So What? Defining the Agency of the Future

Well, hey everyone, happy Thursday. Welcome to So What the Marketing Analytics and Insights Live Show. I'm Katie. This is Chris. This is John.

All three of us are together. And I was I was just looking at the calendar, and we have now hit that point of the year where at least one of us will be missing from all shows moving towards uh the end of 2026 for mostly honestly for events and uh speaking. So if more show up too, this is it. Enjoy it while it lasts, folks. Just kidding, we'll be back in 2027 when it gets quiet.

Um today we're talking about defining the agency of the future. So this week on the podcast, I talked about how AI is changing the notion of billable hours. And you know, this is not a new conversation, but it keeps coming up because the more work that AI is taking from humans, the more agencies uh who use the billable hour structure are struggling to figure out how, you know, how do I bill for 20 hours when it took five? And it's very unethical to just sort of make things up. Now, the flip side of that is that a billable hour is already kind of made up anyway.

This predates AI. And I think all of us on this live stream have been on both sides of the billable hour. One being responsible for it for your team and making sure we're filling the retainers. The other side is what the heck did I do for a whole hour? Well, I sat through a bunch of meetings and nothing got done, but I guess I have to bill for it and fill up the whole hour.

And so that was sort of the setup of the podcast. On the podcast, what I shared was it's really an opportunity to take the time back that. So if AI does the work in five minutes and you have 55 minutes left, how deep can you get into the insights? What other data can you be looking at? What other meaningful and productive and actionable things can you be thinking about?

And so, Chris, you listened to that and you said, wow, that's super optimistic. But before we get into your viewpoint, for what it's worth, Chris was traveling, so it was just me. So we didn't get the other side of the conversation. John, I want to know what has been your experience with billable hours and what are your thoughts on where what's gonna happen to them? Yeah, for me, it's always been one of those things where, you know, billable hours is kind of just enterprise.

It's like it's a big company, maybe you're buying legal services or super complicated software. And the key has always been that you have the infrastructure to keep track of that. You know, if somebody comes to with you like, okay, here's the 500 hours for last week, you have somebody who's gonna go back and be like, okay, yeah, this smells right, this works. For everybody in the mid-market or small businesses or startups, like they just need to get stuff done. And they may not even have any of the expertise to analyze those bills or know if they're getting ripped off.

So they should be paying by the scope of the project. So that's kind of the general thing. So for most of the world that I've stayed in, yeah, billable hours is just that's you're asking to get ripped off. That's pretty much the punchline. Chris, thoughts?

Brains or boots. When you hire an agency, you're hiring for one of two things. You're hiring for brains that you don't have, right? People with skills that are outside what you used to have, or boots on the ground, right? You you just got so much work to do.

You just need more people in the kitchen doing stuff because there's just not enough of you. And this is a familiar situation. To the topic of the podcast this week, AI provides both. AI provides a ton of boots on the ground in this particularly today's AI, and we're gonna talk about this in a bit. And it provides a ton of brains too, particularly in skills and things that you don't have.

You know, we've talked many times in the show about tools like Suno, for example, that creates above average AI generated music. Is it gonna win a Grammy? Nope. Uh, but is it better than you know, your your cat just like clawing on things? Yes.

Uh, or your two-year-old like you know, with a spoon in some cans. Um AI will do a credible capable job at most of the tasks. Now, when I listened to the podcast this week, I I in fact, Katie was saying, I said that's a really optimistic perspective. And uh, and I said, Okay, I would love to to talk about this on the live stream, but first, as John and I talked about on earlier today in an episode of Marketing Over Coffee, uh, it's nice if you have an opinion, but if you don't bring any data, it's not really worth anything. Um, so I said, okay, well, what can we go and provide for the the brains, the boots, and the bills.

