For two years, "AI in business" mostly meant chat: ask a question, get an answer, copy the answer somewhere useful. 2026 is the year that changed. The conversation now is about agents: AI that doesn't just draft the email but looks up the order, checks the delivery date, updates the record and then drafts the email.
Something quietly important made that shift possible, and it wasn't a bigger model.
The standard that snuck up on everyone
In late 2024, Anthropic released the Model Context Protocol (MCP), an open standard that lets AI systems connect to tools, databases and applications in a common way. Within a year it had been adopted across the industry, and in December 2025 it was donated to the Linux Foundation's new Agentic AI Foundation, with OpenAI, Google, Microsoft and AWS among the founding members. Thousands of MCP connectors now exist for everything from CRMs to accounting platforms.
In plain terms: there is now an agreed way to plug AI into business systems: the "USB port" moment. Which moves the interesting question from "which AI should we use?" to "what can ours actually reach?"
The gap between piloting and production
Industry surveys this year tell a consistent story: the large majority of businesses have now tried AI agents, but only a small fraction run them in production. The blockers are rarely the AI itself. They're the unglamorous things underneath:
- Systems with no API. If the only way into your ERP is a human at a keyboard, an agent can't help you.
- Data that can't be trusted. An agent acting on wrong data doesn't make mistakes slower; it makes them faster.
- No sensible permissions. An agent should see exactly what the person it works for can see. If your access control is "everyone's an admin", agents inherit that mess.
- Processes that live in people's heads. You can't delegate a workflow nobody has ever written down.
Notice that every one of those is a problem worth fixing even if you never deploy an agent.
"AI-ready" means "integration-ready"
This is the honest version of AI readiness: clean APIs in front of your core systems, data you'd stake a decision on, access control that reflects reality, and processes made explicit. Businesses that have invested in integration for years are discovering they're accidentally well-prepared; businesses that skipped it are discovering the bill.
That groundwork is our home turf: it's what we've built for clients since long before it had an AI-shaped reason. If you want to know how far your systems are from being something an AI agent could safely use, we'll give you a straight answer.