The AI Reinvention of Go-To-Market: Who Owns the Intelligence? with Jason Ryan

[00:00:00] Jason: We've got demand gen and we've got the meta algorithm and the algorithm can do better than our team of marketers can. It's proven, you know, this algorithm can get faster and cheaper and I think that begs a big question about what does happen when you start to look at possibly, you could say it's a black box, but what you get the trust and the confidence in.
It's that that loop and those hypothesis and that constant learning and testing is efficient and it works.
[00:00:25] Mike: My name's Mike Lander and you are listening to Higgle, the B2B Sales Club podcast, where we bring you actionable insights about sales, RFPs, negotiations, and difficult procurement discussions from sales leaders.
Ground leaders and procurement leaders, please subscribe to get updates when new episodes are released.
Jason, thanks ever so much for joining me on Higgle the B2B Sales Group podcast.
[00:00:52] Jason: Delighted to be here, Mike. Thanks for inviting me.
[00:00:54] Mike: So how long we'd known each other now? On and off for quite a while, I think
[00:00:57] Jason: on and off for quite a while. Yeah. We've kind of been collaborators at a distance
[00:01:00] Mike: Yes. For
[00:01:00] Jason: quite some time, haven't we?
Exactly. But I think these last few months where we've um, it's really enjoyed the conversations with you, so Yeah. It's good to be able to share some of this with other people.
[00:01:09] Mike: Exactly. And we've definitely jumped down the kind of AI rabbit hole, me and Jason over several topics, which has been great fun.
But through that, I think has emerged this. There was a paper that Jason wrote that I contributed to and also this podcast. So without further ado, Jason. Do you wanna explain to people who you are, what you do, and your favorite song and why?
[00:01:28] Jason: Sure. I'm Jason Ryan. I am a long-term, long-time strategist, um, digital marketer and transformation person.
Um, I'm currently working for Magnus Magnus Consulting. So what I do is I've kind of taken all of that learnings I've had through, you know, multimedia and internet and capability building, and I, I guess it was three, maybe four years ago now, maybe three, three and a half years ago. Just the prospects of AI was gonna change everything.
So I've kind of doubled down on that. Mm-hmm. Tripled down on that. All my work now is taking all of that knowledge that exists in organizations and building systems and orchestration and ways of working. So that's really what I'm focused on.
[00:02:07] Mike: Brilliant.
[00:02:07] Jason: Regarding the song, I knew you're gonna ask me this.
Haha. So, and I'm glad I knew up front because it's always very, very. Cool. But I've chosen two actually, Mike, I've taken a bit of a liberty, and the reason I've done this is that it's a bit of a yin and yang situation. The first one is life during wartime by talking heads.
[00:02:22] Mike: Ah.
[00:02:23] Jason: And the reason for that is that it's kind of talking about the, um, the uncertainty and the kind of, I won't say panic, but the, what's kind of going on at the moment.
There's a lot of, um, some of the words is this ain't no party. This ain't no disco, this ain't no falling around. It's a kind of a fight. Yeah. Thing, it's very danceable, but in the context of what we're talking about, there's a line, I've changed my hairstyle so many times now. I dunno what it'll look like.
And it's, it's everyone's kinda reinventing themselves. So
[00:02:51] Mike: they're,
[00:02:51] Jason: there's that, but I wanted brilliant to encounter it with, it's what A Wonderful World by Louis Armstrong.
[00:02:57] Mike: Oh, a beautiful song.
[00:02:58] Jason: And there's a beautiful song. And it's the perfect opposite. And I was, I didn't know this, but it was actually written during the height of Vietnam and it's very much a purposeful decision to look at what's around you and slow down.
So that's my reason to have two. It's that yes, we are in this kind of crazy frantic kind of world sometimes, but don't forget to slow down and look at the flowers. It's my message.
[00:03:19] Mike: That's a very, very good point. I try and do that not every day, but most days, particularly around when our son gets home from school.
It's just to take some time just to have a chat and see how he is. And then obviously later on, try not to work in the evening.
[00:03:33] Jason: Yeah.
[00:03:33] Mike: After dinner. So you can just like spend some time together. Yeah. Because those times won't be there forever.
