Behind the Numbers: Using AI at Work: Part 1—Employees Anxiety Levels and How the Tech is Impacting Jobs | Mar 31, 2025

Summary

Behind the Numbers: Using AI at Work: Part 1—Employees Anxiety Levels and How the Tech is Impacting Jobs

EMARKETER’s “Behind the Numbers” podcast delves into the evolving landscape of digital media, providing marketers, retailers, and advertisers with critical insights. In the March 31, 2025 episode titled "Using AI at Work: Part 1—Employees Anxiety Levels and How the Tech is Impacting Jobs," host Marcus engages with EMARKETER analysts Garjo Sevilla and Henry Powderley to explore the growing concerns and tangible effects of artificial intelligence (AI) in the workplace.

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1. Setting the Stage: The Rise of AI in the Workplace

The episode opens with Marcus introducing the topic of AI’s integration into the workplace, focusing specifically on employee anxiety and job impacts. Garjo Sevilla, EMARKETER’s senior analyst on AI and technology, and Henry Powderley, the SVP of media content and strategy, join the conversation to dissect current sentiments and future projections.

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2. Employee Anxiety Surrounding AI

A significant portion of the discussion centers on the growing anxiety among employees regarding AI's role in their professional lives. Citing a recent Pew Research study, Marcus highlights that "52% of Americans are worried about the future use of AI in the workplace, compared to 36% who are hopeful" (04:07). This sentiment reflects a broader unease about the potential for AI to displace jobs and alter traditional work dynamics.

Henry Powderley offers a counterbalance, suggesting that anxiety may subside over time as employees become more familiar with AI tools. He posits that "the anxiety will lessen as people find relief and efficiency through generative AI (gen AI) tools, allowing them to offload mundane tasks and enhance their strategic work" (05:01). Henry emphasizes the importance of organizational support, including training and resource allocation, to help employees adapt and thrive alongside AI technologies.

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3. Impact of AI on Job Prospects

The conversation shifts to the tangible impact of AI on job opportunities. Marcus references studies indicating a pessimistic outlook among workers:

• 32% believe AI use will lead to fewer job opportunities.
• 6% foresee more job opportunities.

Interestingly, this pessimism spans both AI users and non-users, with AI users expressing a 3-to-1 ratio of fearing fewer prospects, while non-users exhibit a 6-to-1 ratio (06:05). This trend underscores a pervasive fear that AI may render certain roles obsolete, particularly in knowledge-based industries where AI can enhance productivity but might also streamline workforce needs.

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4. Challenges in AI Adoption and Training

A critical barrier to alleviating anxiety is the gap between AI adoption and effective training. Marcus notes that only 12% of workers have taken an AI-related class in the past year (07:30). Garjo Sevilla adds that "less than 40% of the workforce have access to generative AI tools", and of those, only 60% engage with these tools daily (08:31). This disparity highlights a significant challenge: without proper training and access, employees cannot fully leverage AI’s potential benefits, thereby perpetuating uncertainty and fear.

Henry Powderley emphasizes the need for organizational investment in training programs to enable employees to explore and effectively use AI tools. He suggests that companies must balance encouraging innovation with implementing robust security measures to protect sensitive data (07:36).

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5. Security Concerns with Personal AI Tools

The reliance on personal AI tools introduces security vulnerabilities. Marcus points out that "half of knowledge workers are using personal AI tools at work", often at their own expense, as employers do not provide adequate resources (09:04). Garjo Sevilla highlights the risks associated with employees using unvetted AI applications, which can lead to the mishandling of company data and intellectual property (09:48).

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6. Diverging Perspectives on AI’s Impact

The guests explore differing views on whether AI's impact on jobs is currently significant or overstated. Garjo Sevilla argues that while AI adoption is increasing, its full impact is mitigated by factors such as "AI slop"—the proliferation of low-quality AI-generated content that undermines trust and slows meaningful integration (18:01). He suggests that strategic, regulated implementation of AI tools is necessary to harness their benefits without adverse effects.

