Episode 9: Kit Cox, Founder & CTO of Enate Ltd

[00:00:00] Hello and welcome to the Conversational AI News Podcast. Today I'm joined by Kit from Enate AI. Kit, you're very welcome.

[00:00:08] Good to see you, Ian. Great to meet you.

[00:00:09] Thank you for being with us. Kit, would you start with a background on yourself? Tell us what's been your journey. I know, by the way, from your LinkedIn, you started coding when you were 10. What language was that? Tell us more.

[00:00:21] Kit, okay. So I started coding at the age of 10 in BBC Basic because that's how much grey hair I have. And so yes, I got a BBC Micro because my dad is also a self-professed geek like I am at the age of 10 and so that's what I started coding in.

[00:00:46] Take us through the journey then from then.

[00:00:50] Kit, okay. So, so, so, so I, I'm actually a, I'm a manufacturing engineer by kind of training and education and all of those kinds of things. Yeah. And a software developer by hobby and then actually largely by chunk of career. Yeah. And I, you know, I've had some proper jobs along, along the way, but I've yeah, but I, I've had some proper jobs along the way.

[00:01:19] I've run, I've run a business really in three different guises. Yeah. So I've run a kind of bespoke software development business where we did individual things for individual customers. Yeah.

[00:01:30] Created a, a product business with a very, very ultra niche targeted product aimed at a very small sector of the, of the BPO market. Yeah.

[00:01:38] And then in, in 2017, uh, at a point in my life where I, I'd actually been doing a lot working with service provider organizations and really understanding how technology was brought to bear in service provision and service delivery.

[00:01:58] Uh, we started to see some new automation technologies starting to appear at that time.

[00:02:05] Things like RPA, but, you know, and actually at that, at that point in time, uh, I drew a slide, you know, one, one slide, which, which, you know, said the, you know, the future of service delivery.

[00:02:20] It was really, really me noodling on how services would be delivered as different types of automation technology could start automating different types of human capability.

[00:02:36] And then really going through the thought process of, okay, all of those are going to be different technologies that come from different vendors with different underlying capabilities.

[00:02:48] And they need to come to bear amongst the carbon based workforce, amongst real actual intelligence, not, not, not just the artificial.

[00:02:56] The other AI, actual intelligence, actual intelligence.

[00:02:59] Yeah.

[00:03:00] And, and actually going, there is going, you're going to need something to allow you to glue together a, a customer delivery, a customer service journey across those different capabilities and help you manage the pivot as, you know, carbon turns to silicon in different types of capabilities at different points in time.

[00:03:22] And, and then slightly foolishly, uh, set out to go, well, why don't we go and build that?

[00:03:28] Uh, that glue layer.

[00:03:31] Right.

[00:03:31] The thing that's going to allow you to, to manage services, deliver the world's best services and automate them more and more over time.

[00:03:40] And that's what we built with, uh, with, with innate.

[00:03:42] Yeah.

[00:03:42] And as with many good businesses, we pivoted, you know, we, we basically built this business on the back of the previous one.

[00:03:50] Yeah.

[00:03:50] Right.

[00:03:51] Right.

[00:03:51] Interesting.

[00:03:52] And that, so bring us up to date then.

[00:03:54] And so if, if I said to you now, what's innate AI, then of course there's a, there's a clue there.

[00:03:59] There's a clue in the name, I think.

[00:04:01] Right.

[00:04:01] But would you give us an overview now?

[00:04:02] Yeah.

[00:04:03] Yeah.

[00:04:03] So, uh, innate is a platform.

[00:04:06] It is a, it's a, it's a workflow platform for delivering and automating world-class services.

[00:04:12] Yeah.

[00:04:14] Yeah.

[00:04:14] So, and the AI bit of it is, comes in the automating bits of world-class services.

[00:04:18] Yeah.

[00:04:19] So there, there's the core, which is let's make sure we get the right work to the right resource at the right time to deliver an amazing customer experience.

[00:04:27] Yeah.

[00:04:28] Right.

[00:04:28] And then there is the, right, what is the right resource?

[00:04:32] And if that right, right resource is part of somebody's service delivery team, wherever they are, they're working in the world, then that's the right resource.

[00:04:39] If the right resource is an AI component that is understanding what the customer is actually asking you to do, is measuring the cut, the sentiment of how they're engaging with you, is extracting data from the information that the customer has sent to you.

[00:04:55] Yeah.

[00:04:55] Then those are the different types of AI that we're bringing to bear along the way.

[00:04:59] Yeah.

[00:05:00] And, and then some of that becomes conversation as well.

[00:05:04] But we work, we work very much in the, in the B2B space.

[00:05:09] So we are helping people who are providing B2B services.

[00:05:12] Yes.

[00:05:13] Yeah.

[00:05:14] And I find it quite alluring when I'm sitting on a website, I click on the pricing and it's $60, $60 a seat.

[00:05:22] And I'm thinking, okay, okay.

[00:05:23] Wow.

[00:05:24] Wow.

[00:05:24] Would you say some more about the, the, the customers who, you know, the target customers and the customers who are using it?

[00:05:33] Can you pick a, give us a use case or an example of how they're, how they're using this, this platform?

[00:05:39] Sure.

[00:05:40] Sure.

[00:05:40] So I'll give you an example from a, from the corporate services world.

[00:05:45] So corporate services is, is about helping other, other companies manage their global expansion and manage the entities that they bring up in many, many different countries.

[00:05:58] Right.

[00:05:58] Yeah.

[00:06:01] And so this, this big corporate service provider, it's a company called TMF, but you know, this big corporate service provider that, so they're providing entity management and finance and accounting and HR, all of these services.

[00:06:14] Yeah.

