This article first appeared as guest post on Venturebeat.
By now it’s clear that bots will cause a major paradigm shift in customer service, e-commerce, and, quite frankly, all aspects of software-to-human interaction.
For the moment, the state of the art of bots is bot-to-consumer, meaning bots communicating with humans. But at some point soon, bots will start talking to other bots. Enter the bot-to-bot era.
Imagine that a bot — let’s call her Annie — needs to answer a question from a customer but lacks information from her own backend systems. Annie is powered with artificial intelligence and spontaneously decides to reach out to another bot to get the information she needs. Annie aggregates the information and delivers it back to the customer.
Today when two software systems have to talk to each other, software developers need to implement an integration using APIs (application programming interfaces). This integration process is time consuming. That’s why, over the last couple of years, services such as Zapier, Scribe, and IFTT have become popular. They provide out-of-the-box interfaces to hundreds of software applications, allowing you to connect, for example, your CRM system with a mailing tool or analytics platform.
In the bot-to-bot era, however, each software application can talk to each other system, regardless of whether they have an actual API integration in place. Granted, bot-to-bot communication will not be used to exchange large amounts of data, but it will allow for ad-hoc communication between, for example, my banking software and a web shop. My banking software could talk to the webshop bot and ask for that missing invoice: “Niko needs an invoice for order 45678, can you provide that?”
The beauty of bot-to-bot communication will be that it is in plain English, it will be conversations that every human can understand. Assuming that all conversations between my bot Annie and other bots are archived, I will be able to go back and see how my two little bots came to a certain conclusion. In my banking example, when an invoice is missing after all, I could click on a “details” button, which would show me the conversation Annie had with the webshop. The archived bot-to-bot conversation would show me the webshop bot response, that the invoice will not be available for another couple of weeks.
But it gets better. If my bot is stuck in a conversation with another bot, she can call me in for help: “Niko, it’s Annie here, your finance bot. I’m talking to a supplier, but I’m having some trouble understanding what they are saying.” I could chime in — when I have time of course, a couple of hours later, since bots have unlimited patience — and I would rephrase the question of Annie and get the answer from the other bot. Next, Annie could continue the conversation and handle my business.
Didn’t we talk about connecting every online service with every other online service 10 years ago? What was it called again? The Semantic web? Every website was going to be annotated using standard data formats, allowing other services to crawl that data and use it in their own business logic. I believe that bots will deliver on that promise in the next 3 to 5 years, and this will not mean that all data will have to be uniformly formatted. Instead, bots will expose online services and data in plain English, allowing both humans and other bots to interact, even if they have never communicated before.
So, software developers, when you develop your platform for e-commerce, online marketing, finance, ERP or any other software solution, please think about the implementation of a smart bot, besides your traditional APIs, so next time when I buy a new BBQ online, my bot will alert me that it’s going to rain for the next two weeks.