In terms of the brains, uh, one of the my favorite sites out there is a site called Artificial Analysis. And this is a website of uh this is a company that independently benchmarks AI models. They take you know various prompts or agentic workflows and they try to make AI tools do things and then they measure how well it does those things. One of the things they came up with was a capabilities index. So they have their mass index, but then they have a capabilities index with six fields finance and accounting, healthcare and medical, legal, economics, engineering, and strategy and ops.

Strategy and ops is sort of like general business and stuff like that. Because one of the things people like to talk about with AI is oh, well, you know, it can write press releases, but I, the account director on this account, I'm a I'm the real strategist. I know the strategy. Uh that you know, no AI can replace that. Mm-hmm.

Yeah. Um in the strategy and ops index, we can see, of course, you know, all the different models, what they do, but they tell you what the benchmarks are that make that up. So I said, this is a great proxy for the brains that AI can bring. And if we could figure out like over time, how smart AI models are getting at stuff like Strategy and Ops, we can calibrate against that. That makes sense so far.

Mm-hmm. Second, um, I used PR agencies, A, because you and I worked at 1K for five years. So we know the world pretty well, but we also know some of the folks in that world, and we can speak to how they work. One of the agencies that uh in that world we know of is called Golden Partners. This is an MA firm.

So they uh they helped broker uh our old agency sale to their their new corporate masters. Um and Rick Gould, uh, who's a very nice guy, I've talked to him a bunch of times, has these benchmarking reports that they publish every year. And the the benchmark report for this year said here's what agencies are billing at per hour by roll. Here's um what their PLs look like. Again, this is PR firms specifically, so this is not applicable everything.

But at a fundamental level, the bill, these are what the bill rates in 2025 were for PR agencies. So the the CEO, someone like UK average bills bills out an average of 482 an hour, and you know, the list goes up down from there. So this is the boots. How much do the boots cost? Makes sense.

The third thing we wanted to get was how much of a role could AI play? And for this, we use the TRIPS framework by Trust Insights. And I took uh just as a representative sample, I took, I went to Allison and Partners, which is a global PR firm, and I grabbed all their job descriptions, you know, the for all the different levers. By the way, I would just like to point out if we look at this account coordinator, look at these responsibilities. Participate in team and client calls and take notes and action items, develop the first draft of written content.

This is they're hiring for this now. Modern flag client industry media coverage, conduct entry level media relations with instructions from an AE, research speaking opportunities, events, and awards, produce monthly reports, learn be good at media tracking, conduct new business research. Um there isn't a single responsibility here that a machine can't do. Like not a single one. This position itself does not need to exist.

Other than one person to push buttons and say, agent go, agent go. Which is, you know, and I think that's the disheartening thing for a lot of people is, you know, this is the reality. And, you know, I agree. I look at this and I'm like, there's nothing on here that a pretty well prompted large language model couldn't do for you. And I think that was my whole point on the podcast was like, no, I understand there's a lot that the large language model does.

So what does the human have the opportunity to bring to the table? And that's not listed here. And that's a huge missed opportunity from this agency. Mm-hmm. For this level, there isn't for anything for a human to do.

Like literally, this entire position does not need to exist because this is the lowest level position in the organization. And other than, you know, promote and uphold our core values, I mean, there's nothing here that a machine can't do better, faster, and a heck of a lot cheaper. Right. No, I understand that. But typically, and this is, you know, predating AI, we didn't put in, we in job descriptions, we typically put in the very tactical, like button pushing things, like, you know, must be proficient in Microsoft Word and Excel, you know, must produce eight reports a week or whatever it is.

We never get into the responsibilities that are more of those critical thinking. Like we say, you know, must be good at problem solving. Well, what does that mean? You know, and so it's a I and you know, this particular agency aside, it's a huge missed opportunity for anyone posting a job description to really outline like what is that expectation of you being able to use your brain? Mm-hmm.