Conversely, Henry Powderley presents data indicating significant AI penetration across various sectors. He cites a Nextiva survey where 40% of respondents use generative AI for customer communications, and 34% of retail CFOs employ AI for pricing strategies (13:40). These statistics demonstrate that AI is already reshaping job functions, particularly in areas like programming. Marcus references a Washington Post article about the decline in computer programmer employment, attributing it to AI's growing proficiency in coding (15:15).

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7. The Future of AI in Job Markets

Looking ahead, Henry emphasizes that AI will continue to evolve as a tool rather than a replacement. He shares his experience with adopting AI tools like Spiral for copywriting, which streamline workflows and enhance creativity without eliminating the need for human input (12:26). However, he acknowledges the need for companies to establish clear policies to mitigate data security risks while fostering an environment conducive to AI exploration.

Garjo Sevilla adds that major tech companies, like Google, are heavily investing in AI, with 25% of their coding being AI-assisted (16:56). This trend signifies a deeper integration of AI in professional tasks, potentially transforming how industries operate and create value.

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8. Balancing Optimism and Realism

The episode concludes with a balanced view on AI’s role in the workforce. While there is undeniable anxiety and some negative impacts, especially in sectors vulnerable to automation, there is also optimism that AI can augment human capabilities. The key takeaway is the necessity for proactive measures—such as comprehensive training, strategic implementation, and robust security protocols—to ensure that AI serves as a beneficial tool rather than a disruptive force.

Garjo Sevilla remarks, "AI should be seen as an assistant, not a replacement" (10:29), encapsulating the episode’s overarching message: the future of work with AI hinges on thoughtful adoption and continuous adaptation by both employees and organizations.

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Conclusion and Looking Ahead

As the episode wraps up, Marcus teases the forthcoming second part of the series, scheduled for April 4th, which will delve deeper into how businesses are utilizing AI and offer practical tips for integrating AI into the workplace effectively. Listeners are encouraged to stay tuned for actionable insights that can help them navigate the rapidly evolving AI landscape.

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This episode underscores the complex interplay between technological advancement and workforce dynamics, highlighting the importance of preparedness and proactive strategies in mitigating anxiety and harnessing AI’s full potential.

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Notable Quotes

• Marcus: “52% of Americans are worried, 36% about the future use of AI in the workplace.” (04:07)

• Henry Powderley: “The anxiety will lessen as people find relief and efficiency through generative AI tools.” (05:01)

• Garjo Sevilla: “Less than 40% of the workforce say they have access to gen AI tools.” (08:31)

• Henry Powderley: “Organizations need to push in the direction of using generative AI to explore new products and enhance creativity.” (05:01)

• Garjo Sevilla: “AI should be seen as an assistant, not a replacement.” (10:29)

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For further insights and detailed analysis, subscribe to EMARKETER’s "Behind the Numbers" podcast, available on all major platforms.

Transcript

[Marcus]

Struggling with out of stocks, phantom inventory or lack of shelf data. Traxx's signal based merchandising is designed to give real time visibility into what's happening in stores and on shelves so you can take action when and where it matters most. Interested, Head to traxtrax retail traxretail.com and click the Get Started button in the top right hand corner. Hey gang. It's Monday, March 31st. Garjo, Henry and listeners, welcome to the behind the Numbers show and Emarketer video podcast made possible by Tracks. I'm Marcus. Today we'll be discussing using AI at work. For the conversation I'm joined by two folks. Let's meet them. We start with our senior analyst covering AI and all things technology, based in New York, it's Garjo Sevilla.

[Garjo Sevilla]

Hey Marcus. This is exciting.

[Marcus]

Hello sir. Thanks for being here. And we also have our SVP of media content and strategy. Living in the land of the lighthouse, it's Henry Powderley.

[Henry Powderley]

Hey Marcus.

