National Institute of Standards and Technology) launched its AI Agent Standards Initiative, a government-backed effort to create governance frameworks for how AI agents interoperate securely across different platforms. When governments start building standards around something, it's a signal that the technology is moving from "experimental" to "infrastructure."
Why This Is Actually Good News for Buyers
Here's the practical upshot: the major AI vendors are converging on shared protocols. That means the risk of picking "the wrong" platform is shrinking.
Think of it like email. You can have a Gmail account and I can have an Outlook account, and we can still email each other — because everyone agreed on the same underlying standard decades ago. The AI industry is now building its version of that. Tools that support open protocols like MCP can pass information and tasks between them, regardless of which company built them.
For your business, this means:
- Your data isn't trapped. If you move from one AI assistant to another, your integrations and workflows built on open protocols come with you.
- You can mix and match. Use the best tool for each job — Claude for writing, Gemini for spreadsheets, a specialist tool for customer support — and have them work together rather than in isolation.
- You're buying on merit, not fear. The question shifts from "what if I'm locked in?" to "which tool is actually best for this task right now?"
What to Actually Look for When Choosing an AI Tool
You don't need to understand the technical details of MCP or A2A protocols to benefit from them. But there are a few simple questions worth asking before you commit to any AI platform.
Does it support open protocols? Look for tools that mention MCP support or API openness. Claude, ChatGPT, Gemini, and Microsoft Copilot all now support MCP. This is a green flag — it means your integrations will likely survive a future platform switch.
Can it connect to your existing tools? The best AI tools don't replace your current systems — they integrate with them. If an AI assistant can read from your CRM, pull data from your calendar, and push updates to your project management tool, that's interoperability in action.
Is the vendor invested in the ecosystem? Companies that contribute to open standards (rather than building proprietary ones nobody else uses) are betting on the shared future. That's usually a safer long-term bet for you too.
If you're still early in your AI tool selection, the post on choosing an AI assistant for your business is a good starting point for thinking through the basics.
This Doesn't Mean Every Tool Is Equal
Open standards reduce lock-in risk, but they don't flatten the differences between tools. Claude is still better at long-form writing and nuanced reasoning. ChatGPT is deeply integrated into the Microsoft ecosystem. Gemini has advantages in Google Workspace. Specialist tools exist for legal research, customer support, financial analysis, and dozens of other domains.
Interoperability means you're not choosing a prison — you're choosing a starting point. Pick the tool that solves your most pressing problem today. If your needs change, switching becomes easier over time, not harder.
The old question was: "Which AI tool won't trap me?" The new question is: "Which AI tool is genuinely best for what I need right now?"
The Bigger Picture
What's happening in AI right now mirrors what happened with the internet in the 1990s. Early on, every platform was isolated — CompuServe users couldn't email AOL users. Then shared standards emerged, and suddenly the whole thing became dramatically more useful for everyone.
We're at a similar inflection point with AI. The fact that Anthropic, OpenAI, Google, and Microsoft are all building toward the same interoperability standards — and that governments like NIST are formalising the governance layer — suggests we're crossing from the "wild west" phase into something more durable.
For SMBs, that's an opportunity. The businesses that start building AI-assisted workflows now — even imperfect ones — will have a head start when the ecosystem matures. And if they pick tools that support open protocols, they won't have to start from scratch when better options emerge. They'll just swap out the parts that need upgrading, the same way you'd replace a single piece of software rather than rebuilding your entire business process.
The fear of picking wrong is real, but it's shrinking. The more useful question to ask yourself now is: what problem do I want AI to solve first?