[00:06:14] To about 10,000 end clients.

[00:06:16] Wow.

[00:06:17] In 75 countries.

[00:06:19] Right.

[00:06:20] In 12 languages.

[00:06:21] Gosh.

[00:06:22] Uh, and where each of those clients has, you know, there is, you know, there are, there is necessary difference in how you do stuff in Brazil to how you do stuff in Belgium.

[00:06:31] There is necessary difference in how you do stuff between, you know, Microsoft and eBay.

[00:06:38] Yeah.

[00:06:38] Right.

[00:06:38] Yes.

[00:06:39] So within TMF, they are using the innate platform as they call it the beating heart of their.

[00:06:46] Interesting.

[00:06:47] So all of their service delivery teams have got about seven and a half thousand people in service delivery.

[00:06:53] All of that team are using innate every hour of the day to understand what they've got to do for which customer and when.

[00:07:01] And all of the communication with those customers is happening through innate as well.

[00:07:05] Yeah.

[00:07:06] Right.

[00:07:06] Now that's the kind of beating heart bit.

[00:07:08] Okay.

[00:07:09] And then, you know, AI is coming to bear along that service delivery journey.

[00:07:15] And, and we, we break our, our view on AI down into kind of two camps.

[00:07:22] Go on.

[00:07:22] We, we talk about systemic AI, which is the stuff that is about how do we make us as an organization more effective.

[00:07:30] It's the stuff that, that quite often happens, happens in the background in between human touch points.

[00:07:39] Right.

[00:07:39] Yeah.

[00:07:40] So, so TMF are bringing to bear some of that systemic AI.

[00:07:44] So, you know, if we go left to right on a service delivery journey, every service starts with trying to figure out what the customer is asking you to do.

[00:07:54] Yeah.

[00:07:55] That's because until you figure that out, guess what?

[00:07:58] You can't go any further.

[00:07:59] Yeah.

[00:07:59] Yes.

[00:08:00] Start figuring out what the customer is asking you to do.

[00:08:03] Right.

[00:08:03] So they are using, uh, innate AI for categorization of the work that comes into them.

[00:08:10] So an awful lot of the demand and work still comes in by, in the BTB world, lots comes in by email.

[00:08:16] Right.

[00:08:16] Some comes in by voice, but mostly stuff comes in by email.

[00:08:19] So that kind of categorization AI, and they're using sentiment AI from, you know, AI as well to go, yeah, sad face, happy face, neutral face.

[00:08:29] Right.

[00:08:30] Yeah.

[00:08:31] Yeah.

[00:08:31] How is this customer feeling?

[00:08:32] And that's about getting a, to be honest, it doesn't matter what the response, the answer to that on a single email is.

[00:08:38] Yes.

[00:08:38] Or in a single communication.

[00:08:40] That's totally irrelevant.

[00:08:40] What's important is to understand that actually Ewan is one of my important customers.

[00:08:46] Ewan's kind of baseline sentiment is here.

[00:08:51] Yes.

[00:08:52] But right now Ewan is trending down against that or Ewan is trending up against that.

[00:08:58] Right.

[00:08:58] So be aware what's going to help.

[00:09:00] Be aware of that.

[00:09:01] Yeah.

[00:09:01] Why is Ewan getting more grumpy?

[00:09:03] Yes.

[00:09:03] What's causing that?

[00:09:04] Yeah.

[00:09:05] What's, what's, what's, what's driving that?

[00:09:06] Yeah.

[00:09:06] But, but yeah, there is no, there is no absolute sentiment.

[00:09:10] There is no absolute happiness.

[00:09:12] Yeah.

[00:09:12] Because when you're looking at sentiment in 75 countries, in many languages, you see genuine,

[00:09:21] there are, you know, there are stereotypes around this.

[00:09:25] Right.

[00:09:25] Of, of cultures that are, that just have different base points and as individuals, we have different

[00:09:30] baselines.

[00:09:31] So sentiment is all about understanding the baseline for the thing that, and then measuring

[00:09:37] against that.

[00:09:38] Right.

[00:09:39] And then, and then they're coming through using, using data extraction AI.

[00:09:45] So intelligent document processing, which plugs up into the, into the innate platform.

[00:09:50] They're using analyst AI, which is really going, I've written a policy in English.

[00:09:56] Right.

[00:09:57] Every service that you deliver has some kind of policy that says, does this make it, is

[00:10:02] it transactable?

[00:10:03] Yeah.

[00:10:03] Yes.

[00:10:03] I've got a policy for paying an invoice.

[00:10:05] I've got a policy for, can I take this person on as an insurance client?

[00:10:09] Yeah.

[00:10:10] So an analyst AI is going, okay, I've got my policy written in English.

[00:10:15] I've got the data that I've now extracted through, yeah.

[00:10:20] And, and I've got in my customer interaction.

[00:10:22] Is this in line with policy?

[00:10:25] Is it transactable?

[00:10:26] And if it's not transactable, why is it not transactable?

[00:10:29] Right.

[00:10:31] So that's where they're bringing systemic AI to bear, but they're also bringing some conversational

[00:10:37] AI to bear as well.

[00:10:39] Interesting.

[00:10:39] Come to the, come to the, come to the nub of your, which is, which is, and in their world,

[00:10:47] that's very much about if agent effectiveness, effectiveness of their service delivery teams,

[00:10:55] because these are complicated, varied services.

[00:10:59] Yeah.

[00:11:00] And those teams, you know, when you have a situation of, great, I need to make this person a director of a Cayman Islands company,

[00:11:14] but they are a Thai national with a family that are British nationals, and they are a director of this other.