[Marcus]

Hey fella. Today's why do we blow out candles on top of birthday cakes? Here's why. So according to Elisa Levin's book A Slice of History. Great, great book. Historians credit the origin of birthday cakes with the ancient Greeks explaining that it was a way to honor the birthday of Artemis as a goddess of the moon. And they would bake moon shaped cakes decorated with candles to make them glow like the moon. And the Greek candle smoke would rise to the heavens where Artemis, the daughter of Zeus, lived. Since offerings to the gods were a common custom in ancient Greece, the reason we put the same number of candles on the cake as the person's age is because of our German friends. German Kinderfest or Children's festival. Basically, kid's birthday dates back to the Middle Ages and the cake was topped with lighted candles which were presented to the kid on the morning of their birthday. They used to have the candles just burn throughout the day until the cake was eaten after the evening meal. Fire hazard. But then now it's obviously it's changed. They blow them out straight away. According to the Extraordinary Origin of Everyday Things, there's a book by Charles Panetti, the number of candles on the Kinderfest cake equaled the kid's age plus an extra one representing the light of life, which makes blowing them out a little bit dark. Pun. I like one for good luck better intended. Yeah, exactly.

[Garjo Sevilla]

You always need a spare, right? I guess. I don't know.

[Marcus]

Spare candle? Yeah, yeah, but at like 5. What's the like at 5? You stop putting on the Same amount right as the person's age. When does that stop? Teenager?

[Henry Powderley]

Depends on the size of the cake, I guess.

[Marcus]

Yeah. All your parents? My mom was like, we're done here. Okay, six. She cut me off. That's a joke. Kidding. Love you, mum. Anyway, today's real topic, using AI at work, part one, employees anxiety levels and how the technology is impacting jobs. All right, for this episode, it's the first episode of a two part episode. Second episode will be on Friday, April 4th. Today we're talking about how the technology is affecting people, affecting the workers and how it's impacting jobs as well. We'll start with the workers piece of this. So it appears as though anxiety around AI in the workplace is getting worse. There's a recent Pew Research study noting that more Americans are worried, 52% than hopeful, 36% about the future use of AI in the workplace. Current and future use. The gents are going to take differing arguments for us. So these opinions don't necessarily reflect their personal views on the topic. But Henry has volunteered. I made him present to present the argument that folks will become less worried over time. So it seems like they're becoming more worried. But Henry Watson, the argument that that actually will peak and end up going in the opposite direction.

[Henry Powderley]

Sorry, thanks for telling everybody that you made me do this. As a caveat, I do think that there certainly are types of jobs, especially ones that are more automated and I do think there's reason to worry in the future. But most of the jobs that we're talking about, especially in the emarketer audience, are from the knowledge work universe. And I do think that there's reason to believe that the anxiety will lessen over time. And I think it really will boil down to two things. The first being people actually finding help in their job using gen AI tools. The more people use this stuff, the more they find efficiency, the more they are able to offload those low hanging fruit tasks that have kind of made the onerous part of the workday. The more that they find themselves have a thinking partner by using gen AI to validate their strategies to check their copy. There's so many different examples that we could talk about where AI can help someone in the workplace, but it's only when somebody actually feels that relief and feels like they've gotten that help when they're going to start feeling less anxious about it. And then the second side is on the organizational side, like, you know, when people start to see that help in their work, are they met with more resources or more opportunities to grow in the organization. Do they feel like they're getting enough training that's enabling them to find that kind of, you know, relief and creativity that can be found through using gen AI? I think it really will depend on organizations pushing in that direction and then how they react to, you know, people finding more efficiency in their work. Is it, is it going to be a reaction that's downsizing or is it a reaction where investment is made so that we can use the time that people have bought back by employing generative AI to perhaps, I don't know, explore new products? Yeah, you know, level up the products that they have. All the creativity that can come out by using the time that they've saved.