[00:03:37] Jason: You know, I think what comes from that song is it's, you know, it's a purposeful act, isn't it?
You have to actually make time for it and be, be deliberate.
[00:03:44] Mike: You do,
[00:03:45] Jason: because you could so easily. Everything is so fast and so accessible, you can quite easily just keep going. So,
[00:03:50] Mike: exactly.
[00:03:51] Jason: Yeah.
[00:03:51] Mike: And in fact, I think one thing that I said when I first opened the call today, anyone out there that's playing with Codex or with Claude Code or any of those things, it's very easy to jump down a rabbit hole and get lost for hours and hours and hours.
And I find it interesting 'cause I'm an engineer by training, but you can get, yeah, you get lost in the detail, which can be a problem. Anyway.
[00:04:13] Jason: Yeah.
[00:04:14] Mike: Let's open the show with, just talk about GTM in general. Jason. Lots of people talk about GTMI think often it's poorly understood. I'm not looking for an academic definition, but just give us a broad understanding about what you mean by GTM.
[00:04:28] Jason: Yeah, sure. I understand that because I mean, I've worked for years and years in B2C with organizations and GTM didn't really come up and I think it's since been working with Magnus and more in a B2B environment that it's a much more prevalent, um, term. What I would say about it is that go to market is, I would say that in the context of pre ai, it's very much a, a strategic pursuit.
It's very much around, well, actually what's the outside in view, you know, what's the commercial view? Who's the buying unit? Who's the ideal customer profile. You do the firmographic research, you kind of get your target audience, and then it's looking at what you've got internally and it's very much bringing those together in a value proposition and the go to market strategy.
And I think therein lies the interesting bit.
[00:05:13] Mike: Mm.
[00:05:13] Jason: Because the word strategy tends to mean, or has tended to mean it's a strategic output. It's a document. It's a deliverable. Yes. It's a kind of, it's a one-off thing.
[00:05:21] Mike: Yep.
[00:05:22] Jason: And then a year later, if it's not working, you'll, you'll do it again or refresh it.
[00:05:26] Mike: Exactly.
[00:05:26] Jason: So, do you know what I mean? It's the one, I do the one and done thing and I think go to market, and I think you all get onto this, but it, it's going through a little bit of a re-imagining, I would say, as most things are.
[00:05:35] Mike: It is exactly brilliant. And in fact, on that note, I'm just building a methodology for kind of my agency reset research that I did and documented.
Um, what I'm doing now is rather than in the old days, I'd have written a framework in PowerPoint and I'd have sent it to a client. And I'm not, I'm now building an always on kind of always updated methodology, which gets published as a webpage that gets stored privately behind my little kind of private, uh, firewall and dataset because it will adapt and change.
So I've built into it a learning loop. So I think we'll talk about all this as we go through the kind of questions. So let's start with the bigger question, which is from campaigns to systems. What happens when marketing becomes an always on loop? Just talk about that.
[00:06:19] Jason: Yeah. I think what, let's just talk about this in kind of broad brush strokes.
You know, this is, I've taken a sort of a slightly binary position to land the point, but I think when you think back to marketing, generally there's a brief, the brief comes out because. Someone in the organization realizes something isn't quite right or something could be better, or something's failing.
So this is usually, I think, born out of the obvious sense that something's broken, we need to fix it. And very often that's a campaign or it's a piece of work which has a finite, it has an endpoint.
[00:06:50] Mike: Yeah.
[00:06:50] Jason: And I don't think necessarily in the understanding this is gonna fix it, but it's very much a fixed term piece.
And I think a lot of that is based on, there's a problem, let's fix it. It's gonna take six months. We've got the budget, let's move on to the next problem.
[00:07:04] Mike: Exactly. So you kind of, there's a start point, there's a problem, there's a start point, there's a process, there's an end point. Hopefully there's an outcome.
[00:07:11] Jason: Absolutely. And even for those always on and those retainers, you know what tends to happen, I think in a lot of organizations is the campaigns. The campaigns aren't particularly well measured for a number of reasons. It's the data, it's the complexity, it's the pace at which you need to get the next piece of work out and haven't got time to properly stop.