[00:11:23] So you have a lot of variables that come to play, and actually, at that point, as an, as somebody that is going,

[00:11:31] I need to make sure this okay, this is okay, and they are compliant, at that point, they, they need to go,

[00:11:37] okay, what, what are the relevant Cayman Islands?

[00:11:41] What is the data that, that I've got from this, from this particular client?

[00:11:46] And then bring those together and go, and surface that to the agent in a conversational way.

[00:11:52] Right.

[00:11:53] But, but that is all incidental to only putting in front of the agent when you've done those bits of systemic AI heavy lifting first,

[00:12:03] to go, yeah, we know what the customer's asking us to do.

[00:12:06] We've assembled a bunch of the data to do what the customer's asking us to do.

[00:12:11] Now we need to get into the, there's some, there's some complexity here.

[00:12:16] Let's help the agent deal with the complexity.

[00:12:18] Wow.

[00:12:19] I'm curious.

[00:12:20] What's the state before innate AI?

[00:12:24] What does the company look like before they've got your platform?

[00:12:28] So that, that can be very, very variable.

[00:12:33] Yeah.

[00:12:33] So we work a lot with private equity backed service, service organizations.

[00:12:41] Yeah.

[00:12:41] So they tend to be organizations that are on a pretty stellar growth journey.

[00:12:46] Yeah.

[00:12:46] They, they've got some kind of unique or differentiated service proposition that's really helped them grow.

[00:12:52] Right.

[00:12:54] And they have grown fast.

[00:12:57] Now for anybody that's running a business that's grown fast, that comes with, that comes with other things.

[00:13:04] Excel and piles of paper.

[00:13:06] Excel, Endless emails, group mailboxes, piles of paper.

[00:13:10] Yes.

[00:13:11] The crappy systems that someone's made.

[00:13:13] Mild shambles.

[00:13:14] Yeah.

[00:13:14] Right.

[00:13:15] Yes.

[00:13:15] Yeah.

[00:13:16] With, with an awful lot of goodwill from the staff actually being what makes, what, what makes stuff happen.

[00:13:24] So that tends to be a, a not uncommon start point.

[00:13:28] Yes.

[00:13:28] And actually, whether it's a, you know, whether it's a private equity backed service provider or even a, you know, an internal service provider within a, within a big corporate.

[00:13:38] Yes.

[00:13:39] Very often they look a bit like that.

[00:13:41] Right.

[00:13:41] Even, even if they've got, you know, uh, some kind of basic, you know, ticketing system and they've got a cheer or they've got a fresh desk or something like that in.

[00:13:50] They, you know, they, so they, they might be at a point where they can successfully give something a name.

[00:13:56] Right.

[00:13:56] And maybe tell you who, who addressed it with the client, but they can't really get a lot further than that.

[00:14:03] Yeah.

[00:14:03] Gotcha.

[00:14:04] And that's, sorry, please.

[00:14:05] And, and that's, and that's where, that's where the B2B world can be quite different to the B2C world.

[00:14:10] Of course.

[00:14:10] In a B2C world, people do get really quite focused on that.

[00:14:15] No, no, this is going to be beautiful.

[00:14:17] I'm going to make this a very tailored and slick experience with this very specific service.

[00:14:22] B2B world is a bit more shambolic.

[00:14:24] When I was listening to you describe the TMF, uh, example there, it sounds absolutely ideal.

[00:14:32] I can imagine the COO or whoever is in charge of making sure that the business is operating as effectively as possible is, is, is going to look with this.

[00:14:41] This is peak.

[00:14:42] We're doing really good.

[00:14:43] And I, I, I won.

[00:14:45] That's why I was asking you, what does it look like before you come in?

[00:14:48] Right.

[00:14:48] What, who is it typically that's driving that, that, that decision saying we've got to get better.

[00:14:54] We, we need to get something like your services.

[00:14:58] Is that, is it an operating team?

[00:15:01] Is it the CEO?

[00:15:02] Yeah.

[00:15:03] Yeah.

[00:15:03] So, so it's, it's normally the operations leads.

[00:15:07] Yeah.

[00:15:07] In that private equity backed world, it's the PE company as well, because the PE companies is, is, is acting as an almighty cattle prod.

[00:15:16] Yes.

[00:15:17] To go, uh, just remember we're all, we're all on this.

[00:15:21] You're going to double the scale.

[00:15:23] Yes.

[00:15:23] Growth journey.

[00:15:24] Yeah.

[00:15:24] So, and actually for those businesses that are at that, they, they've scaled to that point.

[00:15:29] You know, they're, you know, they're a billion dollar company, but they're still, they still have that somewhat complex, somewhat shambolic core.

[00:15:38] Yeah.

[00:15:40] But one of the absolute levers to, uh, to that further trajectory of growth is then, then really getting their stuff together and going, yeah, we're, we're, yeah.

[00:15:51] Putting in things like Enate to provide that control.

[00:15:56] Yes.

[00:15:57] Then I, I, I wanted to ask, what, what are your favorite use cases or examples that the platform has solved for some clients?

[00:16:09] Give us some, you know, what's, what's top, what, what are you really impressed by?

[00:16:13] So, uh, there, there, there, there are two, there are two things that sort of leaped.

[00:16:18] Actually, no, there are three.

[00:16:19] Go on.

[00:16:19] So, so I love how simple doing sentiment analysis really is now.

[00:16:31] And the fact that most businesses, yeah, we, we dealt with, yeah, we dealt with customer satisfaction by doing NPS surveys and all of that kind of thing for, yeah, for, yeah.

[00:16:47] Most of my career actually.

[00:16:48] Yeah.

[00:16:49] Yeah.

[00:16:49] And, and, and it's great.