[Marcus]

That appears to be a huge concern, doesn't it, that if I use AI and I make my job more efficient, then I'll need less time to do it, which means that maybe they could get rid of me and have someone else do what's left of my job. There was some research on this, actually. Few workers think AI use in the workplace will improve their job prospects in the long run. 32% of people expected to have fewer job opportunities, 6% expected to have more. And interestingly, that was both AI users and non AI users, both appearing to be pessimistic. If you looked at non AI users, it was a 6 to 1 ratio in terms of people who think that they'll have fewer job prospects versus more. And if you look to AI users, it was 3 to 1. So it's still concerning for both groups. You also mentioned that people maybe haven't realized the true potential of it yet. It's not enough to just use it, is it? There has to be kind of that light bulb moment where, oh, this is how it's going to help, because, which is a lot further down the road. There are still a lot of people who aren't using this technology even, and people maybe not realizing its true potential because they just haven't used it. Pew study, 61% of people aren't using it much, if at all. And a further 17% haven't heard of workplace AI use. So this is still very new. And we've just got to get more people, I guess, using the thing before they can be more comfortable with the thing, before they can realize how the thing can help them for sure.

[Henry Powderley]

And then how are companies going to help them find the time to be exploring these texts? I think that's a real big part of it.

[Marcus]

Yeah. So, I mean, that leads me to another point here, which is the Training piece folks aren't, it seems, being trained on its benefits. Of all workers, this Pew study, 12% said they'd taken a class in the past year related to AI use. Just 12%. And there was a one Ranstead study showing that about 35% of employees, so more had received AI training in the past year. However, that's 35% trained on it, 75% of companies adopting it. So there's a big chasm between people using it, people really understanding the benefits of it, and having the time, I guess, being taught and being allocated time, the time to really understand how it could impact people's jobs.

[Garjo Sevilla]

I think that's really the big issue because there's the initiative to adopt AI, but there's also the implementation piece.

[Henry Powderley]

Right.

[Garjo Sevilla]

And part of that is not just subscribing to Chatbots, it's also training. And some companies are falling short on the training aspect while demanding that employees are up on the latest technology.

[Marcus]

Right.

[Garjo Sevilla]

But less than 40% of the workforce say they have access to gen AI tools. Right. And less than 60% of those employees engage with it daily. So I think access is a huge. Yeah, it's a huge problem to solve there.

[Marcus]

Yeah.

[Garjo Sevilla]

And especially if you consider there are discrepancies because according to Deloitte, 29 of AI skilled workers are women. That's a small number considering there are limitations to what is available to them.

[Marcus]

Yeah, yeah. One third of workers paying out of pocket for Gen AI tools because their employer doesn't provide the ones they want. Half of knowledge workers, basically desk and computer people using personal AI tools at work. Some Nova survey that's from company Software Ag, and half of executives saying employees currently are left on their own to figure out Genai as from Genai Platform Writer.

[Garjo Sevilla]

There's a huge security issue with that though, when people start bringing in their own AI tools and subscriptions. Because if they're dealing with company ip, company data, I mean, what's the next step? Where are they putting that information? Where does that reside? Right. We know AI is constantly training to different degrees and putting very critical information out there might improve their jobs, but then also opens up up a lot of possibilities that are, you know, less than great for the company at large.

[Marcus]

Yes. So, Gaja, what's the argument that people will become more worried?

[Garjo Sevilla]

I think the argument, aside from maybe the lack of training and resources, is that, you know, we're seeing a point in time where there's so many AI tools that it's becoming increasingly more difficult to figure out which ones they need to be looking out for. Right. And so there's that. And at the same time, people who are using the tools are training the AI to handle their workflows. Right. So do they feel that they're actually training the AI to replace them? To some extent, yeah. You know what, what company can give a guarantee that? No, that's not the case. You should see this as an assistant, as a tool. It's not going to replace you. But, you know, if you look at the bottom line, for a lot of companies, they're pushing towards automation to sort of speed up and scale certain. Certain jobs. Right?

[Marcus]

Yeah. There are some numbers on that quickly. Workers noticing their jobs becoming more automated. 16% say at least some of their work is currently done with AI. A further 25% say whilst they're not using it much now, at least some of their work can be done with AI.

