Mark Stouse: Why Causal AI Beats Correlation | Ep 1269

Summary

---

Podcast Summary: The Digital Executive

Episode: Mark Stouse: Why Causal AI Beats Correlation | Ep 1269
Date: June 19, 2026
Host: Brian, Coruzant Technologies
Guest: Mark Stouse, Chairman and CEO of Proof Causal AI

---

Episode Overview

This episode centers on Mark Stouse’s perspective as an industry innovator and CEO of Proof Causal AI, exploring why causal AI offers a superior approach to business measurement and decision-making compared to traditional correlation-based analytics. The discussion draws on Stouse’s extensive corporate experience, recent shifts in market volatility, and the growing need for accountability in go-to-market (GTM) investments, finishing with the impact of agentic AI on B2B buying and evolving strategies for demand generation.

---

Key Discussion Points & Insights

The Problem: Ineffective Go-to-Market Spend

• Internal Observations ([03:16])
  • Mark emphasizes a “perennial problem” for GTM teams in major businesses: their inability to prove value and calibrate investments effectively.
  • “More than 52, 53% of [GTM spend] was ineffective. And for startups and scaleups it's a lot worse. It's like about 72% ineffective.” (Mark Stouse, [04:10])
  • Increasing marketplace volatility means “past is not prologue”—traditional approaches are not reliable anymore.
  • Proof originally targeted marketers, but finance teams became the primary users, as they were hungry for fact-based accountability.

Why Correlation Falls Short

• Core Difference ([07:21])
  • Mark delineates causal AI (focused on causal inference) vs. the limits of correlation:
    • “Correlation is essentially, hey, we saw that when it's sunny outside we sell more ice cream. But clearly the sun didn't cause the sale…” ([07:34])
    • Correlation can’t capture the intricate web of causes and time lags in real business environments.
  • Market Examples:
    • Correlational models are breaking down under economic volatility—e.g., comments from the Chairman of the Federal Reserve, and the insurance sector’s inability to price risk using outdated systems ([09:38]).
    • “Correlative systems are breaking right now all over the place because of that extraordinary volatility and high velocity change.” (Mark Stouse, [08:55]))

Causal AI: Trust, Certification, and Financial Rigor

• MASB Certification and FASB Compliance ([12:10])
  • FASB creates the U.S. accounting rules; MASB guides marketing accountability.
  • Being compliant gives finance and boards confidence that marketing investments are finally treated “with the same rigor as any other financial asset.”
  • “One of the wonderful things about causal analysis, causal AI, is that everybody benefits. Well, you could reasonably say how. Well, it shows you what not to do more of because it's not working. And it also shows you where you're absolutely killing it…” ([13:36])
• Implication for Decision-Makers:
  • Helps identify not only what’s ineffective, but also where to double down until diminishing returns set in.
  • Rising costs of customer acquisition (CAC) are underreported and growing, while deal size and velocity are shrinking.
  • “If you don't spend it the right way the first time, the opportunity cost later gets pretty severe.” (Mark Stouse, [14:50]))

The B2B Buyer Revolution: AI Agents on the Demand Side

• AI Empowering Buyers ([17:49])
  • Mark discusses how agentic AI is flipping the traditional sales process:
    • “Customers are actively deploying capabilities using AI to filter and otherwise defeat the outbound marketing and sales activity of vendors.”
    • Legislation in the EU and U.S. (e.g., California) reflects widespread frustration with intrusive marketing tactics.
    • Massive reduction in visible sales/marketing emails and texts—“after they implement those kind of tools, they're seeing really staggering reductions in email traffic…” ([19:39])
  • “Funnel is now a filter”—buyers use AI agents to pre-qualify or entirely block vendor outreach, assembling their own shortlists or conducting purchasing through bots.

