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Bots: Disruption or Bubble?

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Bots: Disruption or Bubble?

Learn why one developer thinks that bots can be both a good and a bad thing, and the different use cases in which each scenario is true.

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The entire tech industry seems to be buzzing with “bot” fever. I and my co-founders often see a “bot” company and discuss its business model. Chirag Jog has always been enthusiastic about the bot wave, while I have been mostly pessimistic — especially about B2C bots. We should consider that there are many types of “bots” — chat bots, voice bots, AI assistants, robotic process automation (RPA) bots, conversational agents within apps or websites, etc.

Over the last year, we have been building some interesting chat- and voice-based bots, which has given me some interesting insight. 

What Are Bots?

Bots are software programs which automate tasks that humans would otherwise do themselves. Bots are developed using machine learning software and are expected to aggregate data to make the interface more intelligent and intuitive. There have always been simple rule-based bots, which provide a very specific service with low utility. In the last couple of years, we are seeing the emergence of intelligent bots that can serve more complex use-cases.

Why Now?

Machine Learning, NLP, and AI technologies have matured, enabling practical applications where bots can actually do intelligent work more than 75% of the time. Has general AI been solved? No. But is it good enough to do the simple things well and give hope for more complex things? Yes.

Secondly, there are billions of DAUs on Whatsapp and Facebook Messenger. There are tens of millions of users on enterprise messaging platforms like Slack, Skype, and Microsoft Teams. Startups and enterprises want to use this distribution channel and will continue to experiment aggressively to find relevant use-cases. Millennials are very comfortable using the chat and voice interfaces for a broader variety of use cases since they used chat services as soon as they got online years ago. As millennials become a growing part of the workforce, the adoption of bots may increase.

Thirdly, software is becoming more prevalent and more complex. Data is exploding, and making sense of this data is getting harder, and requiring more skills. Companies are experimenting with bots to provide an easy-to-consume interface to casual users. So, non-experts can use the bot interface while experts can use the mobile or web application for the complex workflows. This is mostly true for B2Bs and enterprises.

A good example is how Slack has become the system of engagement for many companies. We require all the software we use (GitLab, Asana, Jira, Google Docs, Zoho, Marketo, Zendesk, etc.) to provide notifications into Slack. Over time, we expect to start querying the respective Slack bots for information. Only domain experts will log into the actual SaaS applications.

Types of Bots

Let's go over three of the different types of bots: B2C bots, B2B bots, and voice-based bots.

B2C Chatbots

Consumer-focused bots use popular messaging and social platforms like Facebook, Telegram, Kik, WeChat, etc. Some examples of consumer bots include weather, e-commerce, travel booking, personal finance, fitness, and news apps. These are mostly inspired by WeChat, which owns the Chinese market and is the default gateway to various internet services. These bots show up as contacts in these messenger platforms.

Strategically, B2C bots are basically trying to get around the distribution monopoly of Apple and Google Android. As many studies have indicated, getting mobile users to install apps is getting extremely hard. Facebook, Skype, and Telegram hope to become the system of engagement and distribution for various apps thereby becoming an alternate App Store or Bot Store.

I believe that SMS is a great channel for basic chatbot functionality. Chatbots with SMS interface can be used by all age groups and in remote parts of the world where data infrastructure is lacking. I do expect to see some interesting companies use SMS chatbots to build new business models. Also, mobile bots that sniff or integrate with as many of your mobile apps to provide cross-platform and cross-app “intelligence” will succeed — Google Now is a good example.

An often cited example is the DoNotPay chatbot, which helps people contest parking tickets in the UK. In my opinion, the novelty is in the service and in its efficiency — not in the chatbot interface itself. Also, I have not met anyone who uses a B2C chatbot even on a weekly or monthly basis.

B2B Bots

Enterprise bots are available through platforms and interfaces like Slack, Skype, Microsoft Teams, website chat windows, email assistants, etc. They are focused on collaboration, replacing/augmenting emails, information assistants, support, and speeding up decision-making/communications.