[00:16:51] That is at least a simple questionnaire.

[00:16:53] But the problem is, is something that is entirely rear, rearward facing.

[00:16:59] Yes.

[00:16:59] You do it once a year, once every six months and you go, oh, crikey.

[00:17:03] Well, we didn't do all that well then, did we?

[00:17:05] And you make some guesses about what you're going to do better.

[00:17:09] And then you get to six months and you go, did any of them work?

[00:17:13] Hard to tell.

[00:17:13] Yeah.

[00:17:14] Whereas what we're able to do right now is get that, you know, real time kind of upfront action around, oh, this, this client is drifting off.

[00:17:26] and we can see that

[00:17:27] and you can see that as a signal

[00:17:30] as it happens

[00:17:31] so you can act

[00:17:34] way way ahead

[00:17:35] so actually how do you drive

[00:17:37] how do you actually

[00:17:40] drive genuine NPS

[00:17:42] growth and customer satisfaction

[00:17:43] by having real time

[00:17:46] views of sentiment

[00:17:46] so that's one that I love because

[00:17:50] I am massively

[00:17:52] keen on

[00:17:53] how do you deliver the best

[00:17:57] so

[00:17:59] the one that has

[00:18:02] scared me the most

[00:18:03] but also interested me the most

[00:18:05] is

[00:18:07] one that we've done

[00:18:10] with a big hotel chain

[00:18:11] so

[00:18:12] and this is where there really is

[00:18:15] a mixture of conversational AI

[00:18:18] and systemic AI

[00:18:19] in this

[00:18:21] and it's about

[00:18:23] something that is

[00:18:25] at the absolute essence

[00:18:26] of driving value

[00:18:27] so

[00:18:28] we're engaged by the

[00:18:30] finance

[00:18:31] shared services

[00:18:33] bit of this

[00:18:33] of this

[00:18:35] big hotel chain

[00:18:39] and it's very easy

[00:18:40] to get involved in doing

[00:18:42] kind of

[00:18:42] the transactionally

[00:18:43] bits of finance

[00:18:44] shared services

[00:18:45] and global business services

[00:18:46] that's fine

[00:18:47] but actually

[00:18:48] the

[00:18:48] the desire is to go

[00:18:50] great

[00:18:50] yeah that's

[00:18:50] let's take that as

[00:18:51] red

[00:18:53] how can

[00:18:54] how can

[00:18:55] you help us

[00:18:56] get finance

[00:18:58] actually driving

[00:18:58] some of the real

[00:18:59] strategic imperatives

[00:19:00] for the business

[00:19:01] now

[00:19:01] strategic

[00:19:03] you know

[00:19:03] one of the strategic

[00:19:04] imperatives

[00:19:04] for this business

[00:19:05] is

[00:19:06] is higher growth

[00:19:07] and

[00:19:08] how do hotel

[00:19:09] chains grow

[00:19:11] well it's by

[00:19:13] building more hotel

[00:19:14] rooms

[00:19:15] and

[00:19:17] occupying them

[00:19:17] right

[00:19:18] so the first one

[00:19:19] is you know

[00:19:20] you gotta

[00:19:20] you gotta build

[00:19:21] the hotel

[00:19:22] you gotta build

[00:19:23] the hotels

[00:19:23] so that you can

[00:19:25] occupy them

[00:19:25] so the challenge

[00:19:27] there was

[00:19:27] how can you help

[00:19:28] us build more

[00:19:29] hotels

[00:19:32] and

[00:19:32] and this

[00:19:33] comes down

[00:19:33] to

[00:19:36] actually

[00:19:36] it's a

[00:19:37] it's something

[00:19:37] that comes down

[00:19:38] to

[00:19:39] dealing with

[00:19:40] landowners

[00:19:40] right

[00:19:41] as a landowner

[00:19:42] when you want

[00:19:43] to build

[00:19:43] a new hotel

[00:19:45] well

[00:19:46] you've got

[00:19:46] a piece of land

[00:19:47] and you want

[00:19:47] to start

[00:19:48] earning money

[00:19:49] from that

[00:19:49] it's a bit

[00:19:50] like monopoly

[00:19:50] you go

[00:19:51] great

[00:19:51] I'm gonna

[00:19:51] build a hotel

[00:19:52] on my land

[00:19:53] and you go

[00:19:54] out to

[00:19:56] the big

[00:19:56] hotel brands

[00:19:57] and you go

[00:19:57] can I have

[00:19:58] a proposal

[00:19:58] to build

[00:19:59] one of

[00:19:59] your hotels

[00:20:00] on my land

[00:20:00] and you

[00:20:00] right

[00:20:01] yeah

[00:20:03] and at that

[00:20:04] point it's

[00:20:04] an arms race

[00:20:05] because actually

[00:20:06] the person

[00:20:07] who gets

[00:20:07] the proposal

[00:20:08] in front

[00:20:09] of the

[00:20:09] developer

[00:20:10] first