Yep. So if we marry these data sources, the trips analysis that I did from Allison's roles, plus Rick Gould's great research about the PR industry, plus artificial analysis, what we end up with is a lovely visualization that looks like this. Here is essentially late uh late 2025 and what AI was capable of. And as I drag this slider, you'll see it go from assistive, meaning it can, you know, AI, we would chat with it, um, to agentic where there's workflows to fully autonomous where the machine just does things end to end. And we have the percentage of the billable hour based on trips that goes away as AI capabilities increase.

PR agencies, and again, this is limited to PR for for this particular visualization. PR agencies have a target net margin of approximately I I want to say 15%, uh no, 17%. 17 to 21% is where they try to be, especially and they try to be on the higher side because at that point a holding company is they're worth coming in and buying them. I remember back in the day when we worked at our old agency, the goal was to buy hook or by crook, get to 21% net margin so that we that the owner could get the maximum dollars during the sale, which they did mostly on the back of our team. Not salty.

But here we are today. So let's watch what happens over time. So this is late 2025, right? Uh Q4, and we start to see a divergence as we get into early 2026. The three lines are hourly billing.

Like what uh tasks uh are fall under like an hourly billing uh agreement, what tasks really fall under retainer agreement, and then what tasks are value-based billing. What you talked about in the podcast, Katie, about the different ways to bill um things. As we get to uh the the spring of 2026, look what happens here is retainer based billing goes to the zero profit line, right? Because to your exactly your point, Katie, when a client comes to an agency that says, What are you what are you billing me for? Like you're I'm spending all this money per month.

What am I getting? We've heard that many times on uh from from you know over the years, like what exactly are I paying you for? Um and even hourly billing. Now that this is uh as we move into agentic AI, agentic AI is where um these advanced workflows, multi-step workflows where humans signs off. So this is like claude code, clawed cowork, and you and this corresponds well to um where things were in the middle of this year, back in you know, May, June, when you know, Katie, all of really 2026, you have spent all in on the clawed ecosystem, and you've done some amazing stuff with it.

Trying to um quick plug. If you're going to be at Makeon in Cleveland the second week of October, I am doing a Claude for Business workshop. I will also plug if you want your own Claude workshop for your team, then you can reach out to uh that guy down there in the blue shirt. Hello, hello. Um, but you know, to that point, you're absolutely right.

And, you know, I'm trying to be mindful of not replacing the thinking that I do, but what was the like really what it is is what was the analysis that I wasn't getting to because of my workload and being one person that I can now do, I still have to think about it. I still have to have the inputs. You know, I can have Claude build me a presentation deck for an event, but they're not paying us to have me use Claude to build a presentation deck. They're paying for my expertise that goes into the slides and into the talk. And that's not something that you know I feel comfortable having a large language model replace.

And so my expertise in my brain are still very much happening, but the amount of work I'm able to produce has increased literally exponentially at more than 10x, because a lot of the work that I do includes data analysis that I just didn't have the time or the skill set for. Yep. And we can see at this point here, mid year, the the roles that are getting affected are basically that from that management roll down. 17% of billable hours gone, 20% of available hours gone, 23% of billable hours gone. As we start to move later into this year, you start to see those roles turn yellow.

Like you're now talking 30, 40% of their billable hours vanishing. And as we get to today, to today, autonomous AI, end to end-to-end, we're talking, you know, 71% of billable hours gone. And even at the top, at the present CEO level, 12% of billable hours gone. The only thing that gets kept is the value-based billing. Anything is value-based billing where you are paying for something that no one else can deliver.

If you are paying for boots, gone. And if you even if you're paying for brains, a good chunk of that is gone. And we've seen this with this idea of the digital twin. And so there is enough, not that I would encourage this because it's actually not very ethical, but there's enough publicly available information from certain experts in fields where you could put together a decent proximity digital twin in your large language model for someone based on what they write about, what they speak about, their opinions on things. And you could squint your eyes and say, Oh, now I know how Chris Penn thinks.

