Many organizations are turning to bots — software code designed to automate time-consuming tasks — to save time and money. For instance, AT&T’s Technology and Operations automation team developed bots to handle routine, time-consuming duties such as creating engineering work orders and updating systems for network-boosting activities.

Here at CDW, collaboration solution architect Sankar Nair built a vendor bot to help coworkers easily search for contact and other information from among the hundreds of manufacturers that are our partners. Before the bot, most of that information was populated in a spreadsheet stored in a shared Box folder that took engineers at least five steps to access.

There has been a lot of talk lately about whether bots will replace applications. I don’t think they are necessarily competing, though.

Bot Geek Out

One of the advantages of bots is the way they chain flows of things together into a single command, whereas apps tend to be dedicated to a specific need. I have a travel app, for example, that gets me schedules, looks up flights, reserves cars or identifies hotels. A bot might summon more nuanced information: Let’s say that I need to go on a trip to my branch office in Las Vegas. The bot knows I’m not going for a fun trip or a bachelor party because it taps information based on artificial intelligence. So, it won’t show me best ticket prices for magic shows on the strip, but it might alert me if my colleague’s flight is delayed and how that will affect my schedule.

When you look at what’s behind the bot revolution, the bots that are getting attention — think Apple’s Siri and Microsoft’s Cortana — were built on machine learning and AI platforms that understand natural language well. The same holds for chat bots; you can chat with them in a fairly natural way. So part of what is new and innovative is the way we interface with bots.

Many business managers ask me what all the chatter about bots ultimately will mean for their companies. They want to know if it is a wise move to integrate bots with their enterprise applications. If bots are the next big thing, how will they impact mobile applications? How can a bot help the sales force? How will bots affect external-facing customer engagements? These are all good questions.

Since bots are built on AI, natural language processing and machine learning, managers need to understand how these technologies relate to the goals of their business or the organization’s mission. Bots are only an interface. You must know what the technologies mean to your business to answer these questions about the interface itself.

Learning from One Another

Technically, a bot can do what an app does, but it may or may not be as efficient.  A bot is more about the method of input. Instead of a form or screen or web-based item, typically a bot uses a voice or text messaging interface. You either are going to send a message or talk to the bot. In the future, we will see a convergence in what apps and bots do on the back end. Apps will get smarter using machine learning and AI. Bots will get smarter using the same back-end infrastructure as apps.

Apps and bots have not converged yet because the tools for naturalized language processing for bots remains a specialized domain. It is relatively easy to create a bot but more difficult to integrate natural language and AI. Apps have been around a lot longer — there are tons of them — so the interface and interaction between them is codified. How a user deals with an app on a mobile phone is obvious, given web-like forms, but the back-end infrastructure continues to evolve.

The first iterations of bots are mainly command-driven: “Alexa, what time is it?” The next-gen versions will allow interactions derived much more from natural language. And that is what’s getting people excited.

Read more about efforts to boost productivity using bots in this CDW blog post by solution architect Sankar Nair.

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