---

Notable Quotes & Memorable Moments

• On the need for causal AI:
  • “You can't look at how you've always done it and just assume that it's still going to work.” (Mark Stouse, [03:41])
• Illustrating correlation’s limits:
  • “Correlation is essentially, hey, we saw that when it's sunny outside we sell more ice cream. But clearly the sun didn't cause the sale…” (Mark Stouse, [07:34])
• Why FASB/MASB compliance matters:
  • “When they see that we are FASB compliant, they kind of relax because they understand that we understand their situation.” (Mark Stouse, [12:41])
  • "One of the wonderful things about causal analysis, causal AI, is that everybody benefits…" (Mark Stouse, [13:36])
• On buyer empowerment:
  • “For the first time in go to market history, customers are actively deploying capabilities using AI to filter and otherwise defeat outbound marketing...” (Mark Stouse, [17:55])
  • “The funnel actually is now a filter.” (Mark Stouse, [20:45])
• On opportunity cost and CAC:
  • “If you don't spend it the right way the first time, the opportunity cost later gets pretty severe.” (Mark Stouse, [14:50])

---

Important Segment Timestamps

• [03:16] Origins of Proof Causal AI and market inefficiency
• [07:21] Why correlation can't deliver in today’s volatile business landscape
• [12:10] The significance of FASB/MASB in legitimizing marketing analytics
• [14:50] The underreported costs and business risk of ineffective spend
• [17:49] Agentic AI shifting B2B demand generation; “the funnel is now a filter”
• [20:45] Practical examples of AI-based buyer filtration

---

Tone & Style

The conversation is candid, data-driven, and sprinkled with real-world analogies. Mark’s language is accessible but authoritative, arming listeners with both high-level frameworks and specific, actionable insights relevant to tech executives, marketers, and finance leaders facing rapid industry change.

---

Takeaways

• Causal AI offers a much-needed upgrade from correlative analytics, especially in volatile markets where old assumptions break down.
• Rigorous standards (MASB/FASB) provide crucial credibility and trust, making data-driven marketing and GTM strategies viable for boardrooms and CFOs.
• The future of B2B selling is being reshaped by AI on the buyer side—fewer messages are being seen, buyers have more control, and old approaches to demand generation are rapidly losing effectiveness.

---

Transcript

[Sponsor/Ad Reader]

This episode is brought to you by Google Chrome. You think you know a browser, but Gemini and Chrome? That's new. It can help you with practically anything on the web, like restoring a vintage motorcycle from a 50 page restoration block. Or finally break down that long article you've had open for weeks. Gemini and Chrome is here for it, ready to make anything online make sense. There's no place like Chrome. Check responses set up required compatibility and availability. Various 18 study and play come together

on a Windows 11 PC and for a limited time, college students get the

[Mark Stuss]

best of both worlds.

[Sponsor/Ad Reader]

Get the unreal college deal everything you need to study and play with select Windows 11 PCs. Eligible students get a year of Microsoft 365 Premium and a year of Xbox Game Pass ultimate with a custom color Xbox wireless controller. Learn [e-mail] studentoffer while supplies last ends June 30. Terms at aka mscollegepc.

[Brian (Interviewer/Host)]

Welcome to Coruscant Technologies, home of the Digital Executive Podcast. Do you work in emerging tech? Working on something innovative? Maybe an entrepreneur? Apply to be a guest at www.corazant.com brand welcome to the Digital Executive. Today's guest is Mark Stuss. Mark Stuss is the Chairman and CEO of Proof Causal AI. He leads a team with the only AI native, MASB certified and FASB compliant Causal AI platform that enables Go to Market teams to plan, predict, prove and pivot their investments in real time. With more than 25 years of experience in marketing, communications, customer success and commercial strategy, Mark helps transform business performance with data driven insights and agile decision making. Mark Stuss also leverages his expertise in Go to market analytics and economics to co chair the modern Go to Market Organizational structure at the Marketing Accountability Standards Board and to serve as a member of the Brand Valuation Work Group at the association of National Advertisers. In addition, Mark has been recognized as an innovator and leader in the analytics field. With multiple awards, patents and publications. He is committed to advancing the practice and standards of go to market accountability and optimization across industries and markets. Well, good afternoon Mark. Welcome to the show.

