Consumers skip ads but not rewards. Fetch drives performance with 12.5M+ monthly users and 11.5M+ receipts scanned daily, capturing 88% of household spend. Your brand becomes the reward earning real engagement, verified purchases, and lasting loyalty. Fetch: America’s Rewards App. Where brands are the center of joy. Learn more at business.fetch.com.

Marcus Johnson (00:00):

Consumers skip ads you'll be shocked to learn, but they don't skip rewards. Fetch drives performance with over 12.5 million monthly active users and over 11.5 million receipts scanned daily, capturing 88% of household spend. Your brand becomes the reward, earning real engagement, verified purchases and loyalty. Fetch, America's rewards app, where brands are the center of joy. Hey gang, it's Friday, October 3rd. Grace, Lisa and listeners, welcome to Behind the Numbers, an EMARKETER video podcast made possible by Fetch Rewards. I'm Marcus. Join me for today's conversation. We have two people. We start by introducing our tech and AI analyst living in California. It's Grace Harmon.

Grace Harmon (00:53):

Hi Marcus. Thanks for having me.

Marcus Johnson (00:54):

Of course, of course. And we welcome to the show, senior editor based in Florida, Lisa Haiss. Hello.

Lisa Haiss (01:01):

Hi. Thanks for having me.

Marcus Johnson (01:02):

Absolutely. Thank you so much for being on. We start of course, with today's fact. All right. Today's fact is about Albert Einstein. So a few things about him. Born in Germany, 1879. He lived in Italy, Switzerland, [inaudible 00:01:21] until he eventually moved to the US in 1933. For the final 22 years of his life, settling in Princeton, New Jersey in 1905 was when he came up with his famous formula E=MC2, figuring out that matter, those very tiny particles that make up everything in the world, can be turned into energy. And he made his historical breakthrough at age 26.

(01:51):

Good God. The formula formed part of Albert's... Are we on first name terms Albie? I'm so sorry. This is so insulting. Mr. Einstein's general theory of relativity he worked on over the next 10 years helping him to win the Nobel Prize in physics in 1921. The reason this is my fact is because there was a plumbing company van outside my apartment the other day called Intelligent Service with a caricature of Einstein on the side as the company logo. And I just feel like it's a bit insulting to someone who won the Nobel Prize in physics to have his name on the side of a plumbing truck. Is that fair?

Lisa Haiss (02:35):

I think that's fair.

Grace Harmon (02:35):

It's fair.

Marcus Johnson (02:37):

Okay. It's being used to help sell heating and draining services.

Lisa Haiss (02:41):

It's a little weird.

Marcus Johnson (02:42):

Yeah, you deserve better. No offense to plumbing. It's hard, but it's not Nobel Prize... Anyway, today's real topic. How marketers feel about using AI at work. All right, so our briefing's analyst, Marissa Jones, notes that US ad employment continued its downward trend in June with jobs in advertising, PR and related fields falling by 700 jobs according to the Bureau of Labor Statistics. Adage points out that the decline marks the seventh consecutive month of ad industry job losses. Lisa, I'll start with you. What do you make of these latest ad employment numbers?

Lisa Haiss (03:22):

I hate to say it, but AI is taking over the ad industry. It's so easy to just plug things into AI, ask it questions and it will spit out copy and everything you want it to, but at the same time, I think that ad agencies are getting a little bit ahead of themselves, because they're not keeping humans in the loop.

Marcus Johnson (03:46):

Yes.

Lisa Haiss (03:47):

I think there's a mistake there.

Marcus Johnson (03:50):

Yeah, it certainly feels that way. Grace, to what Lisa's saying, it definitely feels like they're more structural concerns with regards to employment in the ad space than just the typical tariff anxieties, economic uncertainty. They seem like concerns at the moment, but there are stats, like 40% of us ad industry professionals have job displacement concerns related to AI adoption. According to IAB, a quarter of marketing leaders planning to cut staff last year as a result of the emergence of gen AI. According to Gartner, it does feel like AI is really making its impression on the marketing space in a way that is making some jobs, one way or another, disappear.

Grace Harmon (04:31):

Yeah. And we've been seeing companies like Kantar that have had to roll back these pushes into getting rid of employees, automating their work instead. But I think overall, this just marks this large shift. And Marissa said this, but the shift that's prioritizing cost-cutting and short-term efficiency over having human insights staying in the loop, which is really concerning.