[00:20:12] they

[00:20:12] they are

[00:20:13] the one

[00:20:13] that then

[00:20:13] owns the

[00:20:14] conversation

[00:20:15] yeah

[00:20:15] yeah

[00:20:16] yeah

[00:20:16] the

[00:20:17] first move

[00:20:18] first mover

[00:20:19] in the conversation

[00:20:20] is real advantage

[00:20:21] you've got

[00:20:21] their ear

[00:20:22] you keep

[00:20:23] their ear

[00:20:23] yeah

[00:20:25] so

[00:20:25] right

[00:20:26] how can

[00:20:27] we

[00:20:27] yeah

[00:20:27] how can

[00:20:28] we

[00:20:28] use

[00:20:29] AI

[00:20:30] to help

[00:20:30] you

[00:20:31] get a

[00:20:31] business

[00:20:32] case

[00:20:32] in front

[00:20:33] of a

[00:20:33] property

[00:20:34] developer

[00:20:34] to build

[00:20:35] a hotel

[00:20:35] more quickly

[00:20:36] I don't

[00:20:39] know

[00:20:39] but

[00:20:39] it

[00:20:39] made us

[00:20:40] think

[00:20:40] yes

[00:20:42] and actually

[00:20:42] yeah

[00:20:43] it's a

[00:20:45] complicated

[00:20:45] thing

[00:20:45] but if I

[00:20:46] kind of

[00:20:46] pick one

[00:20:47] line

[00:20:47] apart

[00:20:47] of it

[00:20:48] and go

[00:20:48] look

[00:20:50] you have

[00:20:51] lots

[00:20:51] of

[00:20:51] teams

[00:20:51] that are

[00:20:52] involved

[00:20:52] in

[00:20:53] bringing

[00:20:53] the

[00:20:53] business

[00:20:54] case

[00:20:54] together

[00:20:54] in

[00:20:54] Paris

[00:20:55] but

[00:20:55] let's

[00:20:56] just

[00:20:56] take

[00:20:56] one

[00:20:56] of

[00:20:56] those

[00:20:57] teams

[00:20:57] because

[00:20:57] the

[00:20:57] same

[00:20:57] pattern

[00:20:58] applies

[00:20:58] to

[00:20:58] each

[00:20:58] of

[00:20:58] them

[00:20:59] right

[00:20:59] that

[00:21:48] to

[00:21:49] make

[00:21:49] their

[00:21:50] research

[00:21:50] more

[00:21:51] effective

[00:21:51] and

[00:21:51] faster

[00:21:52] so

[00:21:53] this

[00:21:54] is

[00:21:54] something

[00:21:54] where

[00:21:54] they're

[00:21:55] still

[00:21:55] working

[00:21:55] within

[00:21:55] the

[00:21:56] innate

[00:21:56] platform

[00:21:56] but

[00:21:57] we're

[00:21:57] actually

[00:21:57] surfacing

[00:21:58] through

[00:21:58] innate

[00:22:00] a

[00:22:00] dedicated

[00:22:02] Microsoft

[00:22:02] co-pilot

[00:22:03] that is

[00:22:05] where they

[00:22:06] can go

[00:22:06] okay

[00:22:06] can you

[00:22:07] just

[00:22:07] go

[00:22:07] and

[00:22:07] get

[00:22:08] me

[00:22:09] all

[00:22:09] of

[00:22:10] the

[00:22:10] hotels

[00:22:11] within

[00:22:12] 20

[00:22:12] miles

[00:22:13] of

[00:22:13] this

[00:22:14] point

[00:22:15] and

[00:22:16] can

[00:22:16] you

[00:22:16] go

[00:22:17] and

[00:22:17] find

[00:22:17] out

[00:22:17] their

[00:22:17] average

[00:22:18] rack rate

[00:22:18] so

[00:22:19] it's

[00:22:19] about

[00:22:19] giving

[00:22:19] this

[00:22:20] so

[00:22:20] they're

[00:22:21] having

[00:22:21] this

[00:22:21] conversation

[00:22:22] with

[00:22:23] this

[00:22:23] co-pilot

[00:22:24] that has

[00:22:25] access to

[00:22:25] that

[00:22:25] underlying

[00:22:26] data

[00:22:27] but it's

[00:22:29] fundamentally

[00:22:29] down to

[00:22:30] the human

[00:22:30] then to

[00:22:30] go

[00:22:31] right

[00:22:31] have

[00:22:31] I

[00:22:32] got

[00:22:32] enough

[00:22:32] information

[00:22:33] to

[00:22:34] actually

[00:22:34] be able

[00:22:35] to

[00:22:35] take

[00:22:35] forward

[00:22:36] into

[00:22:36] the

[00:22:36] analysis

[00:22:36] because

[00:22:37] actually

[00:22:38] it might

[00:22:38] come

[00:22:39] back

[00:22:39] with

[00:22:39] going

[00:22:40] no

[00:22:41] there

[00:22:41] are

[00:22:49] right

[00:22:49] yeah

[00:22:49] so

[00:22:50] that

[00:22:51] kind

[00:22:51] of

[00:22:51] conversation

[00:22:51] is

[00:22:52] the

[00:22:52] conversational

[00:22:53] bit

[00:22:53] there

[00:22:53] with

[00:22:54] co-pilot

[00:22:55] surface

[00:22:55] throwing

[00:22:55] name

[00:22:56] and

[00:22:57] then

[00:22:57] once

[00:22:57] they're

[00:22:58] going

[00:22:58] yeah

[00:22:59] we've

[00:22:59] got

[00:22:59] enough

[00:22:59] information

[00:23:00] now

[00:23:01] then

[00:23:02] we

[00:23:02] hand

[00:23:03] that

[00:23:03] on

[00:23:03] to