And I've been working in this field for a long, long time and very few people have got the measurement nailed. Absolutely. And, and the feedback loop. And it's been a, kind of suppose it's been a, an ongoing issue for most organizations I've worked with,
[00:07:41] Mike: especially as it's cross channel. Yeah. I mean, I am the furthest thing you could get to from a GA four expert, but whenever I talk to people that are.
There's always, there seems to be a lot of complexity around the reporting and how things don't line up and how you've got to do manual work to adjust things and it just struck me as being, yeah,
[00:08:01] Jason: well
[00:08:01] Mike: agree.
[00:08:02] Jason: Like a reporting ecosystem, isn't it? You've got various agencies and they're all trying to make the best of their, the best narrative to prove their worth.
[00:08:09] Mike: Yeah,
[00:08:09] Jason: so you've got a lot of making the best of the data. Plus inside the organization, it needs to be assimilated for a number of different audiences. And those marketers need to be showing that they've made the best of things. So you know, it's going through a number of filters and it's often the challenge of really getting a true improvement loop in.
And what I mean by that is not just, oh look, this number's gone up or down. But I think what AI's enabled us to do now is moving to a auto generating, if you like, the hypotheses. So we go through the loop, the system can see the target, it can see where we're at, and it can look at that and say, well actually that's off.
What could the possible reasons for that be?
[00:08:44] Mike: Exactly? Let me build a hypothesis.
[00:08:46] Jason: Let's build a hypothesis.
[00:08:47] Mike: So let's rerun something, let's do some split testing. And all of this could be automated. I was listening to, I've forgotten who it was now a couple weeks ago, about where the media platforms are going.
[00:08:58] Jason: Mm.
[00:08:58] Mike: If you think about, and again, I'm not an expert in this, but just thinking logically, if you think about Google as a kind of media platform and go, well, where they're gonna get to is probably saying, you've got an e-com site and you want to get an extra hundred K sales and you've got a budget of 30 K, give us the third 30 K, and we will hit the a hundred K for you.
Because just through a continuous. Always on set of marketing campaigns because they have infinite inventory.
[00:09:25] Jason: Of
[00:09:25] Mike: course. Yeah. So they can afford to go. Is that where you're kind of going with this?
[00:09:27] Jason: It's the really good example. I mean that's, I guess if you take it from that perspective, then I was, you know, as you know, it was a can last week and I think one session somebody said, well, you know, we've got demand gen and we've got the meta algorithm.
Algorithm gonna do better than our team of marketers can. It's proven, you know, this algorithm can do faster and cheaper.
[00:09:47] Mike: Wow.
[00:09:47] Jason: And I think that begs a big question about what does happen exactly. When you start to look at, possibly, you could say it's a black box, but what you get the trust and the confidence in is that that loop and those hypothesis and that constant learning and testing is efficient and it works.
[00:10:02] Mike: Exactly,
[00:10:02] Jason: and I think if you come to the other end of this spectrum, you know when I've been coding and I've been using the tools I've been, it's become to the point now that I'm gonna build in this kind of evaluation hypothesis how to be better and ask the coding to go around that loop five times. And I'm gonna get a better result.
I might spend more tokens and it'll be a longer question, you know, and there's two ends of the spectrum, somewhere in the middle. There's a lot of opportunity, I think, for doing this within organizations, within putting these feedback loops in.
[00:10:30] Mike: Definitely
[00:10:31] Jason: hooking the data up. And it really does beg that question, doesn't it?
Around if go to market is not a milestone, it's a continual loop.
[00:10:39] Mike: Yeah.
[00:10:39] Jason: Um, if marketing becomes. Not a milestone, and it becomes a continual loop
[00:10:43] Mike: because it's always on.
[00:10:44] Jason: Yeah. You know, we've been hearing a lot about loops. You know, I'm certainly hearing a lot about loops at the moment. And
[00:10:50] Mike: yeah,
[00:10:50] Jason: it's very
[00:10:50] Mike: much, and the Senate might say that loops are, you know, a way for the foundation models to make more money because it'll run something five times rather than once in order to hit a better output or outcome for you.
But I think there is a lot in recursive loops aiming towards a improved outcome where it gets better and better.