I have a digital twin of Chris Penn. Why do I need to hire Chris Penn? Now again, it's not going to be as good as the real human version because there's so much nuance missing from what you publicly put out versus what you keep behind the closed doors of your own IP. But that's sort of where I see some of this falling apart as well. Is people are going to say, well, why do I need to hire a fractional CMO when I can just build one?

Mm-hmm. Exactly. Now we get into the contrast. In Gould's world, um, Rick's in Rick published a uh an opinion piece uh how AI is reshaping PR from valuations, and Rick's conclusion there was strategy is fine, no one's gonna take away strategy. Yet we know from artificial analysis strategy is not fine.

And so in our little tool here, when you do back and forth, you can see that in that disagreement, strategy, which forms a lot of these uh role parts, yeah, it eats into more billable hours. AI starts taking away more billable hours. And then when we look at the specific task list of all the tasks by role, as I drag the slider across over time, we see the things that get held vanishing, things that are going, and then ultimately we see things that are just gone, gone, gone, right? These are all the tasks that are completely gone. You know, log media items and issues into the tracking system, write call and action notes, review utilization, available hour role requests, all of that gone.

And this is available on the Trust Insights website. Uh, if you're not a member of our analytics for marketers uh Slack group, go to trusted sites.ai/slash analytics for marketers, uh, and we'll put the URL in there after this live stream because the other thing you can do is using the TRIPS framework, you can put in, you know, whatever, like a task, and then you yourself can say, like, how much time does this task take me? Uh it takes me a lot of time. Uh, how important is the task? Yeah, not particularly important.

Uh, do I have sufficient examples? Yep, I sure do. Um, you know, how repetitive is the task? Oh, it's very repetitive. How painful is this guy?

Oh, it sucks. And you can see that by doing that, and I have the slider all the way to the right, that task has been eaten by AI somewhere. Um, and so it is incumbent upon you to figure out well, if AI, if if this tool says AI can do it, maybe I should see if I can have my AI help me with it. Now, this opens up the conversation to a lot of companies. Okay, so there's a lot of discourse.

There always there's always a lot of discourse. Not now, forever. There's always been a lot of discourse about the use of AI. And what I'm seeing a lot of on social media is leadership wants everything in the red. They want you know AI taking all of these things, they want to pay less money to humans, and the humans are pushing back saying, no, I'm not gonna let AI take this thing.

I am better at this thing than AI. Let me prove it to you. Um, you know, I can build a slide deck faster and more accurately than AI can, because AI doesn't know what I know, and so I feel like there's like this is a good representation of what's possible, but I don't feel like it's reality for a lot of companies, and whether it's because there's pushback from the employees or because they just don't have the capabilities to give AI all of these things. This isn't actually what's happening. What we're seeing is more of a hybrid of AI is doing some things, humans are still doing things, but there's no process on either side.

So billable hours are still a nightmare. One of the things, if we step back and think about it, the work. I do, right? What an agency provides is a neck to choke and a person to blame when things go badly, right? It's uh agencies are an accountability shield for a lot of people in corporate.

And so it doesn't really matter in a lot of ways whether the agency does anything better than a half ass job, as long as they're not going to get you fired and you can blame them for when things go badly. And so that accountability sinkhold, a AI cannot be that. So if you are paying an agency to cover your assets, that is why you would have that you'll still pay an agency for that. You you will not stop paying billable hours if you have someone else to blame. But that's not an AI problem.

Like a lot of the issues with billable hours, almost all the issues with billable hours predate AI. Like this is, I think it's in here somewhere. Where is it down here? New tech doesn't solve old problems. I saw that earlier.

I was like, I gotta use it. But it's true. Like we talk about how AI is not solving problems, it's amplifying things that are wrong within your organization if there's a lack of process, if there's a lack of agreement, if there's a lack of measurable outcomes. And in this case with billable hours, if there is no clear set, this is how we do billable hours, this is what is billable, then you don't have a good proxy to say, well, now AI is doing this, so that's you know, the one for one swap. Like it's still a mess.