[Garjo Sevilla]

Yeah. So I mean that you can't help but consider that, you know, they see that and they become anxious about it.

[Marcus]

Right.

[Garjo Sevilla]

Because they see their jobs changing and at the same time they're seeing the AI get better at doing certain jobs.

[Marcus]

Yeah. So, Henry, I mean, before we move on to the next part of this, which is how it's impacting jobs, Gaj made a good point there. Which is hard enough to know what tools to even be paying attention to, especially if you're not getting that direction from the company, let alone how to use those tools. And you're someone who is an early adopter of AI use it, and you kind of understand it more than the average person. How do you pay attention to the right tools?

[Henry Powderley]

I mean, a lot of experimentation. I certainly play with a lot of tools personally that I don't use at work for the reasons that Gago expressed. I think security concerns, especially when dealing with company data or company strategies, shouldn't just be put into random tools without thought. And we do have a good process internally here for vetting tools, but it doesn't mean that I don't play with things in my. In my personal time to really explore what's out there. And then if I find something that's interesting that could perhaps help my team, I bring it to the folks here and we go through a process embedding it. We did that with a tool that we're using for copywriting right now, and my team called Spiral and I went through that process. So, you know, I do think that It's a catch 22.

[Marcus]

Right.

[Henry Powderley]

Because you want to be explor the options that are out there right now and I think standing in the way of that kind of curiosity is going to slow down adoption. But at the same time, companies got to be smart about setting policy that are going to reduce the risk of data being ingested by these language models. So there's a balance there.

[Marcus]

Yeah. Let's move to the jobs piece of this. Henry, what's the argument that AI is already having a significant impact on jobs?

[Henry Powderley]

Well, I mean, I think we wouldn't be talking about it if we haven't seen this kind of impact already. What's really cool about E marketers that we are always getting data about how the market is changing. And I was just looking in our own chart library to see and there was some interesting stuff there. I mean there was a survey by Nextiva from January that showed that 40% of respondents were using Gen AI for writing to customers. That is a big chunk of time. I saw physicians, physicians, almost a third of physicians are using right now AI for things like translating or even diagnostic help. And then, you know, there was another survey of retail CFOs by Raven Roberts research from February that showed that 34% are using gen AI for optimizing pricing strategies based on market dynamics. So I think the data is starting to come in to show that there's a lot of penetration with this tech. And there's also, there's downsides too. I think. There was a story in the Washington Post last week that showed that computer programmer employment dropping to its lowest level since 1980. You know, that's one of the areas where I think we're starting to see the effects sooner because of how well these tools are at coding. Just the recent update to Claude already has just given folks like me who don't really have a good coding background the ability to create things and program things. And you have to imagine for folks who are actually embedded in the programming work how these things are helping.

[Marcus]

Yeah. Matteo Wong of the Atlantic wrote a really, really good piece and he was saying that tech executives have kind of grown blunt about their hopes that AI will become good enough to do a human's work. In January saying Mark Zuckerberg quoting mark Zuckerberg saying 2025 will be the year when it becomes possible to build an AI engineering agent that's as skilled as a good mid level Engineer. And Anthropic CEO Dario Amodi recently said AI will be writing 90% of code A from now with, with some human specifications. But, but still continuing to say we, we will eventually reach the point where AIs can do everything that Humans can in every industry. Obviously he's someone who is at the forefront of that and believes that and that would be good for, for him and his company. But still the idea that people are openly talking about no, like this thing will be able to do this person's job or this level of a person's job this year is quite surprising. It seems as though it's also being talked about a lot in terms of not what your current job is, but if you're going to find another job, that is something that people are expecting you to have some kind of a grasp of and have some knowledge around AI experience starting to outrank job specific qualifications. Christine Kruz Vergara, Chief Education Strategy Officer at Entry Job level Platform Handshake says employees and our folks said they're willing to take chances on otherwise less qualified candidates if they have AI experience. So that becoming even more and more important, more so than knowing having experience in the actual field.