Marcus Johnson (04:52):

Yeah, it does feel a bit short-sighted. To what we're saying. There's a lot of moves happening right now, but does that help you further down the road? Gadjo Sevilla, our senior analyst, had this really good point. He was saying "AI is taking over tasks once handled by junior staff. Agencies and brands are embracing the efficiency and cost savings of AI, but at the risk of cutting the very pipeline that feeds future leadership per MarTech." So what he's talking about here is AI adoption hitting younger folks the hardest. There was a survey from IBM Institute for Business Value, noting half of C-suite level executives said gen AI would have a significant or extreme impact on entry level positions. So maybe this shows up a lot worse later down the road. What do we think?

Grace Harmon (05:44):

Well, I think later down the road, you mentioned this very briefly, but there's also just a huge shortage of junior roles and roles for younger people at these ad agencies. And that's something that right now is an economic concern and it's unfair. But also down the line, it means you're going to have this shortage of workers at a certain level, you're going to have a shortage of diversity of opinions from different generations. So again, I think it's short-sighted.

Marcus Johnson (06:10):

Yeah. Yeah. The employment numbers, if you look at them, they don't look too bad overall about just over 4%, 4.3% in terms of unemployment rate across everyone. But when you key in on the recent college grads, to what you're saying, Grace, in Q2 2025, recent college grads are 22 to 27 year olds, that unemployment rate is closer to 5.8%. So it doesn't seem like a lot more, but it's 25% higher than the national average of the 4.3. And part of that is because of these entry level positions, which are just going away. And the companies are using AI instead.

(06:49):

So folks are replacing, hold on, maybe not replacing, maybe they're just using it and they don't need the jobs anymore that they had before. Maybe people aren't being directly replaced, but people are using it at work in different ways. And there's a bunch of data that shows how people were using it, marketing folks in particular, how they were using gen AI last year. As you can see from this chart, 25 to 40% of people were using gen AI for data, analysis, market research, copywriting. According to MediaOcean, 34% of Amazon sellers were using it to write and optimize listings. According to Jungle Scout. Lisa, are most marketers still just using AI for these more rudimentary tasks?

Lisa Haiss (07:31):

Pretty much. Probably the top use case right now is still content generation. So that's something that is a really easy thing to do, but at the same time, it's not necessarily the best idea. I think they're missing out on really important use cases like content analytics. That's something that BearingPoint brought up. Only 9% are using it for content analytics right now, and by 2028, 29% are planning to use it for that purpose. But that's honestly still really, really low. Yeah.

Marcus Johnson (08:02):

Yeah.

Grace Harmon (08:04):

Yeah. I think those internal use cases are really important because in terms of just public opinion and brand perception generated social media, content generated images don't necessarily always go over well with consumers. So if you're looking to test AI within your organization, these really useful use cases are also internal facing.

Marcus Johnson (08:25):

Yeah, yeah. What we're using it for is different or it's changing. Somewhat, not as much as maybe it should be. But also what we need to learn to use the technology is also something people are paying more and more attention to, workers racing to upskill in AI was the title of one article from Megan Morrone of Axio saying that employees across industries and job functions clamber to acquire AI proficiencies according to online learning platform Udemy. Grace, when it comes to upskilling in AI, what skills should marketers be prioritizing in your opinion?

Grace Harmon (09:04):

I think one key thing to teach employees is which models are best suited for individual tasks, their strengths, their weaknesses. And then another major one is how to write prompts efficiently. That is just a place where a lot of people are losing a lot of time is figuring out how to coax the right answers out of these engines. So if you can teach people how to leverage the right tools, how to get the best answers out of them quickly, I'd say that's really important. And then another component is just listening to employees, factoring in feedback, providing resources, figuring out which models are most important and which ones they're actually using and provide them. Comprised found that 49% of executives said employees are left on their own to figure out AI tools, and about two thirds are paying for tools out of pocket because their employees just aren't providing the ones they want.

Marcus Johnson (09:51):

That number was shocking.

Grace Harmon (09:54):

Yeah. I don't know how well you can expect people to adopt these tools if you're not providing them with the resources to benefit from them.

Marcus Johnson (10:00):

Yeah.

