How Marketing Services Companies are Reinventing Themselves With AI

How are marketing service companies reinventing themselves in the age of AI?

And how can AI help CMOs answer the constant demand to do more with less?

And if what we’ve seen with AI so far is just scratching the surface of what’s possible, what is hanging out beneath the surface?

Hi, I’m Courtney Baker, and this is AI Knowhow from Knownwell, helping you reimagine your business in the AI era.

For this episode, we wanted to bring you some excerpts from a roundtable on marketing in the age of AI that I conducted earlier this year.

After the roundtable highlights, we’ll bring you a discussion with Jeff Mason of Power Digital on the intersection of marketing, CX, and AI.

And we also have a fun game in store for you called Trick or Treat that will help you get your Halloween celebration started a little early.

But first, let’s dive right in to the marketing roundtable.

Here are highlights from my conversation with Knownwell’s Chief Product Officer and Chief Technology Officer, Mohan Rao, 2X CEO Dom Colasante, and Cognitive Path co-founder, Jeff Livingston.

So Dom, Mohan, what are you seeing as like the state of marketing agencies, marketing services?

What are you seeing in the industry at large?

I’ll jump in first.

I mean, I talked to a lot of peers.

Part of it, we are an acquisitive company.

And so as we look at other folks in the space, what I see is a lot of, I see a lot of concern about the continued growth and prosperity of our industry.

I think of the firms I talk with, flat is good versus high growth.

It’s way better than the alternative that many might see in the last three years of the client of marketing budgets and marketing program spend.

And so I think there’s a bit of caution around the space, but also I think a bit of a hunger of like, how could this be an opportunity?

Like, how might we not be disrupted by this but be the disrupter of larger firms, professional services firms, internal marketing functions, where we can bring something that the marketing leader needs if they don’t otherwise have?

Yeah, I love that.

Yeah.

You know, when I look at this from outside in and look at different marketing agencies, I really wonder about what is the differentiation for marketing agencies, right?

So it’s a case of, hey, physicians, can you heal thyself, right?

So how do you stand out, right?

And it is, as we talked to so many of the agencies out there, from the outside, when you go in, they’re very similar.

2X, I believe, is differentiated in a very special way.

But furthermore, just looking across the landscape, it’s really hard to see this differentiation.

And let’s focus on mid-market.

So, Dom and Jeff, what do you think?

Courtney, you’re a marketer yourself, you’re a CMO.

What do you think are some of the elements of differentiation that one should be looking at?

I think utilizing generative AI is just like table stakes now.

I mean, I think we’re getting very quickly to the point that it’s just a given.

And so it’s like, how are you leveraging it differently to actually deliver value in a new way?

How are you bringing something that I can’t get from any other agency that I choose and making that really clear?

Yeah, there is a difference.

I agree with you.

There’s a difference between doing things certainly, but being able to present and convince the market that you are truly different, right?

So what are your thoughts, Jeff and Dom?

You know, when I think of agencies, I always think of creative, right?

And the real differentiator, and I think we could probably all agree on this, the real differentiator, as we move further and further into the AI cycle, is going to be creative.

And it’s not going to be creative in the traditional, I’m Don Draper and I’m showing up with my great billboard at Chrysler, or here we go, don’t you love it?

It’s really going to be a hybridization of incredible human thinking and how it’s executed well with AI, so that it feels like an exciting experience.

I think there’s a few levels to build on too, of how it creates differentiation for an agency and what value it provides.

I think the story of values evolved.

And I think when we started, it was like, I’m using AI, therefore I’m innovative, I’m next gen.

That was the thing that was a phase that we had to say we were doing it, or someone had to see it somewhere.

That’s now become table stakes.

If you’re not using it, you’re a dinosaur.

So then it was the phase of like, well, we’re using it and therefore getting productivity benefits.

We can produce more output, we can save money, we can be more efficient.

There’s some cost-safe benefits maybe.

I think that’s quickly also becoming table stakes.

I think the next phase we’re moving to is, this produces something that’s better.

We’ve got examples of, it’s always fun to poke holes at AI-generated imagery.

And there’s plenty of evidence and warrant for that.

But we’ve seen that, you take an ad that we would have built in the old world, and take an ad bill with AI, and you could see real lift in conversion and engagement.

They’re more eye-catching, they’re more innovative.

They might not look right, and that’s kind of interesting in some ways.

