AI in Restaurants Isn’t a Feature Problem. Context and Action Are the Problems. We’re in the middle of a gold rush. Every restaurant tech company is racing to position itself as an AI company—launching copilots, assistants, chatbots. On the surface, it feels like rapid innovation. But if you zoom out, most of what’s happening right now is familiar. Historically, vendors built walled gardens by restricting access to data. Now, many are building AI-powered walled gardens—tools that work best (or only) within their own ecosystem. Same strategy. New interface. And it still doesn’t solve the underlying problem. — ### The Real Constraint: Context AI is only as powerful as the context it can access. If a model can only see labor data, it will give you labor insights. If it can only see POS data, it will give you sales insights. But restaurants don’t operate in silos—they operate as interconnected systems:
- Labor impacts service
- Service impacts retention
- Menu design impacts both
When AI operates on a narrow slice, it can sound smart—but it can’t be holistically useful. And no single vendor is going to own the entire stack. That’s just the reality. So the question isn’t, “Which AI tool should we use?” It’s: “Where does the context live—and how open is it?” — ### The Missing Piece: Open Data A durable AI strategy requires more than just access to data. It requires an open data philosophy. That means:
- Systems that integrate easily
- Data that can flow across tools
- Vendors that prioritize interoperability over lock-in
Because a closed system—even with great AI—will always be limited. An open, context-rich layer compounds in value:
- More integrations → more context
- More context → better insights
- Better insights → more action
Solutions are starting to emerge that take this approach—platforms designed to sit across systems, aggregate context, and remain fundamentally open. A solution like Axial Shift is one example of this model, where the goal isn’t to replace your stack, but to connect it. — ### This Isn’t About Replacing Analysts—It’s About Elevating Them AI doesn’t replace roles like FP&A—it amplifies them. Today, most analytical teams are constrained by volume:
- Too many questions
- Too many manual pulls
- Too many competing priorities
So they spend time finding insights instead of developing them. With the right context layer in place:
- Insights surface in minutes instead of days
- Teams can validate and go deeper, faster
- More time is spent on strategy, experimentation, and impact
The role doesn’t go away—it becomes far more powerful. — ### The Next Shift: From Insight → Action Here’s where things get more interesting—and where most of the market hasn’t caught up yet. Right now, most AI tools are focused on delivering answers. But the real opportunity isn’t answering questions. It’s driving action. When AI has access to a full context layer, it can do more than identify opportunities:
- It can suggest the exact contest to run to drive attachment
- Draft the message to your team
- Identify who should lead the initiative based on performance
- Highlight where scheduling adjustments need to happen
And increasingly, it can go one step further: It can help execute. Imagine sitting down at your desktop, connecting a model like Claude to a context-rich system, and within minutes:
- You’ve identified an opportunity
- Validated it with deeper analysis
- Generated an operational plan
- And triggered the systems that put it into motion
Not just insight. Not just recommendation. Execution. Of course, with human oversight—but at a speed and scale that wasn’t previously possible. — ### Why This Matters: A Return to Hospitality All of this only matters if it improves the guest experience. The winners in this next phase won’t be the companies with the best chatbot. They’ll be the ones who use AI to:
- Improve service consistency
- Empower teams in real time
- Recognize and replicate great performance
- And ultimately, make guests feel taken care of
This is a return to hospitality—enabled by better tools, not replaced by them. — ### What Should You Do Now? If you’re a restaurant operator evaluating AI, don’t start with features. Start with structure. Ask:
- Where does my operational context live today?
- How fragmented is it?
- Do I have a layer that can unify it—and keep it open?
Then look for solutions that:
- Sit across your systems, not inside just one
- Are designed to integrate broadly
- And are building toward action, not just insight
Platforms like Axial Shift are one path to explore—but the broader principle matters more than any single vendor:
AI only delivers real value when it has full context and the ability to drive action.
— ### A Note to Restaurant Tech Providers This isn’t just a shift for operators—it’s a shift for all of us building in this space. The next generation of winners won’t be defined by who builds the best standalone AI. They’ll be defined by who contributes the most to connected ecosystems—and who enables action, not just analysis. That means:
- Designing for openness
- Making integration easy
- And thinking beyond your own product boundaries
Because the future isn’t a bigger walled garden. It’s a connected garden—where the industry cooperates, collaborates, and delivers the guest experience that today’s guests expect. — The companies that get this right won’t just “have AI.” They’ll have something far more valuable: A system that helps their teams ask better questions, get better answers—and take better action—faster than ever before.