In the podcast, I used, you know, legal as the industry that kind of sets the stage for billable hours because that's how they operate. There is no value-based thing that you can buy generally. Um if you're engaging a lawyer, you are likely engaging them hourly for their expertise, for their ability to know stuff that you don't. And you know, a lot of law firms, not all law firms, but some law firms are now using AI to do some of that research, to do, you know, uh some of the work that a paralegal might have done or a junior associate might have done in terms of preparing everything so that the senior lead on the account can say, yes, this is how we're going to proceed, and then go argue it in court. You're not necessarily going to get AI to replace a human to go to court and argue.

People love to argue. Why would they want to replace that with a machine? But you're going to get a machine to replace a lot of the research that goes into building that argument. One of the things that the folks at meter, um, M E T Rorg said earlier this year was that your average firm, your average agency, so we've talked about defining the agency of the future is really an inverse pyramid. So the standard pyramid model is you have a few senior people and a whole bunch of junior people, and you bill by the hour because you're billing for brains and boots.

Uh, boots are the easiest to bill for, you know, with one rate of 279 an hour. And the more people work, the more hours they spend, the more revenue you make. Um, the inverse pyramid in a value-based building says you have more people at the top, you have fewer no people at the bottom because machines do that stuff. And that, like you're saying, Katie, that judgment, that expertise is what you're paying for. So if you think about it, in a lot of ways, that's really how trust insights is shaped, right?

We have a bunch of senior people, we have one uh junior person, and we have a bunch of machines, and we don't and we're never going to have that layer of a hundred associates all churning away, you know, copy pasting things. That's that's never gonna happen. Uh it's going to be machines, but that's what the agency of the future likely looks like. Because the other thing besides accountability shield, uh, that uh humans are particularly good at um, humans are good at well, well, the law supports human created works as having copyright. Um, that's sort of a tangential thing, but humans are really good at ideation.

Uh, machines are good at new to you, but not net new. Um, and so if you are sitting there saying, like, how can I come up with some creative ideas for my next campaign? You're going to get stuff that has been done in some fashion before. Machines are even at in most situations, kind of going back to your earlier point, Katie, in most situations, people are not going to have the sophistication or the systems to force a machine to truly ideate something new. And so there is still value there in having a human ideate, then the machine can help you refine, find blind spots and stuff like that.

But that supports that inverse pyramid structure of a few big brains and then a bunch of machines. What do you think, John? Yeah, it does make sense. It's just amazing how much of that our model as it was, was just in the crank, you know, it was just doing stuff that agents can make completely go away. So it's one of those areas where it's like uh if you've been digging dishes with a shovel, I got bad news for you.

You know, the this uh bulldozer is gonna ruin your entire career. So I guess I mean, but that brings up the question that every agency is struggling with is so what are we do instead? So if we were previously employing, you know, uh four account coordinators to do research and you know, drafting things, and that was the part of the billable thing, and now one single large language model is doing that, you know, what do we do? How do we account for all of that revenue loss? Well, and I'm not saying we have to like solve it here, but that's really where that's why we talk about it, because that's where that's really what the question is.

It's not can AI do it, it's what do I do about all the revenue that I'm losing because I can no longer bill for this work. Do I just not use AI so that I can keep the billable people? That's one solution. But then you have the other side of that conversation of the expectation is how much faster and the volume of things that companies they don't really care whether or not you're using AI anymore, they just want it, they know it's possible. So don't build them for work you're not doing and produce more.

Like you can't reconcile that you can it's the what is it, Chris? You the good fast cheap. Like I feel like that has now become like a dodecagon or something with all the different factors. The fundamental premise of value-based building is that your deliverables are priced by their economic impact. So if you are good at measurement, if you're good at analytics, if you are good at understanding what your work means to a corporate to a customer, then you can price it accordingly.

