Everyone is building a bot. At Talla, we talk about this a lot because we are too, so we have to make some bets on how this space plays out. Around the office we frequently use the term "Botageddon" because we are constantly discussing what happens when you have dozens of bots on your messaging platforms that are all trying to do various tasks for you. It's too many and it can create a terrible user experience as a result.
The underlying cause of this bot problem is that, the state of A.I. is not good enough to build a good general intelligence bot. Some big companies are trying, and you've probably used their products (Siri, Cortana, Alexa), and come away amused but not impressed. Some startups are trying too, but I can't imagine they can outwit these big tech companies on something like this. The result is, a lot of companies (mine included) are taking approaches to building vertically targeted bots. By limiting the scope of what the bot has to know and do, it is possible to build something pretty good for that domain. And we all know that if we can get something good enough to sell, we can keep improving it until the technology one day allows us to build a real human like metamind bot.
With all these vertically targeted bots, how many will an average user need? I really doubt that you want to use a banking bot, a fitness bot, a dating bot, a restaurant bot, etc, etc, etc. Since the current trend is for all the bots have names, you will forget which bot does what if you have too many. And sometimes the bots may conflict with each other. The big question then is, if the user experience of using 47 different bots isn't a good one, how does it get resolved? Where does the ecosystem settle in to a stable equilibrium?
I see 3 key possibilities for resolving this Botageddon.
1. Industry Consolidation - I think this scenario plays out if the technology and algorithms improve fast enough that we move quickly from a period of too many bots to a period where building a generalized intelligence bot is feasible. In this case, the initial winning platforms/bots buy up or merge with the smaller niche bots that didn't achieve scale. Some players get to a general intelligence bot by combining lots of niche bots.
2. MetaBots - In this scenario, meta-bots emerge that manage and route requests through the other bots. This could take two forms. One form is meta-bots that are intentionally designed to be meta-bots. Much the way Google is a search engine that helps you find the right information on the web, a meta-bot could help you find the right bot to do the task, or get the information, you need. The second way could be less direct, with some popular bots becoming sort of like meta-bots by default, maybe because they are the first to build bot APIs for easy integration, and because users are most comfortable with their interfaces.
3. Platform Management - In this scenario, the messaging platforms on which most of these bots are built will serve the function of routing requests to the right bot. So, a Slack or WhatsApp or even a mobile platform like Android might develop some functionality to do the routing.
As the bot industry emerges, there may be other solutions that emerge, but for now, these are the 3 ways I see the bot industry playing out as it matures. If you have other ideas, I would love to hear your feedback.