The Next Frontier of Headless, Agentic AI

As diverse as the methods and uses of AI are becoming in today’s world, people really have only been exposed to it through one manner: the chat.

Whether it was the traditional service chatbot for a big brand or asking ChatGPT both productive and distracting questions, AI (to this point) has been a conversational transaction. I ask the AI a question or to do something, the three dots appear on the screen, and then it provides a response. Now, the nature of that conversation has evolved dramatically in recent years, with AIs able to learn and adjust to your language and do greater tasks, but it still has been pigeonheld by this one interface.

That is changing thanks to headless AI, which is about to unlock a greater power that will free AI and its users in order to accomplish more.

AI on the Move

If you’re a developer or tech-head, you’ve likely heard the term “headless” for a while now. If not, what comes to mind is probably more like the Headless Horseman. But oddly, both can prove the point.

When we say headless, what we mean is a back end (the code and internal guts of the tool) that is decoupled from the front end (what the user interacts with) and connected through APIs. Traditionally, the head (front end) sits on top of the body (back end) and works as one. In a headless architecture, the back-end body can distribute data, content, actions, etc. to a number of environments simultaneously, pushing it to the head no matter where it is.

So for AI, instead of the tool sitting on top of a website or app, it is engrained in the platform itself, so it looks like part of the interface rather than an extension or add-on. Where that benefits is in what we began talking about with the chat interface. Headless AI opens up a breadth of new surfaces where you can interact. You can link your CRM with Slack and Google Docs, for instance, to create automation workflows that make collaboration easier.

Let’s use Google as an example. Gemini is available in chat formats in GMail and Google Drive, among other tools. But now it is also a different interface within Google Meet. Instead of having to kick off a chat, you can click a singular button in the top corner of your meeting and Gemini will transcribe the conversation. That’s the power of a headless AI architecture (though there’s a second benefit we’ll get to in a bit that takes this to another level).

Not every situation allows for the time and attention to have a conversation. Apps like Uber and Waze have figured out how to provide a customer experience in brief taps and swipes where focus is limited, rather than typing on a small mobile keyboard.

That same power is coming to AI, because not everyone has time for a conversation. And it’s even easier to spin up a headless AI than it is building into the traditional chat interface.

We have been sold on chat as the mode of initiation for AI because that was what was possible. It was the only way. It’s not hard to decide on chicken for dinner when nothing else is in the fridge. But that’s not the case anymore.  

The Power of Headless AI

One of the reasons we’re beginning to see headless AI appear is because the AIs themselves are getting sophisticated enough to leverage the power of a headless architecture.

Take Salesforce’s Einstein AI, for example. It is to the point where Salesforce feels comfortable enough to expose it to an API. And the benefit here is that in this headless environment, Salesforce’s AI can now access all of your data, actions, etc. from your Salesforce Data Cloud and other platforms and provide more accurate and personalized experiences.

Let’s go back to the Gemini and Google Meet example. Gemini’s notetaker doesn’t have the full awareness of your data. You may mention a brand name, but Gemini doesn’t know your relationship to it. But in that situation with a headless Salesforce AI, for example, it could go into your CRM, see that the brand was a partner, and pull recent opportunities and historical information to boost the context around your conversation.

An even better example is, while a general AI could whip up a promotional campaign for your marketing efforts, one tied to your data could pull your top five best-performing products over the last year and create a campaign specifically tied to those use cases. 

This creates a massive value proposition. Why would a company use an agnostic AI tool when it can use one that is engrained into its systems and data?

Divergence, Not Convergence

Eventually, it’s likely that all the major software players have their own headless AI (Salesforce is just ahead of the game). This is the path we’re headed down. Rather than converge toward one AI that does everything for everyone, we’ll have a slew of AIs that have access to specific data and platforms to handle certain jobs. In the future, you may have 3-4 different headless AIs performing actions within your customer experience.

That doesn’t mean that all AIs are going to survive. But it indicates a path for growth. Part of what makes AI exciting is that it allows you to do something you could have done before, but now can do more quickly and efficiently. This, however, is opening up opportunities that have never been done before. To me, that’s even more exciting.