[Mark Stuss]

Hey, glad to be here.

[Brian (Interviewer/Host)]

Absolutely my friend. I appreciate it. And you're hailing out of the Phoenix area. I'll say Paradise Valley, but trippy. I didn't know. It seems like Phoenix was built around it, but I didn't know that. And I'm in Kansas City, so we're just a little bit of apart. I just appreciate you making the time today and traversing the time zone. So Mark, if I could, I'm going to jump into Your first question. You spent 25 years inside major corporations like HP, BMC Software and Honeywell Aerospace as one of the first B2B Chief Marketing Officers to actually use causal analytics to measure and calibrate go to market spend globally before founding Proof Casual Proof Causal AI. What did you see from the inside that convinced you that this was a problem worth building a company around?

[Mark Stuss]

Well, I mean anybody who has been in the go to market professions for any length of time knows all too well that the business is still not persuaded that the value is clearly established, that they know what to invest in and what not to invest in. They don't know how to calibrate their investments at all. And that has only been exacerbated by the volatility and high velocity change in the marketplace, which essentially means that past is not prologue. You can't look at how you've always done it and just assume that it's still going to work. And we see that. I mean every year we publish an annual report on effectiveness in different parts of companies, but one of them is go to market effectiveness. And we just keep on seeing it sink and sink and sink. And it crossed over the 50% mark in 2025. So that meant that was in the Fortune 500 or so Fortune 1000 actually it was over 50% of go to market spend. So that's sales, marketing, product, customer success, and depending on the company, other things that touch the customer. That's more than 52, 53% of it was ineffective. And for startups and scale ups it's a lot worse. It's like about 72% ineffective. So it's a huge issue that everybody talks about all the time. And so even nine years ago when we started Proof, it was a big, really big deal. And so that's the basis of filling that need, is the basis of starting company. And I would say this, the only pivot that we've really made in that is that we work primarily with finance teams today, looking at the objective performance of different parts of the company. That would include go to market, but not even remotely exclusively that. And we started out selling to marketers and that that was a hard sell because once you really figure out what causal inference and causal AI really represent, you realize that you're looking at something that's going to really show you the facts of the, of what's going on and that can be a little scary. And so the only people at that time that weren't, well, they, they not only weren't terrified, they were eager to find out more were finance leaders and that is only proven to be more and more true.

[Brian (Interviewer/Host)]

Thank you. Really appreciate that. And obviously your experience lends to what you're building at proof causal AI but you talked about, I just like to highlight a few things is you know your go to market business, which you mentioned early on, really doesn't know how to prove that value. And you mentioned some statistics, the ineffectiveness across a range of, let's say for fortune for 1000 over 50%. And, and that's, that's kind of scary when people are spending a lot of money in this space. But what you do is you measure the companies and the go to market, go to market effectiveness which includes marketing product, customer success and some of those other areas within the company. So I appreciate you sharing your insights. And Mark, most marketing analytics tools are built on correlation, showing what happened alongside what else happened. Why is that fundamentally insufficient for go to market decision making? And what does causal AI do differently that changes the quality of those decisions?

[Mark Stuss]