You know, that can produce more engagement clicks, eyeballs, leads, dollars.

So it’s about, I think, telling the story of, like, how does AI get me more?

How does it get me more impact, more ROI, more revenue?

And I think that’s the phase where we can finally tell that story.

We’ve really brought value into the equation.

That’s great.

And I think it’s a great transition because I think where we are right now, so much of, you know, we don’t have really clear winners and losers in even which technology to use for which deployment.

You know, it’s kind of a, hey, what are you doing?

What’s working for you?

And Dom, because we have you on this call, we’re gonna pick your brain on what is 2X leveraging AI for?

What are the problems that you’re solving with AI?

And just share what’s working, what’s not working.

Yeah, so just to order of magnitude, about 400 of our people on our team use AI day to day, central to their role.

And I think it falls into two categories.

One being more the generative, creative type stuff, generating content, creating images, editing videos, and look the benefits of that are real.

And our team has embraced it.

I think there was a conversation at one point in the journey we’re all on in AI where it was scary for people, not our team.

Like this is a way for us to create leverage, deliver more, do the work of do five times as much work, which means maybe have a little more time to think.

And so that is a big part of our business.

We have some tools like Jasper that we have enterprise licenses with.

We partnered with Jasper about six months before the November ChatGPT launch, and I want credit for that because we were on the path earlier than everybody else.

But that’s sort of like a common thing you’d expect a marketing service firm to have.

We’re great at it.

I think the AI doesn’t replace the human.

The human that knows how to use AI replaces the human.

And we sort of embrace that as an opportunity of we’re going to bring more output and more value from creative.

The second part, I love that Jeff brought this up, is sort of the traditional type of AI in the predictive and the analytics space.

We partner pretty extensively with a company called Sixth Sense, which is one of the leaders in the ABM space.

We are their largest partner.

We do more consulting, implementation, managed services engagements than anyone in the world.

And in that area, we’re using the machine learning and sort of, I don’t want to say legacy AI, but the commonly known AI into help identify where there’s signals of intent and engagement and targeting.

That has huge lift.

I mean, we’re in a world where the buyer wants to be anonymous.

They don’t want you to know who they are.

They don’t want to fill out a form.

They want to operate on their journey in their, you know, independent way.

And then when they’re finally ready to buy, pop out and say, I’d like a proposal or a quote.

And the more as a marketer, you can learn about who’s consuming information, who’s on a website, who’s viewing content, who’s engaging in, you know, some type of program, the better you can do your job as a marketer.

And that effort, which, you know, about a third of our revenue is in that kind of space, is hugely beneficial because we’ve always wanted as marketers, like if we just knew who was kind of in market, we could aim at them.

And, you know, we spend so much of our time kind of marketing to the whole market, expecting that we’ll trip in people that are maybe in a buy cycle or maybe we can get into a buy cycle.

But if you just knew the people that were there, you can be 20 times more efficient with your spend.

And so that kind of stuff has been really where we’ve seen a lot of excitement.

And we add that all together between the generative, between the traditional or analytics.

It’s about 20 million of revenue per year we’re generating with AI solutions.

Might be one of the largest marketing services, AI practices.

We don’t always talk about it like we have AI services.

We talk about it like we have marketing services that are AI enabled.

Therefore, they’re better.

And they produce more impact and cost less and create leverage.

And I think that’s back to my point originally.

Every marketer is trying to find a way to get leverage.

They need to get more work done.

They need to deliver more impact.

They have less resources.

Some marketers are out there because they’re put under the gun by a CFO to cut costs.

But I think every marketer really needs to deliver more.

That’s the real problem.

And AI is a secret weapon to do that.

I feel like that is so true from our experience.

Mohan can chime in here as well.

Over and over again, we’ve seen marketing firms or CMO, they’re kind of on that cutting edge of using the technology or looking for ways to leverage it to get ahead more so than probably any other department and organizations.

We’ve really seen marketing lead the way.

And in a lot of ways, it makes sense, but it’s just even with this brand new technology is playing out for us.

Mohan, would you add anything to that?

Yeah, you know, I think everybody is on this journey, right?

So there is a two by two of thinking and doing.

AI can help with more creative thinking and more efficient doing, right?

So you kind of keep moving up that to the right top quadrant.

But the next sort of big thing would be around a more autonomous AI, right?

In terms of how can you build programmatic ad buys, right?