If I give you this thing and you use this thing to 2x your profits, right? And you go from being a million dollar company to a $2 million company, then I could say, you know what? I'm gonna charge you know 5% of that as the bill for this thing because you you paid in 5% to get 100% more revenue. You get you have you know 20x ROI, you're happy, you're gonna get promoted, you look great. The challenge for a lot of firms is they don't know what the economic impact of their work is.

This was especially true in public relations, right? This has always been true in public relations. New tech doesn't solve all problems. Um what economic value does a public relations firm drive? If you're paying Allison or Edelman or Weber Shamrick or whoever 50 grand a month, 100 grand a month, can you say we paid it for every dollar we paid in, we got a dollar 25 out?

Can you say that? If you can, then whatever they charge you, as long as that math holds, you're gonna be happy paying it, right? If you pay if you hire Trust Insights and you pay us a dollar and you we give you work and you get two dollars of value out of work, you'll put a dollar in the machine as fast as you can, right? How can I give you more dollars because I then more dollars come back to me? If you can't prove that, you're going out of business.

I mean, that that's the harsh truth. You're going out of business. If you can't prove the economic value of what you're doing, no one's gonna hire you because you're dead weight. So how, and again, I'm I'm hitting you with all the hard questions. How does an agency start to think about that?

Like, we don't have to give them a formula, but what are the things that an agency who is still using a billable hour model, but also the expectations of AI are on the table. How do they start to think about that economic impact? Like, what are the things that they should be looking at to be able to say to their client, here's why we can justify you paying us $50,000 a month, which that still makes me cringe a little bit because like that's a lot of money. I mean, our team earned that back in the day. I know one client.

I know, which was amazing. Um, but like how do like, you know, let's say I'm the CEO of a company. Let's just play pretend for a second. I'm a CEO of a company. Shaq is a basketball player.

All right, here we go. Well, I mean, I don't have the energy for big imagination today. So here's here's where we go. Um, you know, but I guess the the question is like, you know, I'm a leader of a PR agency, which I'm not, but let's say I was, and suddenly I'm seeing our retainers are dropping by half, by thirds, by you know, more than we're really comfortable with, because the conversation is we can't say we can still justify you paying the monthly retainer, and they're like, oh, but we know you're using AI, so why am I gonna pay that? How do I start to think about how to justify that economic impact?

Like, what should I be looking at? What should I be talking to my team about, and what should I be saying to my clients? And this is all just like we're just kind of coming up with it right now, like there's no magic formula, just to be clear. We actually did this back in the day. Um at the old shop.

Um because we have in fact, I remember exactly who was involved. We were called in on the carpet as an agency uh by this one client, and the VP on that account called me in a panic and said, You need to help me prove that I'm worth what they're paying us and and save this massive account. What we did was we said, okay, great. Let's get a couple of years worth of the client's data, data like Google Analytics data, et cetera. Uh, this is back in the days when that data was reliable.

Um, and whatever else we could get our hands on. We said, okay, what is the economic value of like in this case, a website visitor, um, following it all the way through the funnel and stuff like that, amortizing, you know, the our our KPI maps that we that we've since taught. And then said, okay, doing uplift modeling. We know when this team started working with you, and we know what things were like before then, and we know all the things that would have happened regard with without hiring us. What is the statistical difference between the treatment period, aka when you hired us, uh, and the control period when we didn't work for you?

What is that delta in those measures? Because we knew that a website visitor to this company is worth a dollar 17, right? So I can measure that as an outcome based on what this team did to say this is what this is worth. And in that particular case, I um toothless. Oh, I was yeah, anyway.

Um in that particular case, we're able to we're able to show with reliable math from the client's own analytics. Yes, what you are paying this team for is generating positive returns because this traffic goes to here, and then it's up to your sales and marketing team to convert that traffic into paying customers. We're doing our job of getting people to the door. Then you have to get, you know, once they come inside, you got to do your job and not like punch them in the face. Um and so that's how you would apply it to today, right?