Well, causal AI is, is fundamentally about causal inference, which is not a new idea. The math on it has been around for a very long time. It is substantially more representative of reality than correlation. Correlation is essentially, hey, we saw that when it's sunny outside we sell more ice cream. But clearly the, the sun didn't cause the sale of more ice cream. Those two things just move together in time. And so if anything the sun in that sense would be what, what mathematicians call a confounder. And, and that's a negative word but what it really means is something that you don't control that has an impact that you don't control. But it's not the whole thing. It's by no means right. We're talking about a network of causes and effects that stretch out over time. The time lag is totally variable with the business and with the industry and with the market situation. This is, you know, we're talking about something that the marketplace reality is highly variable and correlative systems are breaking right now all over the place because of that extraordinary volatility and high velocity change. Two really primo examples of this that have nothing to do with go to market would be the chairman of the Fed commented about this about a month ago. And in his world, the more correlative kinds of approaches, econometric approaches, are just completely shattering. They're no longer representing the way that the economy can be expected to move. And that's just because it's correlation within a closed analytical system and it's diverging more and more and more from absolute reality, which it did not do that nearly as much for say the past four, 40 years. Another really huge example is actuarial analysis in the insurance business. We've all seen the news coverage about this property insurance company or that one exiting a particular state or a particular zip code where they won't write policies anymore. It could be because of wildfire danger, could be because of hurricanes and climate change related stuff. But the real deal is that because of the increasing volatility in the in the macro world, that their systems are struggling to accurately predict their level of risk going forward, which makes it impossible for them to price that risk, in other words, decide what they're going to charge you for your policy. And so that risk is so severe that they would rather do something they don't really want to do, which is just not write any policies for people in that area. But they'll do that because to accept the bet, so to speak, could expose them to levels of risk that their modeling no longer delivers. And so these are all reasons and illustrations of why correlation is a bust, right in the current environment.

[Brian (Interviewer/Host)]

Thank you. Appreciate you breaking that apart for us here. You did mention a couple things here. Causal AI is about causal inference. Your analogy about the sun and selling that ice cream, right. You explain the variability that can go into something like this and not everything can have a correlation that is going to give you that answer you're looking for. There's just too much volatility. And I appreciate you really unpacking a lot of that here for our audience. And mark proof, Causal AI is the only AI native platform that both masb, which is, I believe, the Marketing Accountability Standards Board Certified, and FASB Financial Accounting Standards Board Compliant. For listeners who may not know those bodies, why do those standards matter and what does it mean for a CFO or board to finally see marketing investment treated with the same rigor as any other financial asset?

[Mark Stuss]

Well, I think that's exactly what finance teams have been looking for for a really long time. And to be perfectly honest with you, they have just been really frustrated for years by the tendency of go to market teams to seek other ways of illustrating their value other than what you might call a truly business approach. FASB in particular is super important because FASB is the organization that develops the accounting rules that all companies in the United States use, and particularly public companies. But it goes well beyond that. And so when they see that we are FASB compliant, they kind of relax because they understand that we understand their situation. We actually do a lot in the FIDUCIARY duty and decision governance areas as well. So all of that kind of dovetails together in their minds. And it gives them, particularly early in the sales motion, a lot of confidence that they're talking to the right people who really understand what they're, what they're dealing with. The, the MASB piece is also really important for marketers. I mean, we want, we want, we want marketers and other professional groups to know that we understand where they're coming from too. Right. And that we are not, we're not trying to sharpen a knife at their expense. Right. In the end, one of the wonderful things about causal analysis, causal AI, is that everybody benefits. Well, you could reasonably say how. Well, it shows you what not to do more of because it's not working. And it also shows you where you're absolutely killing it and where you can do more and how much more until you reach a point of diminishing returns. So it's not only a kind of like good, not good kind of rubric, but it's also much more refined than that. It's saying, okay, how much should you really be doing in these areas to make sure that you get the most value without wasting money? And today, today that is, that's really super important because there's money is no longer easy and it's no longer cheap to get. And if you don't spend it the right way the first time, the opportunity cost later gets pretty severe. So you're kind of looking at a situation, maybe this is the best way to talk about it. Right. So for the last, say, four years, we're seeing a situation where cac, that's where acquisition cost is actually underreported. It's far larger than it's commonly declared as being, and it is growing substantially. At the same time, the deal volume that the company in question is experiencing, the average deal size, the average deal velocity, these are all going the other way. Right. Which is not good. And then you have the really arguably the worst possible compounding outcome, which is after 12 to 18 months of pursuit, the, the, the decision is, well, we're not going to buy from anybody. Okay? So you've just wasted all that CAC on that particular customer and didn't get anything for it. And you wasted it for a long period of time. So we are all about helping people, whether it's finance and those kinds of people or go to market professions who need and can benefit from better guidance in this area. We're here to help in that respect.