So where really there’s no human in the loop, it’s human on the loop, and just sort of just it’s been programmed and it just kind of it’s like financial trading, right?

So those sorts of things as well as personalization at scale.

I think those are the next frontiers with marketing and AI, at least from what I observe.

And I would love to get Dom’s and Jeff’s thoughts on this.

Yeah, I think that’s right.

They have a slightly different use case, but it’s in the same vein.

I think there’s an opportunity with AI to completely change how we do testing in the marketing world.

I think a lot of our old processes are, we generate a version we like, we come up with a few different variations that take different angles or different images or different personas or use cases or industry segments.

And we sort of split the segments up and test them and see if they’re statistically significant differences and then spend more money on those.

There’s ways to automate that.

One, from the content production side, we’ll do things like, well, instead of generating six different pieces of ad creative, we’ll write a little paragraph where we want and have a tool generate 700 different versions of ad creative.

Look at those, pick out the ones that are something we wouldn’t use, and then test 200 of them, and test them quicker.

Oftentimes, we find is the one that might win, either from a copy or a visual perspective, is the one we probably would not have put first or second as humans.

We would not have picked that one.

But the market votes with their clicks and eyes and engagement.

We’re piloting right now ways where you still want a human in the loop, but can you have a process where you’re dynamically creating, exponentially more creative than you otherwise would, and then automatically testing it, and then optimizing and pushing more budget and more intensity on the ones that are working, and really get to a better state of performance without seven times as many humans doing more work.

There’s some pilot cases we have and that are working really well.

You have to have a human in the middle to make sure you’re checking what’s going out, but oftentimes let the market vote on what they like the best.

And AI has huge leverage to be able to do that.

I love that and also do hate when that happens.

I would like for the market to choose the one that I just think looks the best, but it is so true.

Sometimes it’s the ugly that wins.

I’m not sure what we do about that.

Maybe AI can help in the future.

Jeff, what were you going to say?

Well, the whole conversation about the lesser quality content made me think of politics.

All jokes aside, we are in the championship season for politics, and if you’re going to take yourself out of the political framework and just look at it from a cold, sterile marketer’s perspective, what we’re about to see right now with AI is some of the most dynamic uses possible.

And I guarantee you that the creative agencies, like, forgive me, I’m going to say Targeted Victory because I know one of the guys there that owns it is a good friend of mine.

But I do know that what they are doing is using these variants very quickly.

The speed that they’re deploying ads and creative is just incredible.

And we’re going to see some really fast moving campaigns and topics are gonna shift from day to day.

And I think if we can, again, and I struggle with this as much as anybody, remove my personal politics and just look at how this is being communicated out to people, quite a lot of lessons to be learned on how quickly memes move from social network to social network to email to fundraising to ads and it’s going to be really kind of dynamic.

And I think you’re going to see AI play a massive part.

Again, to Dom’s point of view or point, excuse me, about versioning content, we’re going to see that happen and it’s only possible using brand frameworks or communications frameworks where this is the message, this is the look, now give me 30 variants, human, make sure there’s nothing that’s crazy and off the rails, it’s going to get us in trouble there.

Great, let’s go.

That’s how we ended up with mobile video by way with all these candidates just shooting videos of themselves walking around.

It’s by these variant types of technologies and different ad cuts.

When people use these two polished videos now of communications, it’s just less effective.

If you even look at, for example, with the Harris campaign, the video of her welcoming a little girl who had a cape on, much more dynamic than any of the professional cut video.

That’s because people identified with it.

This is about AI versioning and striking that humanity balance.

That’s good stuff there.

What I think is really interesting about this conversation is, in the beginning, we talked about marketing agencies really deploying creative and these external marketing use cases.

I would love to turn the coin over and talk about how do we start to deploy AI in agencies to help with the operations of the business, to help with things like client relationships, with just the ins and outs of running the business.

Dom, I feel like you have some specific use cases of 2X and how you’re doing that.

I do, and supported by none other than Knownwell in that sense.

There’s kind of a comment I made about analytics, about how the buyer wants to be anonymous, and the more signals we know, the more effective we can be at marketing to them.

As a marketing service company owner, the number one metric I track is net revenue retention.

I also care about margins and growth, and profitability and all those things, but net revenue retention is a scorecard, employee retention as well.

But net revenue retention first is the number one thing that tells me if the business is healthy or not.