[Garjo Sevilla]

Going back to the coding part, it's interesting that, you know, at Google AI is coding 25% of their code right now. That was last year. I think that's probably going to increase. And that goes hand in hand with, with a lot of the investments they're making. Right. So they do have a 14% stake in anthropic right now. And that's precisely because of Claude's advanced AI coding capabilities. So, you know, they're not just drinking the Kool Aid, they're actually applying, you know, that knowledge, those transformations into their own business. And, and that should be interesting for anyone who's following how these companies are using AI internally.

[Marcus]

Yeah. So what's the argument, Gajo? That AI isn't already having a significant impact on jobs? Maybe we're exaggerating things, maybe we're getting a bit ahead of ourselves and it's a thing. We've been talking about it, but really the impact isn't that seismic yet.

[Garjo Sevilla]

Yeah. So I took this argument as a devil's advocate, although I do believe the opposite to a greater extent. But that said, I tend to look at it not just that AI isn't having a significant impact on jobs, but in certain cases it's having a negative impact in certain markets. So in the aspect, say of AI image generation and video generation, we're seeing a lot of AI slop, as I call it, which is basically just a lot of random AI generated imagery that's being pushed as being official or being pushed as prime content. And I think that's the danger there. It's an overuse of AI, but at a super unregulated level where the quality just isn't there just to sort of stuff pages with content and images. Right. So that could have a negative impact and kind of, you know, make consumers and anyone else kind of mistrust AI or mistrust what they're seeing.

[Marcus]

Yeah.

[Garjo Sevilla]

So, you know, in most cases I think that's the danger, that's the extreme. And to, to get back to why it isn't having a significant impact in, in some, in some areas or in some, you know, business models, it's, it's possibly because it's not being strategically rolled out, you know, as a proper tool. Right. And that's, and that's causing the lag in adoption, the mistrust and maybe, you know, it's the inability to kind of focus on, you know, we need this, this particular tool to help you save hours or improve customer service. It's something that a lot of companies are addressing, which I mean, I mean to say it's going to change, for example, once Adobe's agentic AI gets adopted at large. Right. Because they have specific tools, tools that cater to business use cases, just things like understanding the audience that you're trying to attract, content production, just speeding up the different steps towards that, helping creatives be more creative and less of, be less focused on production and also experimentation and prototyping.

[Marcus]

Yeah, yeah.

[Garjo Sevilla]

So, but all that takes time to adopt. So maybe it's not that it's not having a significant impact, but it's just taking longer.

[Marcus]

Yeah. I'll give kind of both sides of this in one answer, which is that if you look at kind of the new jobs that are being posted, it seems like AI skills are being increasingly sought after. So nearly one in four US tech jobs posted so far this year was called newly listed, if you will, asking for employees to have some kind of AI skills. It's from UMD Linkup AI Maps that shares even higher for specific categories, 40% for information related jobs, close to 30% for finance, professional services, retail, education, et cetera. Even manufacturing was at like 20%. They're asking for some AI skills, however that's newly listed. If you look at that, all jobs AI related listings represent just a fraction of the overall, the old and the new. I think it's about 1% of all job listings. So it does feel like we're being hit with this tidal wave of AI jobs or AI being listed in the job description of every job that you see now. But in the grand scheme of things, it's not as big, as significant as maybe we think. All right, that's where we'll leave part one of today's episode. Thank you so much to my guests for today. Thank you to Henry.

[Henry Powderley]

Thanks Marcus.

[Marcus]

Thank you to Gajo.

[Garjo Sevilla]

Thanks again.

[Marcus]

Thanks to the whole editing crew, Victoria, John, Lars and Danny. Thank you to Stuart who runs the team and Sophie does our social media. And thanks to everyone for listening into the behind the Numbers show. Any marketing video podcast made possible by Tracks. Sarah will be back Wednesday with the Reimagining Retail show and me, Gajo and Henry will be back Friday. Part two of Using AI at Work Our two part episode talking about how businesses are using it and some tips for using AI at work.