[00:23:03] the

[00:23:04] systemic

[00:23:05] AI

[00:23:06] to go

[00:23:07] right

[00:23:08] here

[00:23:09] is our

[00:23:09] policy

[00:23:10] for

[00:23:11] deciding

[00:23:11] whether

[00:23:11] we should

[00:23:12] build

[00:23:12] a new

[00:23:13] hotel

[00:23:13] yes

[00:23:14] and

[00:23:14] what

[00:23:15] brand

[00:23:16] of

[00:23:16] hotel

[00:23:16] we

[00:23:16] should

[00:23:17] build

[00:23:17] right

[00:23:17] so

[00:23:18] you

[00:23:18] feed

[00:23:18] that

[00:23:19] data

[00:23:19] in

[00:23:19] that

[00:23:19] the

[00:23:20] analyst

[00:23:20] has

[00:23:20] put

[00:23:21] together

[00:23:21] by

[00:23:22] working

[00:23:22] with

[00:23:22] this

[00:23:23] conversational

[00:23:23] AI

[00:23:23] you

[00:23:24] feed

[00:23:25] it

[00:23:25] into

[00:23:25] the

[00:23:25] AI

[00:23:26] analyst

[00:23:27] here's

[00:23:28] my

[00:23:28] policy

[00:23:28] here's

[00:23:29] my

[00:23:29] data

[00:23:30] write

[00:23:31] me

[00:23:31] the

[00:23:31] recommendation

[00:23:32] section

[00:23:32] for

[00:23:33] the

[00:23:33] business

[00:23:33] case

[00:23:34] document

[00:23:34] that

[00:23:34] explains

[00:23:35] what

[00:23:36] hotel

[00:23:36] should

[00:23:36] build

[00:23:37] why

[00:23:37] we

[00:23:37] should

[00:23:38] build

[00:23:38] it

[00:23:38] whether

[00:23:39] we

[00:23:39] should

[00:23:39] build

[00:23:39] one

[00:23:39] at

[00:23:39] all

[00:23:40] and

[00:23:41] then

[00:23:41] go

[00:23:41] and

[00:23:44] assemble

[00:23:46] it

[00:23:47] into

[00:23:47] the

[00:23:47] final

[00:23:47] business

[00:23:47] case

[00:23:48] document

[00:23:48] and

[00:23:49] the

[00:23:49] fact

[00:23:49] that

[00:23:50] we

[00:23:50] could

[00:23:50] do

[00:23:50] that

[00:23:51] by

[00:23:51] breaking

[00:23:52] it

[00:23:52] down

[00:23:52] into

[00:23:52] those

[00:23:53] sections

[00:23:53] going

[00:23:53] look

[00:23:54] here

[00:23:54] is a

[00:23:54] bit

[00:23:55] that

[00:23:55] must

[00:23:55] be

[00:23:56] human

[00:23:56] centric

[00:23:57] because

[00:23:57] the

[00:23:58] edges

[00:23:58] of

[00:23:58] it

[00:23:59] are

[00:23:59] very

[00:24:00] hard

[00:24:01] to

[00:24:01] define

[00:24:01] therefore

[00:24:02] conversational

[00:24:03] AI

[00:24:03] and

[00:24:04] co-piloting

[00:24:04] is the

[00:24:04] right

[00:24:05] thing

[00:24:05] there

[00:24:05] but

[00:24:06] then

[00:24:06] this

[00:24:07] making

[00:24:08] a

[00:24:13] no

[00:24:14] actually

[00:24:15] works

[00:24:15] really

[00:24:16] well

[00:24:16] yeah

[00:24:16] wow

[00:24:18] so

[00:24:18] that's

[00:24:19] the

[00:24:19] one

[00:24:19] that

[00:24:19] scared

[00:24:20] me

[00:24:20] most

[00:24:20] in

[00:24:20] the

[00:24:21] okay

[00:24:21] that's

[00:24:22] cut

[00:24:22] it

[00:24:22] that's

[00:24:22] going

[00:24:22] across

[00:24:23] a

[00:24:23] whole

[00:24:23] bunch

[00:24:23] of

[00:24:23] areas

[00:24:24] going

[00:24:24] that

[00:24:25] surprised

[00:24:25] me

[00:24:26] when I

[00:24:26] say

[00:24:26] scared

[00:24:26] me

[00:24:27] what

[00:24:27] I

[00:24:27] mean

[00:24:27] surprised

[00:24:27] me

[00:24:28] surprised

[00:24:28] me

[00:24:28] the

[00:24:28] amount

[00:24:29] of

[00:24:31] hard

[00:24:31] to do

[00:24:32] nuanced

[00:24:33] humany

[00:24:33] stuff

[00:24:34] we

[00:24:35] could

[00:24:35] do

[00:24:36] in

[00:24:39] this

[00:24:39] in

[00:24:39] that

[00:24:40] example

[00:24:40] there

[00:24:40] I

[00:24:41] moved

[00:24:42] to

[00:24:42] think

[00:24:42] of

[00:24:42] that

[00:24:42] phrase

[00:24:43] it's

[00:24:43] not

[00:24:43] AI

[00:24:44] won't

[00:24:45] take

[00:24:45] your

[00:24:45] job

[00:24:45] it's

[00:24:46] a

[00:24:46] human

[00:24:46] using

[00:24:47] AI

[00:24:47] that

[00:24:48] will

[00:24:48] take

[00:24:48] your

[00:24:49] job

[00:24:49] this

[00:24:50] is

[00:24:50] a

[00:24:51] really

[00:24:51] interesting

[00:24:52] example

[00:24:53] of

[00:24:54] if

[00:24:54] you

[00:24:54] don't

[00:24:55] have

[00:24:57] all

[00:24:57] of

[00:24:58] that

[00:24:58] capability

[00:24:59] which

[00:25:00] comes

[00:25:00] from

[00:25:01] for

[00:25:01] example

[00:25:01] you're