Customers vote with their dollars, and how are they voting with us?

And one of the things we found is there’s signals everywhere in the business to know if someone is in a position of happiness or anxiety or dissatisfaction or potentially growth, like, I’m so happy I need more.

And as the company gets bigger and our firm has been on this rapid scale.

I mean, right now we’re hiring almost 100 people a month into the firm.

It’s hard to sort of build regimented processes to make sure all this data flows with humans involved, right?

And there’s signals and emails and ticketing systems and responses and meeting invites and call recordings from QBRs and weekly updates and NPS feedback.

There’s data everywhere.

And being able to look at that and say, what is the signal telling us?

And where might there be someone that we should lean in a little more?

Where might there be someone that seems to be exhibiting pains that we actually solved, that we’re not currently selling them?

And how might we look at that data through a very different lens and be more proactive in sensing sentiment and then behaving differently, which is what we know how to do really well in the marketing side.

We can sense someone was on your website and they followed you on social media and they clicked on these three ads and they opened these six emails and then we’re going to do something.

Well, how do we do the same thing when a customer is exhibiting those signs to the existing customer to us so we can provide a better level of service or even just like better fit their expectations that might have moved since we signed our original relationship.

And our business is all recurring revenue.

And so that becomes such a critical part.

And in my view, sort of one of those problems that you really can’t solve with the traditional process in humans and you can only throw so many managers and risk people and governance people and QC into the mix.

You got to kind of look at what all the data around you is saying and showing.

And I think we’ve made some really interesting headway in that space.

I had to build some kind of really cool ways to look at that and then sort of using AI to help us serve our real goal.

Are client facing teams, so like sales, customer success, using AI on a daily basis?

And if not, why not?

I think we’ve alluded to this a little bit, our perception, but I want to get like in a direct answer on this one.

Are there client success and customer teams using AI in their day-to-day work?

In our world, not enough.

No, it is not the most essential tool in their job.

It needs to be.

I think part of that is frankly, there’s not an AI customer service piece of technology that is out there that everybody buys.

I think Knowwell will be that, frankly, as a customer.

I’m seeing the capability that you have to proactively identify insights.

All of the churn prevention, the retention kind of conversations, the net promoter score analyzing, all of these things are backward looking of after something has already happened.

Those individuals need to be living in a system where they’re seeing things before they happen or in the moment that they just happened.

I think a tool like Knowwell can be really great at doing that and providing insights of like what are all the signals going on right now?

And how might I decide what I’m going to do today based on that?

But I think that’s a kind of an emerging area and one that not a lot of attention by, frankly, the tech companies and others have been focused on AI in that use case.

I think it’s a huge opportunity to make it back.

Yeah.

I mean, I think obviously, even if you look at ReadAI, very simple tool that integrates into any video chat.

One of the first things I look at when we get our transcript is the sentiment analysis.

I’m the lead for business development for Cognitive Path, which, God help us.

But for me, when I look at that, the first thing I want to see is one, how was our person, the person we were speaking with, how was her, how was his tone on that?

Were they feeling positive?

Were they speaking more at the time?

Or were we speaking more?

Were there clear take aways?

Things like that.

Now, of course, I have my own notes and my own recollection and may see things that the AI didn’t.

But more often than not, it’s the other way around.

And if there’s a moment where I thought things were probably going a little south or there may have been some concern that was expressed that needs to be resolved, I will definitely center in on that.

It’s a very powerful tool, even though it’s a very simple tool for me.

And if you think about the way we can use this in every single touchpoint and to pull out trends and to look at a larger relationship, this is something that could be extraordinarily useful, not just for attaining clients, but retaining them.

And in that sense, I really do see AI, and in particular, analytics, as something that can really fuel success for agencies and for professional services firms in general.

If you’re a marketing firm, guess what?

Good news.

We actually have built Knownwell just for you.

That’s right, nearly 70% of our first cohort of early access partners are marketing firms.

Remember, in the intro, when I asked what else lies beneath a service when it comes to marketing services and AI?

Turns out, it just might be platforms like the one we’re building here at Knownwell.

Go to knownwell.com/demo to find out why leaders like Dom at 2X are so excited to be among the first to use Knownwell.

Jeff Mason is the CEO of Power Digital Marketing, a modern growth marketing firm that works with companies in B2B, B2C, fashion, retail media, and more.