[00:11:09] Jason: Yeah. You know, it's been part of machine learning. For a long time, but it's, yeah,
[00:11:12] Mike: exactly.
[00:11:13] Jason: But it's all, it's not been available to the general non-technical marketers. And so having this kind of capability now to, and it's a mindset shift.
I mean, I think a, a lot of it is that it's moving from a, this is how we budget, you know, and this is the finite, this is finite length and budget for this piece of work almost. You know, it could be moving back into this, a retained model or an always on model. I think this is a conversation that possibly kicked us off down the line of, well actually how are procurement teams and how are people buying this?
Right,
[00:11:43] Mike: exactly. And so let's move on to that kind of question, which is the buyer shift. So how clients and procurement will buy AI enabled GTM. So given the setup you've just given us, which is about it, will increasingly be an always on loop, then what does that mean in terms of how procurement teams in particular are gonna buy AI enabled go-to market systems?
Because it's complex as we found out.
[00:12:07] Jason: Yeah, it is complex. You know, I think one of the things that we, well, we discussed this in the paper and one of the things that you raised actually, which I thought was really interesting, was what business model is hidden in the contract.
[00:12:19] Mike: Yeah.
[00:12:19] Jason: And we said that, you know, activity and rate card sales expertise, and that's really good if.
If you're doing exploratory work or you need consultancy work, and the question is not answered, it's a piece of research work. We've got the deliverable, you know, as a finished asset, and that's clear because it's finite. But who's to say that it's not out of date by the time it's delivered in this, in this rapidly changing, fast changing world, there's consumption.
You know, this scalable usage, which is kind of have it when you need it. There's access and subscription, which buys you, they're always on capability. You know, the skin in the game thing. There's the shared. The shared out there is. And then we've got a much more complicated system now because it's not about hours or deliverables or outputs or outcomes.
There's intangibles in there now because as we were saying with the media layer, if all of that starts to become quicker and faster. And the hours are faster than what you are actually buying. Yeah. What's more, and a lot of this is intangible, you know, it's, it's taste, it's judgment,
[00:13:12] Mike: and there's also institutional knowledge, Jason.
[00:13:15] Jason: Yeah.
[00:13:15] Mike: The more I thought about it, following on from the paper that we were working on, who owns the institutional knowledge that's inside that intelligence layer within the wider system? Obviously the client ultimately owns it. But can the agency use that knowledge on its next program with other clients if it's anonymized?
Lots of questions to be answered around that. I think
[00:13:35] Jason: this is the big question. I think it depends on, I mean, I would say at the moment, and our minds change all the time on this as we sort of, yes. New things. But I think picking up on your point around demand gen and the algorithms, yeah, there doesn't seem to be a lot of resistance if to just trust that data with a provider if it's gonna give you the right outcome.
And there's kind of a, a spectrum along here. Between, and a lot of organizations are asking themselves, what should we be sharing? What should we be putting into ai? And to the finer point, it's okay, are you gonna be using my data? Do you own my data? Am I what do you retain? And what do we retain in this?
[00:14:10] Mike: Yeah, if we part ways.
Then
[00:14:11] Mike: who owns what
[00:14:12] Jason: Exactly. '
[00:14:13] Mike: cause it has to be really clear from the outset. Yeah. I think I was saying when we wrote that paper was, I always think as a procurement person, what's the offboarding route before I even sign the contract? How do I get you outta my organization? And that's not because I don't want to work with you, that's because I have to manage risk.
And if we end up in a position whereby we cannot off board because we are entirely dependent upon you. That's just a bad place commercially to be.
[00:14:35] Jason: And I found that really, really helpful. We were going in and speaking to potential clients about this. You know what? What have we got here? We're consultants, you know, so we can do consultancy, but we're also looking at an always on operating system.
[00:14:50] Mike: Exactly.
[00:14:51] Jason: We're also bringing signals into this, but, so we're gonna do some reporting. Oh, and actually we'll do some integration work as well, because the system could be talking to this system,
[00:14:59] Mike: oh, we'll, we'll build some agents for you as well, because we've got some agents that we can build. Yeah, they're now in anthropics, um, managed service agents.