[00:25:01] based

[00:25:02] in

[00:25:02] or

[00:25:02] rooted

[00:25:03] in

[00:25:03] AI

[00:25:05] you know

[00:25:06] a lot

[00:25:06] of

[00:25:07] businesses

[00:25:07] are

[00:25:07] going

[00:25:08] to

[00:25:08] really

[00:25:08] struggle

[00:25:08] to

[00:25:09] be

[00:25:09] able

[00:25:09] to

[00:25:09] move

[00:25:09] faster

[00:25:10] yeah

[00:25:12] it's

[00:25:12] the

[00:25:13] so

[00:25:14] to

[00:25:15] deploy

[00:25:15] to

[00:25:16] operationalize

[00:25:17] AI

[00:25:17] yeah

[00:25:18] that's

[00:25:19] the word

[00:25:19] that I

[00:25:20] like to

[00:25:21] use

[00:25:21] to

[00:25:22] deploy

[00:25:22] yeah

[00:25:24] there's

[00:25:25] all

[00:25:25] sorts

[00:25:25] of

[00:25:25] nasty

[00:25:26] history

[00:25:26] of

[00:25:26] technology

[00:25:27] deployment

[00:25:28] not being

[00:25:28] used

[00:25:29] so

[00:25:29] operationalize

[00:25:30] means

[00:25:30] actually

[00:25:31] do

[00:25:31] useful

[00:25:31] stuff

[00:25:32] with

[00:25:32] it

[00:25:33] so

[00:25:33] to

[00:25:34] operationalize

[00:25:35] AI

[00:25:35] in

[00:25:35] service

[00:25:36] delivery

[00:25:36] where

[00:25:38] you

[00:25:39] are

[00:25:39] doing

[00:25:39] something

[00:25:40] that

[00:25:40] is

[00:25:41] it

[00:25:42] doesn't

[00:25:42] have

[00:25:43] a lot

[00:25:43] of

[00:25:43] QA

[00:25:44] that

[00:25:44] happens

[00:25:44] through

[00:25:45] the

[00:25:45] process

[00:25:46] yeah

[00:25:48] then

[00:25:48] actually

[00:25:49] you've

[00:25:49] got to

[00:25:49] do

[00:25:49] something

[00:25:50] that

[00:25:50] is

[00:25:50] where

[00:25:51] you

[00:25:51] are

[00:25:52] controlling

[00:25:53] the

[00:25:53] purpose

[00:25:53] of

[00:25:55] that

[00:25:55] AI

[00:25:55] you

[00:25:56] have

[00:25:57] to

[00:25:57] operationalize

[00:25:58] it

[00:25:58] within

[00:25:58] a

[00:25:58] platform

[00:25:59] that

[00:25:59] it

[00:26:00] can

[00:26:00] flip

[00:26:01] to

[00:26:01] human

[00:26:02] without

[00:26:04] any

[00:26:05] issue

[00:26:05] yes

[00:26:05] yeah

[00:26:06] of

[00:26:06] great

[00:26:07] AI

[00:26:07] is not

[00:26:08] confident

[00:26:08] flip it

[00:26:09] across

[00:26:09] yeah

[00:26:10] human

[00:26:11] is

[00:26:11] supported

[00:26:13] by AI

[00:26:13] great

[00:26:14] yeah

[00:26:15] so

[00:26:15] you have

[00:26:16] to work

[00:26:16] within

[00:26:17] some

[00:26:17] kind

[00:26:17] of

[00:26:17] orchestration

[00:26:18] platforms

[00:26:19] yeah

[00:26:19] like

[00:26:19] like

[00:26:20] innate

[00:26:20] yeah

[00:26:22] so

[00:26:22] that

[00:26:22] you've

[00:26:23] got

[00:26:23] that

[00:26:23] control

[00:26:23] layer

[00:26:24] and

[00:26:25] so

[00:26:25] that

[00:26:25] you've

[00:26:25] got

[00:26:26] the

[00:26:26] complete

[00:26:27] audit

[00:26:27] of

[00:26:27] this

[00:26:28] is

[00:26:28] what

[00:26:28] the

[00:26:28] AI

[00:26:28] did

[00:26:29] this

[00:26:29] is

[00:26:29] everything

[00:26:31] coming

[00:26:32] together

[00:26:32] yeah

[00:26:33] how do

[00:26:34] you

[00:26:35] deploy

[00:26:36] this

[00:26:36] what's

[00:26:37] the

[00:26:37] right

[00:26:37] someone

[00:26:39] that's

[00:26:39] listening

[00:26:39] thinking

[00:26:40] we should

[00:26:41] do

[00:26:41] more

[00:26:41] how do

[00:26:42] you

[00:26:42] deploy

[00:26:43] innate

[00:26:44] AI

[00:26:44] what's

[00:26:45] a

[00:26:46] time

[00:26:46] scale

[00:26:46] roughly

[00:26:47] time

[00:26:47] to

[00:26:47] value

[00:26:48] okay

[00:26:49] so

[00:26:51] our

[00:26:51] focus

[00:26:52] is on

[00:26:52] most

[00:26:53] operations

[00:26:53] yeah

[00:26:54] where you

[00:26:55] are trying

[00:26:56] to engage

[00:26:57] things

[00:26:58] it's

[00:26:59] about

[00:26:59] identifying

[00:27:00] teams

[00:27:01] and rolling

[00:27:02] out and

[00:27:03] working

[00:27:03] team by

[00:27:03] team

[00:27:04] across

[00:27:04] an

[00:27:04] organisation

[00:27:05] yeah

[00:27:05] because

[00:27:06] actually

[00:27:07] whose

[00:27:07] work

[00:27:07] are you

[00:27:08] trying

[00:27:08] to

[00:27:08] automate

[00:27:09] and

[00:27:09] improve

[00:27:09] it's

[00:27:10] the

[00:27:10] work

[00:27:10] of