Lisa Haiss (10:01):

Yeah. I was just talking to a friend of mine yesterday about her company is implementing AI across the board, but there is zero training. She asked me how I use it because she doesn't know how to use it.

Marcus Johnson (10:13):

Yeah.

Grace Harmon (10:14):

There's also a generational and gender gap in terms of upskilling that is really concerning.

Marcus Johnson (10:19):

It feels like there needs to be a certain level of AI literacy because of this aphorism of you won't lose a job to AI, you'll lose it to someone who knows how to use AI better than you. Part of the problem though is when? When am I supposed to learn? People have a lot to do already, right? There was a marketing director piece by Esther Lastra who was noting two thirds of marketers emphasize that learning the latest AI tech is important, but it takes time away from their day-to-day responsibilities according to Gartner. So a big part of the question is, yes, you need the right training, you also need time to take the training, and it ideally needs to be ongoing as well. We had one today actually that our colleague, Corina Perkins led. And Grace your point, I thought it was really good because one of the things she was saying is not just here's how to use it, but here's where you shouldn't use it. And I think that's an important piece as well.

Grace Harmon (11:12):

These models have weaknesses. Absolutely.

Marcus Johnson (11:14):

Yeah. Lisa, how about for you? What do you think the most important skills, what the market should be prioritizing?

Lisa Haiss (11:20):

I think it should be SEO and GEO. And SEO isn't dead. It's always going to be around. Keywords are important. Analyzing keywords is important. But generative engine optimization is really key to make sure that your content is still appearing in AI overviews or any other AI results just because you still need to get your brand out there. And if readers aren't clicking elsewhere, they need to at least see that you are authoritative on a subject and they need to be able to link to that content.

Marcus Johnson (11:55):

You wrote a really brilliant piece. Folks can go and look it up, the title of it being Marketers Lack GEO, Generative Engine Optimization Skills As Consumers Embrace AI-Generated Results. I thought it was, yeah, it speaks exactly to what you were talking about. It was a really good piece.

Lisa Haiss (12:11):

Thank you.

Grace Harmon (12:13):

Just to capitalize off one thing Lisa was saying that yeah, SEO definitely isn't dead. There's some data that our coworker, Nate Elliott was sharing with me just the other day, that people who are jumping on using these chatbots and these generative engines are still using search at a very high rate. ChatGPT users are not non-users of search. So yeah, it's absolutely so important to keep those SEO strategies going.

Marcus Johnson (12:35):

Yeah, it's going to be a balance. It's going to be a 90, 10, 80, 20, and slowly paying more attention to GEO without neglecting the SEO portion. Talking about using it, what people are using it for, what skills should people be prioritizing? There's still a stigma though, it feels like when people are using AI in general, but work in particular, there was an Inc. article by Bruce Crumley writing that employees fear the stigma of using AI at work according to a Duke University study. He explains that companies tell workers to use AI to do their work more efficiently. Many worry their colleagues will think of them as lazy. And there was another stat I found from this Augusto survey. 45% of US employees have used AI at work without telling their supervisors. Grace, what's your take on this stigma of using AI at work?

Grace Harmon (13:31):

Well, yeah, there's a huge amount of shadow use, but I do think the stigma has two main sources, and that would probably be fear of replacement and skepticism about quality. On one hand, employees worry that, like you said, relying on AI signals a lack of skill or can make the roles redundant. And on the other managers and peers, I think sometimes assume and often accurately that AI outputs are less trustworthy. So I'd say from an analytical standpoint, what's interesting is that stigma does tend to fade once organizations set clear boundaries for AI use and position it as an assistive tool rather than a replacement.

Lisa Haiss (14:09):

Using AI as a co-pilot rather than a replacement, I think is really important.

Marcus Johnson (14:15):

Yeah, I like that. A helper of sorts is a great way of looking at it. But yeah, I don't know, wondering how long it's going to take to get past that. Is this something where in the next year it won't be as much that taboo to be using this? Or is this just going to be something that takes a long time?

Lisa Haiss (14:37):

I think if there's full disclosure from a company, I think that's really key to transparency and making sure that everybody's on the same page as far as AI goes. There shouldn't be stigma around using it to figure out how to get an Excel formula to or how to calculate percentages. Because I have used that many times and I check it elsewhere too, of course. But there's ways to use it that are just going to supplement and give you more time to do other things that are more interesting to you.