He recently sat down with Pete Buer to talk about the intersection of marketing, customer experience, and AI.

Jeff, it’s so nice to meet you.

Welcome to the show.

Thank you, Pete.

Nice to be here.

Tell us, if you would, for a little bit of context, those who are listening, about Power Digital and your role.

Yeah, sure.

Jeff Mason, CEO of Power Digital, and we’re a growth marketing services company.

The way to describe what we do is we meet mostly consumer brands, but as of recently more B2B, those types of brands on their growth journey, and we help them break through that proverbial glass ceiling of their next chapter of growth.

Whether it’s a $50 million brand trying to become $100 million brand, or $100 million brand trying to be $500 or $500 trying to be a billion.

Inevitably, all of them have challenges, sometimes more bespoke than others.

We figure out what those challenges and opportunities are, and we help them break through that glass ceiling of growth.

How we do that, very simply, is we help them get to know their customer better.

Oftentimes, a lot of these brands don’t have a data-related strategy.

If you don’t have a data strategy, you don’t have a customer-centric strategy.

A prerequisite to work with Power Digital is to connect your data sources, three primary data sources, customer data, advertising data, financial data.

This allows us to develop a full-motion video of what’s going on in the business.

Oftentimes, what we find is that they have a business problem, not necessarily a marketing problem.

What that leads to is studying the customer, refreshing the go-to-market, and marketing to a current customer more effectively, and then also leveraging what we know about the customer through that research, to find new audiences, to grow the TAM, to help them continue their growth journey, and more importantly than ever, a profitable growth journey.

Because I think there’s a much more heavy emphasis on profit today, which it should be, based off of where the economy is, where the interest rates are, than just pure growth at all costs from a revenue perspective.

And I think partly how you unlock that profit is through understanding the customer, marketing them more efficiently, acquiring customers at an efficient rate, and growing LTV to drive that bottom line.

The name of the podcast is AI Knowhow, and we haven’t said those two letters yet in this conversation.

So, can you share with us where AI fits in to the act of getting to know customers better or scaling the effort?

Yeah, I think number one is first recognizing, especially for consumer brands, that the buyer journey is very, very complex.

From discovery to research to consideration to validation to reconsideration to shopping and then buying.

And if you think about a customer journey, I might discover a brand on TikTok.

I then Google them to evaluate their reputation.

I might search their organic social profile to see, look at customer reviews.

I might look to see if they’re available on Amazon, because I’m a prime customer, right?

I have all these different touch points, right?

So, the first way to leverage AI is to, one, harness your data and most importantly, your customer data.

Because again, you don’t have a customer related marketing strategy unless you have a data strategy.

And you certainly do not have an AI strategy unless you have a data strategy.

And so, what we help our clients do is first and foremost, develop a data strategy.

And I think that’s the beginning part of the journey of being able to be AI enabled.

And one of the things that we can do now, especially with our product launch on September 10th, for our Nova Customer Insights AI product, is we can AI enable a consumer brand in 24 hours.

And I think that’s incredibly valuable to be able to interact with your customer related data in a chatable experience, where you can start asking very strategic and tactical questions to better understand what’s happening within your current customer file and what can I do to impact that.

What are the kind of things that either your alphas, betas are learning or you anticipate customers in the next launch are going to learn by working through the system with you?

If you think about what the look back period is for a lot of brands, they rely on reporting.

But reporting is very much a lagging indicator of what’s going on.

But when you look at reporting, and by the way, every different brand has bespoke reporting requirements.

Number one, giving the brand the ability to customize their own reporting environment is critical.

That’s the first thing we did.

That came directly as feedback from the clients is like, we want our own bespoke custom reporting environment.

We built that.

Number two, when you look at a report, the first thing you’re going to have is a question.

Where do you ask that question?

You’re going to either ask your marketing professional, you’re going to ask your financial resource, or if it’s a hidden data point, you may have to involve a data analyst, a data scientist, etc.

Now, picture all three of those experts built into a chatable experience that I can now interact with while looking at my custom reports.

Show me my top 20 most profitable customers.

What ad platforms were they acquired on?

What advertising creative did they engage with?

What was their conversion rate?

What was their cost to acquire them?

What’s their associated LTV?

I can now have this conversation with my data for my customers and how it ties to the engagement of the advertising that we’ve deployed, but also the financial economics that surround that customer profile so I can get a full motion video of what’s going on.