If I can say, if I if I could if I work with a client and I say, here is what you you are trying to do, you want more of this. People to the website, market qualified leads, whatever. And here's when you start working with XYZ public relations firm. Here's the delta in that measure that we agree upon, and we agree upon that based on your own data. This is the value that XYZ delivers to you.

And the first thing I tell the CEO of XYZ is you stop value, you stop hourly billing immediately. You go to value-based building, and you say, here's how we calculate our value. We calculate our value based on the economic value we create for your company. We will get people to the door. It is then your responsibility to get them in the door and to sell them something.

But we will get people to the door. We will get the right people to the door. I remember having this exact conversation with our good friend Ginny Dietrich, um, who, if you don't know, is the founder and owner of SpinSucks. And she has talked to me about she's had to do that uh justification many times over for well, what am I paying for? And to your point, that's exactly what it is is she's been able to demonstrate and she builds this into her engagements where it's just a line in the monthly report of and it's not labeled as like, and here's what you're paying for, but it's like, and here's everything we brought you.

And it's she's able to, when that question comes up of say, like, yeah, here's all the qualified leads we brought you. It's on your sales and marketing teams to close them. But like, look what we did for you. Here's where you started. Here is your baseline before us, and here's what we did since you've engaged with us.

And that, you know, as you're describing it, I'm like, oh, I do remember doing that. Like, that seems like something that any agency should be including in their monthly, whether or not it's asked for, proactively create it. Like, and here's what we've been able to do for you since engaging, you know, with our agency. And, you know, I'm making a mental note for us to make sure that we are including that in everything that we're doing. Because it, you know, I understand it's a natural question for the person who's paying to say, What am I paying for?

Especially if there's not a lot of transparency, if it's not blatantly obvious that, you know, since hiring Trust Insights, revenue has gone up exponentially. That may not be what you hired us to do, but it's a very black and white, like, well, did revenue go up or down? That's not why we're here. Mm-hmm. In our case, and you know, there are the management consulting firms and stuff often have to do this.

It's what what tangible things do you have? Like, oh, I have a box of these things that I didn't have before, and I understand the value of these things. Like earlier today, um, I was doing some work for a client, and I I pulled some data from something I had seen out there in the world, like, ah, I can adapt that. I grabbed that data, I pulled it, I created a handout to the client, and they're like, Wow, I've never seen this before. And so when the client stakeholder comes back and says, Well, what have you done?

What did you do for this this month? I said, I proactively made this thing for you that no one else has ever made that tells you exactly what's going on with your AI visibility that is real data. Um, and this this is something that you can't get anywhere else because it didn't exist until literally 11 a.m. today. And so that may not necessarily have a dollar figure attached to it, but if the stakeholder says, you know, what things do I have that I did not previously have?

We can incredibly say, you have never had this before. No one has this before, has had this before. Now you have it and you can use it. Now, if you don't use it, that's kind of your fault. Um, we can certainly provide some enablement materials to tell you how to use it, but you still have to do the work.

But again, that goes back to the value-based billing. I didn't count how much time it took me, right? And frankly, nobody cares. Um, I count if I give you this thing, does it give you an advantage that you don't you previously did not have? And I think that goes back to again, a lot of this is foundational, the KPI map.

And so, what KPI specifically were you able to influence? So, if you take the very top of that KPI map, is likely always going to be revenue or sales or whatever it is, like something tied to money. And then you start to break down well, what are the things that influence revenue? Which KPI was Trust Insights able to influence, therefore, there's a trickle effect because as you bring it down, you know, to the bottom of that KPI map, there's more things that start to influence, you know, each number and they roll up. But if you can influence even one small part of that, there is going to be a trickle effect, and you should be able to track that.

And so it really comes back to can you measure the work that you're doing? Which is not an AI thing, that is just a general best practice for any agency. Yep. Agencies need to get a handle on this today, like right now, today, because the pace at which AI models are improving is going to get much, much faster very, very, very soon. This was a paper that came out from Shanghai Chan Chaotong University last week.