[00:27:14] looking

[00:27:15] to

[00:27:15] do

[00:27:15] something

[00:27:15] that's

[00:27:16] useful

[00:27:16] for

[00:27:16] that

[00:27:16] team

[00:27:18] you

[00:27:18] have

[00:27:19] to

[00:27:19] talk

[00:27:19] to

[00:27:20] them

[00:27:20] holistically

[00:27:20] about

[00:27:20] right

[00:27:21] what's

[00:27:21] everything

[00:27:22] that you

[00:27:22] do

[00:27:22] yes

[00:27:23] let's

[00:27:24] at least

[00:27:24] control

[00:27:24] everything

[00:27:25] that you

[00:27:25] do

[00:27:26] yeah

[00:27:27] to the

[00:27:28] level

[00:27:28] of

[00:27:28] we can

[00:27:29] give it

[00:27:29] a name

[00:27:29] and count

[00:27:30] it

[00:27:30] and understand

[00:27:30] who's

[00:27:31] doing it

[00:27:31] and how

[00:27:32] long

[00:27:32] it's

[00:27:32] taking

[00:27:32] yeah

[00:27:33] and

[00:27:34] that

[00:27:34] so

[00:27:35] that's

[00:27:35] the

[00:27:37] start

[00:27:37] there

[00:27:37] yeah

[00:27:40] and

[00:27:41] then

[00:27:41] you

[00:27:41] have

[00:27:41] a

[00:27:41] data

[00:27:42] set

[00:27:42] coming

[00:27:42] out

[00:27:43] of

[00:27:43] the

[00:27:43] platform

[00:27:43] that

[00:27:44] goes

[00:27:44] great

[00:27:46] here

[00:27:46] is the

[00:27:46] first

[00:27:47] thing

[00:27:47] that you

[00:27:47] should

[00:27:47] then

[00:27:47] automate

[00:27:48] yes

[00:27:48] the

[00:27:49] next

[00:27:49] thing

[00:27:49] you

[00:27:49] should

[00:27:49] then

[00:27:50] automate

[00:27:50] and

[00:27:50] for

[00:27:51] some

[00:27:51] of

[00:27:51] those

[00:27:51] it's

[00:28:04] a

[00:28:15] things

[00:28:15] you

[00:28:16] you

[00:28:19] need

[00:28:23] going

[00:28:23] to

[00:28:24] deliver

[00:28:24] most

[00:28:24] value

[00:28:24] by

[00:28:25] doing

[00:28:25] it

[00:28:25] you're

[00:28:25] going

[00:28:26] to

[00:28:26] save

[00:28:26] most

[00:28:26] time

[00:28:27] or

[00:28:27] create

[00:28:28] the

[00:28:28] biggest

[00:28:28] customer

[00:28:29] impact

[00:28:29] if

[00:28:30] if

[00:28:30] if

[00:28:30] want

[00:28:30] to

[00:28:30] know

[00:28:31] more

[00:28:31] if

[00:28:31] I'm

[00:28:31] keen

[00:28:32] to

[00:28:33] really

[00:28:33] discover

[00:28:34] more

[00:28:34] about

[00:28:34] what

[00:28:34] you're

[00:28:35] doing

[00:28:35] what's

[00:28:35] the

[00:28:35] right

[00:28:35] way

[00:28:35] of

[00:28:36] engaging

[00:28:36] with

[00:28:36] you

[00:28:37] and

[00:28:37] the

[00:28:37] company

[00:28:37] cool

[00:28:38] so

[00:28:39] first

[00:28:40] thing

[00:28:40] I

[00:28:40] say

[00:28:40] is

[00:28:41] head

[00:28:42] to

[00:28:42] our

[00:28:42] website

[00:28:42] inate.io

[00:28:43] yeah

[00:28:44] feel free

[00:28:45] to ping

[00:28:46] me on

[00:28:46] LinkedIn

[00:28:47] you know

[00:28:47] I'm

[00:28:47] sure

[00:28:48] you can

[00:28:49] put

[00:28:49] my

[00:28:49] I'll

[00:28:49] put it

[00:28:50] in

[00:28:50] there

[00:28:50] put

[00:28:50] my

[00:28:51] details

[00:28:51] I'll

[00:28:52] link

[00:28:52] you

[00:28:52] yeah

[00:28:52] or

[00:28:53] engage

[00:28:54] or

[00:28:55] engage

[00:28:55] direct

[00:28:59] is

[00:28:59] providing

[00:29:00] a service

[00:29:01] a B2B

[00:29:02] service

[00:29:02] yeah

[00:29:03] and if

[00:29:04] what you

[00:29:04] are thinking

[00:29:05] of doing

[00:29:06] is

[00:29:06] making

[00:29:07] the

[00:29:07] delivery

[00:29:07] of that

[00:29:08] service

[00:29:08] better

[00:29:09] yeah

[00:29:10] what

[00:29:10] the

[00:29:11] essence

[00:29:11] of your

[00:29:11] thought

[00:29:12] process

[00:29:12] is

[00:29:12] I'm

[00:29:13] delivering

[00:29:14] this

[00:29:14] service

[00:29:14] and I

[00:29:15] want to

[00:29:15] make

[00:29:15] it

[00:29:15] better

[00:29:16] that

[00:29:16] is

[00:29:17] a

[00:29:17] conversation

[00:29:17] that

[00:29:18] we

[00:29:18] should

[00:29:18] have

[00:29:18] yeah

[00:29:20] thank

[00:29:21] you

[00:29:21] so

[00:29:21] much

[00:29:22] for

[00:29:22] taking

[00:29:22] the

[00:29:22] time

[00:29:23] that's

[00:29:23] been

[00:29:24] fantastic

[00:29:25] absolute

[00:29:25] pleasure

[00:29:26] it's been

[00:29:26] great to

[00:29:26] talk to

[00:29:27] you

[00:29:27] thank you