I think we’ve been able to develop this ecosystem because I think what brands that are in our alpha and beta are realizing is that they don’t know enough about their customer and so by having them ask questions into this AI-powered LLM that we’re building, it trains it and gets it smarter and smarter and the feedback loop is, yes, this is exactly what we’re looking for.

The short answer to your question, which was already long-winded, is what they’re trying to do is that they’re learning more about their customer and then they’re more importantly learning what they should be doing to market to them in a more effective manner.

Does this change marketing?

There’s so much conversation in every application of AI about what it does to jobs.

Will we see marketing teams changing configuration?

Will they need new skills?

What comes next?

Yeah.

Listen, I think the way we advertise is going to be different, and that’s what I call precision marketing.

A precision marketing environment, I would look at it in three pillars.

Number one, I alluded to this earlier, is forecasting customer behavior.

How they buy, when they buy, what they’ll buy, where they’re buying.

Being able to leverage data to be able to do that is step number one.

Step number two then is then what I call hyper-personalization.

Think about pricing models based off of income levels, based off of buying behaviors, based off of certain products they buy, based off of subscriptions, et cetera.

Customized sales, customized promos, et cetera.

I mean, you see dynamic product recommendations, but how about dynamic pricing that goes up with the dynamic product recommendation?

How about dynamic creative and dynamic case studies?

All these things that we drive hyper-personalization down to consumer level.

But then number three, I think what you’re alluding to is this notion of augmentation and efficiency, right?

And I think we’re starting to see this creep up in certain areas.

I think number one, content creation.

Obviously, you can leverage several different LLMs to create content.

And not just obviously text-based content, but now obviously creative-based content.

And so I think that’s going to make the workforce more, I would say, more efficient.

But I also think it will make them more creative because they can iterate on content so much faster.

And so instead of spending so much time on creating it, you can spend more time about thinking about it.

And so I think to your point or to your question about what type of skills, I think those skills are going to be more about how to create different types of content, whether it’s text content, blog content, creative content in a way where I’m thinking strategically about the customer and less about what I’m creating, if that makes sense.

And I think also it adds itself adds a layer of predictability into it.

So for instance, I talked about one of our Nova Intelligence applications called Creative Affinity.

It’s the only application that I know of that connects ad related engagement data to customer economics or customer purchases.

So I know, Pete, you engaged with this ad on meta.

And then I know your associated purchase behavior after engaging with that ad on meta.

I have that ability within our Creative Affinity application.

And so if I think about it, if you’re the ideal profile customer I want to market to because you’re the most profitable, you have the highest LTV, then I want to know what creative and what advertising best makes sense to you.

And so if I can take that content that’s created and then say, tell an AI to create 20 iterations of this, and maybe you want to see a background with sun in it or mountains, or I want to see the person wearing a watch, or black shoes, or his white shoes, or I want this.

I can quickly create 20 different iterations of that creative and deploy that into the advertising engines, and know that it’s going to speak to the most profitable customer cohort that I want to attract.

So I think it’ll allow marketers to think more strategically.

And I think that’s an incredibly important skill to have.

And it’s one frankly that we’re pivoting more into across all of Power Digital.

And why I think being able to use applications and data to do strategic work faster is where the whole industry and marketing is going.

Jeff, thank you.

It’s been wonderful to meet you and thank you so much for sharing your insights.

Yeah.

Same here, Pete.

Thanks for having me on.

Last Halloween, we played a game of trick or treat to close out a discussion that Mohan, David and I had.

We had so much fun that we brought it back this year.

Mohan and David insisted that I play along as well.

I am inviting Will Sherlin, one of our producers to come and join us to host this game.

Hey, Will, welcome to the show.

Welcome to the show, Will.

Long time listener, first time caller, honored to be here.

Thanks for having me.

You actually are the show.

That’s what people know.

Let’s get going.

But the idea here is we have four headlines, and we want you all to guess whether they are real or fake.

The first one is this.

Google DeepMind’s AI learns to play soccer from scratch.

Is that a trick?

Is that a real headline, Courtney, or a treat?

We’ll start with you and then we’ll go David Mohan.

Well, I do know that there was, I’m pretty sure this is true.

I’m pretty sure I heard about this.

I know that there was some AI that learned how to play soccer from scratch and learned how to pass.

I’m going to go with true.

I think it could be true that they learned the concepts of the game, but DeepMind itself would need a robot to play.