Um, this is 13 different AI labs in China. It's called the last AI built by humans, called Toward Genuine Recursive Self-Improvement. This is a methodology that the Chinese AI labs are using to take massive leaps forward in agentic capabilities where the tools can truly and autonomously improve themselves at any given task. So not just get smarter generally, but you it's given a task like write a press release, for example. And the system is capable of not only building its own tooling, but building a self-improvement system around that tooling to get better and better results without being told by a human.

This matters because if we go back to this, you know, the artificial analysis, the these AI capabilities, you're gonna see these charts go up and to the right for all these different areas. So brains and boots are less going to be less and less of a shield for your revenue than they are now. And as we saw in the visualization, that's already going away. So you have to get a handle on value-based billing and outcome-based billing, which is really what we should call it outcome-based billing, as quickly as possible. Because if you don't, these tools are going to eat your lunch.

If you can go back to that academic paper for a second, I think, as a side note, I think this is the first time I've personally seen an academic paper include a too long don't read statement. Like when did that happen? That's here. That's the executive summary. The executive executive summary.

Yeah, you're not showing it on screen, but yeah, the uh that's wild to me because I mean, I worked, like I said, I worked in academia for a long time. That was never a thing that was included. The abstract was meant to be good enough, but now it includes this too long. Anyway, that's sort of an aside that took me by surprise. Um but I agree.

I think that agencies who are still operating on the billable hour need to shift their focus, need to shift their thinking to that outcome-based um billing, because it's only gonna get harder, and you're only gonna get more scrutinized and you're gonna get more pushback. And if you can't say this is how I impacted this particular KPI on your map that leads up to your revenue, you're gonna have a hard time justifying that $50,000 a month uh retainer. And that's gonna be a hard hit when you lose it. And I would just like to I was just gonna say this is a drag race, right? It's like there's multiple firms out there.

The firm that gets there first can cut prices and basically pull the chain out from anybody else. I would just like to point out we have been saying this. I have this blog post up from October 2023. Stop being an hourly knowledge worker business. Like you need we we have been warning you for three years now.

Get away from hourly billing. Just don't listen. Right? Which means that things we're warning you about now in three in 2029, we'd be like, we told you back in 2026 that recursive self-improvement was a thing and you didn't listen to us. And now Skynet runs everything, and it's just like Wally.

Where's my drink? Yeah, uh, there we go. So yeah, the TLDR of this entire episode, stop hourly billing immediately. But with the caveat that you can do other things without overhauling your entire agency. Exactly.

So Katie, how optimistic do you feel now? You know, here's I still feel optimistic. I feel like it's just a matter of, I always say a little bit better planning up front. Um can't be, you know, it can't be a live stream without the five Ps. Your purpose, people, process, platform, performance.

In this instance, you're thinking about as you're bringing it on an agency, it's your job as the payee uh to think about like why am I bringing on an agency? What are they meant to actually have an impact on? And then as the agency, your job is to proactively say, these are the metrics that I know we are going to have a positive impact on. Bring it back to the numbers, bring it back to those outcomes, and you'll have to worry less about the billable hour. Because to your point, Chris, if someone's getting a dollar twenty-five for every dollar they spend, they're gonna spend more dollars to get that quarter.

Yep, exactly. They'll do it all day, every day. That is the win, but you've got it, you've got to be good at measurement and proving your worth. I mean, you tried. You can't kill my optimism, Chris.

I know. I'll keep trying. Keep trying. Uh that's gonna do it for this week, folks. Thanks for tuning in.

We will see you all on the next one. Thanks for watching today. Be sure to subscribe to our show wherever you're watching it. For more resources and to learn more, check out the Trust Insights Podcast at TrustInsights.ai slash TI podcast. And a weekly email newsletter at trustinsights.ai slash newsletter.

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