[Brian (Interviewer/Host)]

Thank you. And again, I appreciate you really unpacking a lot of this for our audience. But just again, I like to highlight a few things. You know, you talked about early on, the finance teams, the boards, they've been really frustrated with the way things have been reported in the past. And there's a lot of strategies where we throw a lot of money down after something that isn't provide a good roi. But they were frustrated and they want to find alternative ways to demonstrate their value in these areas. But you did mention being NASB certified and having that FASB compliance helps build that trust and helps really at the end of the day, people believe in that they're doing something that has some rigor behind it. Some, some, whether it's a certification or some sort of compliance is always a good thing. And then you talked about of course, the cac, the customer acquisition costs that are continually rising. And there's a lot of frustration in this area as well because we throw a lot of money after this. So I appreciate that. And mark the last question of the day. You've written about how AI is shifting B2B buying behavior and putting buyers more in control as agentic AI begins to act on behalf of buyers, researching, evaluating and even initiating purchases. How does that transform go to market strategy and what does it mean for demand generation as we know it?

[Mark Stuss]

That's a great question. It has very far reaching implications and consequences. For the first time, in kind of like in go to market history, we have a situation where customers are actively deploying capabilities using AI to filter and otherwise defeat the outbound marketing and sales activity of vendors. That is, that's really important for a lot of reasons, not the least of which is it demonstrates that they're pretty fed up with the last 10 to 15 years of go to market activity. Constant bombardment of marketing automation and things like that. I mean, you see this also in the EU legislation for the past decade. I mean, how many, how many laws have, you know, in their preamble say basically that, that the abusive marketing tactics of businesses is the reason why this law exists. I mean, wow, right? I mean, talk about an indictment. That is pretty bad. And so what we see today is enormous filtration of email and text messages so that the person that is the intended recipient doesn't even see it. It's intercepted at the server level. And you talk to IT teams, they're seeing, after they implement those kinds of tools, they're seeing really staggering reductions in email traffic because they're getting back to the actual non go to market kinds of email. Right. And Most. Well, just for those that are kind of wondering about this common question is well, just how much of your email is going to market? It's generally in a lot of businesses that I talk to and that Gardner has written about and all that kind of stuff. It's in the vicinity of 2/3 to 3/4. That is a lot of go to market email text is just as bad. I think anybody who is in business today can attest to that in their own experience. Right, so that is that we're seeing I think a fundamental move by customers to gain control of the process so called funnel and the funnel actually is now a filter. And one of the things that we did on our homepage we have a kind of looks like a chat bot attached to an LLM, but it's more than that and it's geared to talk to machines, so bots. Right. And we have a lot of bots that hit our website and interrogate our, our LLM, which is probably the most comprehensive LLM about causal AI that I've seen and also about proof, clearly. And so it is these are customers who are deciding who they're going to buy from. At an absolute minimum, they're creating their short list from all of that work. And that's great. I mean that's the way it should be.

[Brian (Interviewer/Host)]

Thank you, appreciate that. Really. Do you talked about AI in this space. We're looking down the road a few years and like many verticals, it's a double edged sword right now and we're exploring a lot and we're seeing AI just constantly leapfrog in some of the technologies. But your example of some folks using AI to circumvent those traditional go to market strategies be out of frustration and of course out of all this mess we start to see legislation come out, starting to crack down, limit some go to market strategies. You mentioned an example in the EU and, and they do have a lot just like California, but really to add more chaos to all this. Then you got all these bots. We talked about that quite a bit and there's just, there's just a lot to navigate and I'm glad that we have experts like you out here helping us find our way in this crazy go to market strategy space. So thank you and Mark, it was such a pleasure having you on today and I look forward to speaking with you real soon.

[Mark Stuss]

All right, thank you so much, Brian.

[Brian (Interviewer/Host)]

Bye for now.