So we can actually stick an agent up there and it's multi-tenanted and soc two compliant and you could use those agents if you want.
[00:15:13] Jason: Yeah.
[00:15:13] Mike: It all starts to sound quite attractive to, it's gonna solve all my problems. And then I go, Hmm. And when you leave me, can I run my business?
[00:15:22] Jason: I think this is why this procurement conversation is so valuable because we have been on opposite sides of the fence for a long time, you know?
Yeah. You've been in procurement. I've been in agents.
[00:15:32] Mike: Exactly. Exactly.
[00:15:34] Jason: But quite often, you know, agencies don't get a chance to speak to procurement people. They're the people that come in the edge and try and beat you down on price and so, you know.
[00:15:41] Mike: Yeah.
[00:15:42] Jason: It's not a productive conversation often, is it?
[00:15:44] Mike: Exactly. Correct.
[00:15:45] Jason: Having this insight. From yourself, Mike, around, well, actually, what's the exit strategy? And it really helps. I think it really helps agencies, consultancies that are moving into, because everyone's moving into a platform. Everyone's using AI to some degree.
[00:15:58] Mike: Yeah.
[00:15:58] Jason: These are the big questions that do need to be answered as we kind of move into this.
[00:16:02] Mike: They are, and I think also. If you look at, as we're on that kind of topic, if you look at where the consulting market's going, I always think the big consulting market's always an interesting market to look at. 'cause it's knowledge workers ultimately. And if you'd look at the, well, how much of their fee income will be based upon performance?
True performance related pay. They're now saying, I don't know, between 20 and 40% maybe of their total fees across the entire organization could be performance related. We've not really seen that before. There's always been performance related pay. I, I used to work on gain share models all the time, but it's becoming increasingly the norm is that.
Anyone that has a knowledge worker type services business that supplies organizations, in order for them to get better outcomes, well you need to put part of your fees at risk, and that's gonna become an increasingly common model.
[00:16:51] Jason: Yeah, absolutely. Well, I think another subject in Cannes, which was interesting to be there and sort of here where conversations were coming up a number of times and sort of taking that as a bit of a signal.
Hearing, if you like, the disconnect sometimes between media agencies and CMOs,
[00:17:06] Mike: right?
[00:17:07] Jason: Because often there's those KPIs aren't always aligned.
[00:17:09] Mike: Correct.
[00:17:10] Jason: If it's about growth, then what are the levers of growth? And then you've got these other measures. You know, I'm gonna talk old media measures, but reach, impressions, engagement, all those sorts of things, which are rather seen intermediate measure.
And I think a lot of the closing that gap between what does this mean in terms of growth has been people looking at the data and looking at the, and going back to our conversation about reporting and the complexity. As humans, we have to go back and look at that data and those dashboards and make sense of it.
And what these systems are now enable us to do is they're making sense of that for us and they're pushing us into this is your next move and these are the decisions you need to make. You know, and that's kind of what the Google algorithms are doing. But it's pushing us further into clear decision making, um, really understanding growth leader's in a way that we've not always been able to close that gap so much in the past.
[00:17:57] Mike: Exactly. Which leads us onto the kind of final question really, which is around who wins the new marketing macro structure? 'cause we've now got platforms. That claim to be your marketing operating system that will deliver outcomes for you. We've got, hold cos that are moving into the, I think I thought publicist move when they bought that massive data company was very interesting.
They'll own it end to end. Then you've got, you know, really niche specialists or you've got kind of agent operators. So who do you think, and there won't be a one size fits all clearly, but what's your view of who wins that new marketing macro structure?
[00:18:31] Jason: It's a really good question, and you can kind of see it going in a number of different ways.
One of the things that I was again struck by from the, the conversations last week again was this kind of collapsing, if you like, of of the doing layer into algorithms.
[00:18:45] Mike: Yes. Now for the listeners, so we're now at. 2nd of July, you've literally just come back from Cannes.
[00:18:51] Jason: Yeah, exactly. Yeah.
[00:18:52] Mike: Genuinely was there a definite recognition that the engine room, the execution layer, is genuinely now, you know, a lot of it is being AI enabled, or it's AI first.
