The 2 things holding AI assistants back (and it’s not tech)

We’ve long had a vision for what AI assistants could be capable of. Hal, Computer from Star Trek, Kitt from Knightrider, Holly from Red Dwarf, JARVIS from Ironman, Samantha from Her and so on.

In real life, there’s been various attempts at creating this all-encompassing assistant. An AI concierge that’s at your beckoning call, accessible from any device, and that can deliver on anything you ask it.

—

Register for this free CX maturity workshop with yours truly and Cognigy.

—

Big tech attempts to create AI assistants

We know about the big tech companies and their efforts to deliver this. Apple’s Siri, Amazon’s Alexa, Google’s Assistant, Samsung’s Bixby. Each has their own challenges.

• Apple doesn’t allow much third party developer capability, meaning it’s functionality is limited to what Apple decides it should do.
• Amazon does have a third party ecosystem but hasn’t been able to crack discoverability, monetisation or keep pace with the functionality developers need to deliver robust experiences. A walled garden approach isn’t going to work because it takes too much management and effort. You’ll never move quickly enough and you’re constantly conflicted between your incentives and the needs of third parties.
• Google made an attempt to do the same as Amazon with conversational actions, realised how hard it is and how much effort it requires to create and sustain a developer community, and so has now cancelled the program and is pushing for Google Assistant to be a launchpad into existing apps and functionality. A conversational assistant on the front end, a GUI on the back and relying on existing services.
• Samsung could have nailed it with Bixby, created by the same team that built the first Siri (Apple acquired Sri, and Samsung acquired Viv, both built by Adam Cheyer and Dag Kittlaus), but it didn’t have the adoption and user base to make it work.

What’s interesting is that the big assistants don’t fail on the AI side. Most of them understand almost everything you say today. They fail on the fulfilment side (aside from Samsung which doesn’t have a huge user base for Bixby, despite its huge device presence).

What’s interesting is that the big assistants don’t fail on the AI side. Most of them understand almost everything you say today. They fail on the fulfilment side Click To Tweet

Issue no. 1: Fulfilment

They can’t do everything you’d like them to do because they don’t have access to the services they need. How can you ask Alexa to book you a hotel room for Thursday if Booking.com doesn’t have a skill? How can you ask Siri to add cucumber to your shopping list if Sainsbury’s can’t play Siri’s game?

How can you ask Alexa to book you a hotel room for Thursday if Booking.com doesn’t have a skill? Click To Tweet

Cue the smaller players

Maybe a smaller, more focused player could deliver on this? If so, you’d look at SoundHound , Mycroft AI Inc, and other smaller players like Magic, Omega or Velocity Black. Perhaps they could offer the kind of functionality that the big guns can’t?

In some cases, they can. Mycroft has a whole community of developers building out capabilities for the open source assistant. SoundHound has a whole bunch of domains that it can handle really well. It’s language model for finding a place to eat is second-to-none.

The challenge for those companies again isn’t on the AI side. They can all understand what you say, some even better than the big guns. The challenge for them is on the distribution and fulfilment side.

Issue no. 2: Distribution

They don’t have the reach of Amazon, Apple and Google, and so they can’t possibly become the go-to assistant for the masses.

All the devices we have to hand are mainly Apple and Google (iOS or Android) or Amazon (Alexa). Those smaller players can’t compete for distribution because each of those devices has a gatekeeping assistant already.

And so, if you don’t have the distribution, you don’t have the users, and if you don’t have the users, you can’t encourage third parties to develop the capabilities you need to become an all-encompassing, fully capable assistant.

Perhaps the new EU legislation will change this and force the big guns into allowing access to other assistants on their devices, but you’d still have the fulfilment issue.

Solving fulfilment

You could consider building all of the fulfilment services yourself, but it’s impossible. Just look at this simple use case from Velocity Black’s website:

A guy asks Siri to ask Velocity to book him a gym class tonight. Siri responds with “There’s a new Hitt class. Your first one is complimentary for Velocity members”.

To deliver the above, all Velocity needs is to have a partnership with one big gym, like a David Lloyd or Nuffield, and throw a promo in there when someone asks for gym classes. But that’s not what the guy asked. He asked it to book him a class.

To fulfil that properly, Velocity needs to:

1. know which gym the guy is a member of,
2. interrogate the classes on offer on that evening,
3. poll an API to see whether there’s any availability,
4. suggest the type of class, time and availability back to the user (ideally, it’d be a class that Velocity knows the guy enjoys through knowledge of previous bookings),
5. have it confirmed by the user,
6. book it,
7. confirm the booking

This whole journey is small fry. Not very complex, really. Even if the time didn’t workout and you had to go back to the class search step, it’s not the end of the world.

Fulfilment challenges

However, this journey can’t be delivered today. None of these gyms have open APIs that would enable a third party to make a booking. You’d have to do it on their website directly.

Now, Velocity could use RPA or humans on the backend to fulfil this, but that’d take forever. The guy may as well just do it himself.

This is the problem that all assistants face, even the big ones that have the distribution, they don’t have the capability to fulfil the long tail of requests that would make them indispensable.

This is the problem that all assistants face, even the big ones that have the distribution, they don’t have the capability to fulfil the long tail of requests that would make them indispensable. Click To Tweet

This is why Magic, SoundHound, Velocity Black and Omega all pivoted to serve the enterprise market. It’s the only way to create revenue at the minute.

What about domain-specific assistants?

So then you’re left with trying to focus on specific domains. Individual companies trying to crack those long tail use cases. Jetson’s food ordering use case, RedRoute’s taxi booking capability, KAI Kasisto’s banking assistant.

But then, you have neither the distribution (aside from direct assess via an enterprise white labelling the solution, which isn’t part of the all-encompassing assistant vision) nor the breadth of capability required for a personal assistant. You’re again stuck with going to the enterprise for revenue and hoping that, in the long term, you can weave a distribution position with one of the big assistants, providing they can find a way to surface your capability to users.

The vision is still alive, it’s just a lot harder than some make it out to be

Don’t get me wrong, that vision is still there. One assistant (or one overarching assistant that integrates with thousands of other narrow assistants) that can fulfil your every desire. Something that knows what you need before you know you need it and can be proactive. And, to get there, it’s no longer a question of AI technology on the language front. We have that. NLP is so good now that we can understand what you say, no problem.

Many of the big assistants have the distribution and reach millions of people everyday (or are within earshot of millions) as well.

The biggest problem is in fulfilling requests, in integrating other assistants that can fulfil requests or in waiting for the rest of the world’s businesses to create infrastructure that’ll make their data and available via APIs to be consumed by AI front ends.

Not long now then, ey?