Grace Harmon (15:11):

Yeah, there's the societal normalization aspect, but like you said, I think company by company, normalizing it, it follows education, transparency and governance. Those are the big three.

Marcus Johnson (15:21):

Yeah. I find this part of the conversation really interesting, which is that there's stigma of using it, but there's also a level of embarrassment about how little people actually understand the technology. There was a third of workers saying they were embarrassed about how little they understood AI according to a July LinkedIn report. So that's on the one hand, people being honest and saying, look, "I'm embarrassed about how little I know about this, how AI literate I am, or I am not." The other part of it. As a colleague, again, senior analyst Gadjo Sevilla was pointing out this great AI bluff. He was writing that AI proficiency is now a baseline job requirement with 95% of organizations prioritizing it in hiring new staff, which is likely why nearly 80% of professionals exaggerate their AI knowledge and over 90% of C-suite execs admit to overstating their skills according to a plural site 2025 AI skills report indicating a culture of AI faking it at work in the US and the UK companies.

(16:20):

Gadjo explained that fear is likely driving the deception as employees worry about AI being directly tied to job security, Grace, as you were mentioning, whilst their leaders are increasingly pressured to project confidence as businesses race to adopt AI. That seems like a bigger problem to me almost than the stigma of it is people pretending that they know more than they do with regards to the technology. Finally Lisa, which part of the using AI at work conversation do you think needs more attention?

Lisa Haiss (16:51):

Honestly, it's just training. It's so easy to get trained on AI and you don't even have to wait for your company to say anything. There's really short courses to take and they're free. So the only reason that somebody wouldn't be trained on it is if they didn't take the initiative to do it. And I think that's really important right now to take the initiative to learn more about AI.

Grace Harmon (17:15):

Yeah, and a lack of training does really carry the opportunity to widen those skill and opportunity gaps if some workers are empowered and some aren't. So yeah, I think that the next phase of that conversation needs to move past working just on efficiency and working on equity of training and sustainability of the organization, because like what we were talking about earlier in terms of being short-sighted, looking at productivity gains, it's a lot more important to make sure your employees understand, of course, how to write prompts. Like I said, what tools are useful in different use cases. But data privacy policies at the company, ethical guardrails and how you want the brand to be presenting its use of AI.

Marcus Johnson (17:53):

Yeah, yeah. I really like that part of this, because to what you're both saying, Grace to what you just said, Megan Morrone of Axio saying it's not just chatbot tutorials. Learning how to use AI responsibly means understanding its capabilities along with its risks, limitations, and as you just said, it's ethical concerns. And I found some research, general assembly, just 17% of marketers said they've received comprehensive role-specific training that prepared them to use AI effectively. That's too low.

Grace Harmon (18:25):

That's horrible.

Marcus Johnson (18:27):

How about you, Grace? Is there anything else you think people should be paying more attention to when it comes to this using our work conversation?

Grace Harmon (18:34):

I think, again, just circling back to data privacy is a really big deal. I've met people that didn't really understand that on these free accounts, that you might not attach your name to whatever you're putting into a chatbot or a generative engine, but using proprietary data and these AI tools can leak the data. It's used for AI model training frequently. So I think that's one big thing, just in terms of shadow use that could be an issue for a company. And then just in general, I think consumer privacy.

Marcus Johnson (19:02):

Yeah. When you say shadow use, explain for folks what you mean.

Grace Harmon (19:05):

Shadow use is use of AI, I guess in this case I'm talking about specifically at work when it's not sanctioned or not disclosed.

Marcus Johnson (19:13):

Excellent. Unfortunately, that's where we're going to leave conversation. It's been a brilliant one. Thank you both so much for your time today. Thank you first to Grace.

Grace Harmon (19:20):

Thanks guys for having me.

Marcus Johnson (19:21):

Of course. And thank you to Lisa.

Lisa Haiss (19:23):

Thank you. It was great.

Marcus Johnson (19:24):

Yes, indeed. Thank you of course. To the whole editing crew, to everyone for listening in to Behind the Numbers, an EMARKETER video podcast made possible by Fetch Rewards. Subscribe, follow, leave a rating and review all that stuff. We'll be back on Monday talking about the ethics of AI in ads. Happiest of weekends.