Most of the enterprise bots solve niche and specific problems. This is a great advantage considering the current state of AI/ML technologies. Many of these enterprise bot companies are also able to augment their intelligence with human agents thereby providing better experiences to users.

Some of the interesting bots and services in the enterprise space include:

  • x.ai and Clara Labs provide a virtual assistant to help you set up and manage your meetings.
  • Gong.io and Chorus provide a bot that listens in on sales calls and uses voice-to-text and other Machine Learning algorithms to help your sales teams get better and close more deals.
  • Astro is building an AI-assisted email app that will have multiple interfaces including voice (Echo).
  • Twyla is helping make chatbots on websites more intelligent using ML. It integrates with your existing ZenDesk, LivePerson, or Salesforce support.
  • Clarke.ai uses AI to take notes for your meeting so you can focus better.
  • Smacc provides AI-assisted, automated bookkeeping for SMBs.
  • Slack is one of the fastest growing SaaS companies and has the most popular enterprise bot store. Slack bots are great for pushing and pulling information and data. All SaaS services and apps should have bots that can emit useful updates, charts, data, links, etc. to a specific set of users. This is much better than sending emails to an email group. Simple decisions can be taken within a chat interface using something like Slack Buttons. Instead of receiving an email and opening a web page, most people prefer approving a leave or an expense within Slack. Slack will add the ability to embed cards/webviews/interactive sections within chats. This will enable more complex use cases to be served via bots. Most enterprise services have Slack bots and are allowing Slack to be a basic system of engagement.

Chatbots and voice-based bots on websites will be a big deal. Imagine every website having a virtual support rep or a sales rep available to you 24/7 in most popular languages. All businesses would want such agents or bots for greater sales conversions and better support.

The automation of back office tasks can be a huge business. KPOs and BPOs are a huge market. If you can build software or software-enabled processes to reduce costs, then you can build a significant company. Some interesting examples are Automation Anywhere and WorkFusion.

Voice-Based Bots

Amazon had a surprise hit in the consumer electronics space with their Amazon Echo device, which is a voice-based assistant. Google recently released their own voice-enabled apps. Voice assistants provide weather, music, searches, e-commerce ordering via NLP voice interfaces, and more. Apple’s Siri should have been leading this market, but as usual, Apple is following rather leading the market.

Voice bots have one great advantage with the miniaturization of devices (i.e. Apple Watch, Earpods, smaller wearables): the only practical interface is a voice. The other option is pairing the device with your mobile phone — which is not a smooth or intuitive process. Echo is already a great device for listening to music with its Spotify integration. Just this feature is enough of a reason to buy it.

Conclusion

Bots are useful and here to stay. I am not sure about the form or the distribution channel through which bots will become prevalent. In my opinion, bots are an additional interface for intelligence and application workflows. They are not disrupting any process or industry. Consumers will not shop more due to chat or voice interface bots, employees will not collaborate as desired due to bots, and information discovery within your company will not improve due to bots. Actually, existing software and SaaS services are getting more intelligent, predictive and prescriptive. So, this move towards “intelligent interfaces” is the real disruption.

My concluding predictions:

  • B2C chatbots will turn out to be mostly hype and very few practical scalable use cases will emerge.
  • Voice bots will see increasing adoption due to smaller device sizes. IoT, wearables, and music are excellent use cases for voice-based interfaces. Amazon’s Alexa will become the dominant platform for voice controlled apps and devices. Google and Microsoft will invest aggressively to take on Alexa.
  • B2B bots can be intelligent interfaces on software platforms and SaaS products, or they can be agents that solve very specific vertical use-cases. I am most bullish about these enterprise-focused bots that are helping enterprises become more productive or increase efficiency with intelligent assistants for specific job functions.

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Topics:
artificial intelligence ,bots ,big data ,nlp

Published at DZone with permission of Kalpak Shah. See the original article here.

Opinions expressed by DZone contributors are their own.

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