And so I’m going false because it can’t actually learn to play unless it’s got real arms and legs and we’ve attached Elon Musk’s new humanoid to it.

Okay, let me tell you the answer.

It’s true.

Whoa, period.

End of story.

The one thing I’m nervous on, Mohan, is is it the right company?

Hold on, we said true or false.

We’re supposed to say trick or treat.

So we all got it wrong.

Hold on.

I’m saying trick.

And I’m saying treat.

And I’m saying treat.

Courtney and Mohan, you get a bunch of candy in your bag because that is a treat.

According to Google DeepMind’s blog, Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning.

Okay, next up on the docket, is this a trick or a treat?

AI cameras spot toddlers not wearing seatbelts.

Courtney, since you went first last time, I’ll go with David first this time, then Mohan, then Courtney.

If it’s not a treat, it needs to be a treat.

It can be done.

I’m going treat all the way.

It sounds like something real.

Let me see.

I’m going to go with treat.

Okay, I’m going trick and I’m going to go trick that it’s not just toddlers, it’s just anyone not wearing seatbelts.

Look at you.

Picking up on the nuance.

Yeah.

Okay, this time, Mohan and David get the candy because according to the BBC, in August of this year, AI cameras did spot toddlers not wearing seatbelts.

Got to keep those kiddos safe.

Yes.

I mean, what is wrong with these people?

Courtney, David and I care about safety.

All right.

So, Mohan’s up.

Mohan’s winning.

Okay, Courtney, come on.

We got to get this.

Come on.

Let’s go.

Yes.

All right.

Well, Mohan has had the advantage of not going first yet.

So, Mohan, you’re up first this time.

Headline number three, AI startup claims breakthrough in emotion detection for customer service applications.

Is that a trick or a treat?

What?

I’m going to go with a trick on this one.

No rationale to help me think it through, huh?

I know, right?

So, this one feels like a treat to me, but there has to be one in here that they made sound real.

It’s totally doable and is wrong.

So, I was thinking trick, but I really want to go against you, Mohan, because I need to pick up a point, but I got to go with my gut.

I’m going trick.

Awesome.

This win, y’all, not fair.

I feel like now I’m playing the odds on winning and losing.

I know.

That’s what I really think.

I’m going to listen to the directions.

My gut is this is a treat, that this just makes so much sense.

Unfortunately, this win is a trick, but it’s because people don’t know about Knownwell yet.

Courtney, you and I have to do a better job of getting the word out.

Oh, gosh.

Yes.

I’m firmly putting myself back in the host seat from now on.

I’m never playing again.

All right.

Headline number four.

I’ve lost track of who goes first, but I think it’s Courtney.

Robot artist becomes first AI to hold solo art exhibition at major gallery.

Trick or Treat.

I don’t know.

I just want this to be a trick.

I just don’t like the idea of AI taking things like art away from us.

We love art.

We want to keep doing art.

It’s ours, AI.

Sorry.

I’m going the opposite direction.

It’s totally a treat.

I think I really did see a story on BBC on this one, so I’m going to go with a treat.

It is indeed a treat dating all the way back to 2019.

From 2019?

Yes, Time Magazine.

This robot artist just became the first to stage a solo exhibition.

What does that say about creativity is the headline.

Yeah.

I don’t like that one, so I’m going to stand with my answer.

Mohan, did you go undefeated?

Did you go four for four?

I think I went four for four.

Wow.

For the record, we came on the show and Mohan was like, hey, I didn’t have much time to prepare today.

I think that was just setting us up.

He actually found these and went and dug them up and did some research.

Is that what you’re saying?

You’ll see you in Halloween 2025 for the next round.

That’s right.

Thanks as always for listening and watching.

Don’t forget to give us a five-star rating on your podcast player of choice.

And visit knownwell.com/demo for a guided tour of our AI-powered platform for commercial intelligence.

At the end of every episode, we like to ask one of our AI friends to weigh in on the topic at hand.

Hey, Perplexity, how are you?

This episode, we’re talking about how marketing firms are reinventing themselves with AI.

So what do you think?

Marketing firms are really shaking things up with AI, making their strategies more efficient and personalized.

It’s exciting to see how this tech is transforming everything from content creation to customer engagement.

And now, you’re in the know.

Thanks as always for listening.

We’ll see you next week with more AI applications, discussions and experts.