[00:19:03] Jason: Yes, absolutely. I think there's a real shift from this is coming to, this is happening, I would say.
[00:19:09] Mike: So a definite recognition that this is no longer a theory by a bunch of people who are at the edge of ai. Yeah. This is genuinely front and center. CMOs are talking about it, brands are using it and agencies are starting to feel the effect of it.
[00:19:23] Jason: Yeah, a hundred percent. And I think if you, you know, one trajectory if you like is if it becomes. More accessible, cheaper, faster.
[00:19:29] Mike: Yep. More consistent, reliable.
[00:19:31] Jason: Yeah, exactly. It actually gives that capability and that access to a lot of brands and a lot of organizations have not been able to afford that in the past.
[00:19:39] Mike: Exactly. Right. Particularly the mid-market.
[00:19:41] Jason: Exactly. So it's a mid-market thing and I think when you start to get smaller players having access to that level. Of analysis. It's a threat to the holding companies. It's a threat to the ones where that have got that, that advantage, if you like. There's that side of it.
Also, I think you've got this, this thing around it was a creative festival, but I also think that that expert layer is kind of been hollowed out a little bit. You know, we're starting to move agents into these positions. You know, even starting to think about it in terms of the experts, we used to think about like, you know, your gp for example, it becomes an admin to a, an algorithmic system.
So this isn't, you know, this is a, a cultural or a societal shift.
[00:20:22] Mike: It is, and we're not saying, Jason, to be clear, we're not saying tomorrow morning, it's the end of creatives. But we're saying that if there's a triangle of creative talent, half of the triangle may well be done by agen. The other half will still need human taste and judgment at the moment.
[00:20:39] Jason: Yeah, absolutely. But I think this is the point. I mean, I think you can sort of see how, how that execution layer. It's starting to, it's starting to become, well, I suppose it's trending towards zero, if you like. You can see how that would work, but at the same time, the creative is the conversion. The creative is what sets you apart.
[00:20:55] Mike: Yes,
[00:20:55] Jason: and look at it from another perspective. The more creative, the better ideas, the more you have got your finger on the pulse. You've got creators that are representing your audience, your communities. I think it's a massive opportunity for creative agencies. To be honest. So where the media agencies might be, might be up against it, particularly if those creative agencies have access to those planning algorithms that they haven't necessarily done before.
'cause there's been this separation. I had a man thought there that was, imagine if all of the media planning and buying was available as a plugin,
[00:21:27] Mike: right?
[00:21:28] Jason: No, and that's not, obviously not gonna happen for a long time. No,
[00:21:30] Mike: but it's a forcing function.
[00:21:32] Jason: But does, yeah, as a forcing function. What does that mean?
If you are an amazing creative agency and you had that capability as well. I think there's a lot that's gonna be decided by pushing the creative. I think in a CWE there are more ideas and more ways to do creative work, you know, and there's more AI slop out there and there's more opportunities to do that.
[00:21:51] Mike: Yeah.
[00:21:51] Jason: Who's going to differentiate when it comes to
[00:21:53] Mike: exactly
[00:21:53] Jason: work and creative thought? '
[00:21:54] Mike: cause the creative is what, and we know that the Kantar evidence was clear about, if you look at excellent creative versus average creative, you get a much higher response rate. You get a much higher retention rate, you get better commercial outcomes.
So we know that great creative is highly valuable, and I think, as you say, Jason, if you flip the coin and go, what would happen if it was ubiquitous access? Always on to running ads. The reporting platforms were completely accurate, and you could have synthetic humans that you could run ads past and see what the response rates was like.
Well, that would enhance creativity, wouldn't it? It would show that the really good creatives would shine because they'd be able to test and learn in a safe sandpit. Then say to clients, we know this is gonna deliver X, Y, and Z 'cause we've tested it.
[00:22:42] Jason: Yeah, I, I agree with you. I think, but there's a difference I think between optimization and original creative thought.
[00:22:47] Mike: There is absolutely, origination versus optimization are very different.
[00:22:51] Jason: You can see how you could start with an idea and you can optimize your way. To better placements and better messaging and all sort of, those sorts of things. And I guess that's gonna be a large part of it because you know when you can make anything.
So the only question worth asking is, you know, is it any good? And how do we know if it's any good?
[00:23:08] Mike: Exactly. Precisely. So bringing it all together, if you were, and I think look at it, I don't mind which side to look at it from a brand side or from a an agency side. It doesn't matter, uh, to me. But bringing this kind of conversation together, what do you think it means practically for people that are trying to build and grow their businesses?
[00:23:25] Jason: I think what it means practically, it's recognizing that as I think, I think I said before, that strategy is not a milestone, it's a continual process. It's a continual process of optimization. And I think the operating system, we've used the operating system in the buyer's guide.
[00:23:39] Mike: Yep.
[00:23:40] Jason: And I think it's starting to think about things as an operating system.
You know, what exactly, what are the inputs and what's the quality of the input and what's the quality of the data? I mean, what the quality of the data. It's such a fundamental thing.
[00:23:52] Mike: It is. And do I trust what it's saying?
[00:23:54] Jason: Yeah, absolutely. And I was with one client recently that did, I, I won't say who they were.
[00:23:59] Mike: No,
[00:23:59] Jason: but they sell a product and I think at one point in the conversation they said, so we're becoming a data organization that just happens to sell this product. I think that is where it will go. So three things. What are the inputs? What are the signals? How fresh are they? How reliable are they? How much do we trust them?
[00:24:15] Mike: Yep.
[00:24:15] Jason: Then we've got this middle piece, which is, it's a data structure and it's a set of processes and connected systems.
[00:24:22] Mike: It is correct.
[00:24:23] Jason: And how effective and how, and how efficient is that system of being able to create the right outputs that reach the right audiences and do what they're supposed to do.
And at that end, it's the judgment layer, isn't it? It's the,
[00:24:34] Mike: it is.
[00:24:34] Jason: Is this good enough? Is this better?
[00:24:36] Mike: Yeah.
[00:24:36] Jason: And I think that's a. Is it
[00:24:38] Mike: tasteful
[00:24:38] Jason: way of thinking about it, but it feels like a different type of machine that we're, than we're used to thinking about.
[00:24:43] Mike: And Jason, I think, I dunno if you saw last week, the World Economic Forum report.
[00:24:47] Jason: Absolutely.
[00:24:47] Mike: Really, really good. I thought a really well put together piece of thinking around, there are five core components to AI first organizations. And anyone listening, I would highly recommend just go to the World Economic Forum site, look at the AI Operating Model Research paper and just look at that.
What you've just described, I think is exactly that. It's encapsulated in that paper.
[00:25:10] Jason: Yeah. Feels to me that this is, as I say, it's a mindset shift and it's a re-imagining, you know, we,
[00:25:15] Mike: yeah.
[00:25:15] Jason: Everybody that's been involved in AI has been saying this for, you know, since they came across it. It'll help us do things.
Quicker. It's gonna help us do things differently and then it's gonna help us think differently. And I think we're, we're in that help us think differently stage now.
[00:25:30] Mike: Exactly right.
[00:25:30] Jason: We've done the optimizations, we've we're putting it to work for ourselves personally. It's now the re-imagining stage. And I think this is, I wouldn't say it's, yeah, it's urgent.
I think it's urgent because it, it's, it is urgent. It feels like a race. I go back to my life, it's
[00:25:43] Mike: urgent
[00:25:43] Jason: war time. It feels like,
[00:25:45] Mike: yeah,
[00:25:45] Jason: we're in that race and there is a bit of urgency and there's obviously a bit of, um, uncertainty around this.
[00:25:51] Mike: Yeah,
[00:25:51] Jason: but exciting times.
[00:25:53] Mike: Jason, where can people find out more about you?
[00:25:54] Jason: People can find out more about me on LinkedIn, Jason Ryan, or through Magnus Consulting.
[00:26:00] Mike: Brilliant. Jason, it's been a real pleasure having you on the show. Thank you ever so much for joining me.
[00:26:04] Jason: Thanks for inviting me, Mike. It's been great.
[00:26:06] Mike: Thanks for listening to Higgle the B2B Sales Club podcast series with your host, Mike Lander.
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