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Tech Brew

Future of Work

Jordyn Grzelewski

techbrew.com

CEOs of some of the biggest companies in the US have been outspoken of late about the ways they believe AI will disrupt workforces.

“AI is going to change literally every job,” Walmart CEO Doug McMillon 

Ford CEO Jim Farley echoed those remarks at an event in Detroit this week.

“The efficiency and automation always rips through our economy. And it will take jobs away from all sectors of the economy,” he said, speaking at a summit Ford hosted called Accelerate the Essential Economy. “Listen to what the CEO of Walmart said this week.”

US Labor Secretary Lori Chavez-DeRemer, speaking at the same event, offered a more optimistic view on how the technology stands to affect US workers.

“I don’t think it’s a hollowing out of anything. I really think it’s just a shift change, no different than the industrial age, no different than the technology age,” she said. “We will adapt.”

US workers must not only adapt, but lead the way on AI adoption, Chavez-DeRemer argued: “Because if America doesn’t do it, another country will. And that’s what the president wants, is to be dominant in AI.”

Chavez-DeRemer was one of dozens of government and business leaders on hand on Tuesday to talk about the “essential economy,” made up of roles like construction workers, electricians, and plumbers. In a 

, Farley pointed to a shortage of 600,000 factory workers and 500,000 construction workers in the US. One of the themes of the event was how to attract workers to these unfilled jobs, especially amid an AI-fueled data center boom.

“The narrative for the last 30 years has been, ‘Go out and get that four-year degree,’” Chavez-DeRemer said. “But to counter that 30-year narrative, now, for people to understand that there’s pride in building back America, that’s what this administration is doing. And so my part of the…equation is to make sure that we’re upskilling and reskilling the American worker, and letting businesses know that we’re here to help.”

Chavez-DeRemer touted opportunities in the skilled trades, like well-paying jobs, in addition to efforts by the Trump administration to support training programs. The Department of Labor recently awarded $86 million in grants to 14 states to support investments in skills training programs.

“We are not here to displace the American workforce at all,” Chavez-DeRemer said, “but we want to give them the tools so that they can be proficient and literate to move along with what is here to stay.”

 about the ways he believes AI could disrupt the white-collar workforce in the US, but said he sees 

 for blue-collar workers to benefit from the tech’s growth.

“When I look at the AI solutions that get pitched to Ford, they’re all about white-collar efficiency,” he said. “Very few AI companies come to us and say, ‘We want to dramatically help your efficiency repairing cars or your factory workers.’”

But it’s up to local communities, small businesses, corporate leaders, government officials, and other stakeholders to come together and make sure demand for “essential economy” jobs aligns with the workforce, he argued.

“We have to put some points on the board here,” he said. “And if Ford has to take the lead or other companies have to take the lead, if we have to sacrifice our short-term profitability to put more people in the workforce as apprentices, I think we’re going to have to.”

Lori Chavez-DeRemer, United States Secretary of Labor, spoke about the Essential Economy labor shortage at the Ford Pro Accelerate event on Sept. 30.

‘We will adapt’ to AI in the workforce, US labor secretary says

US Labor Secretary Lori Chavez-DeRemer participated in an event hosted by Ford on the “essential economy.”

Patrick Kulp

 recently confirmed what economists had already suspected: The labor market has not been doing so hot lately.

Whether that big summer hiring slowdown has anything to do with AI disruption is still somewhat of an open question, however. Some recent data suggest that the technology’s impact may be disproportionately hitting younger 

. Other reports aren’t clear on whether AI has much of a detectable effect.

“It’s very difficult to disentangle, you know, what is the impact of AI, compared to what is the impact of the uncertainty in the economy in general,” Columbia Business School professor Stephan Meier said.

Some recent studies on AI and jobs attempted to tease it out:

 from Stanford University traced a 6% decline in employment for early-career workers—those between the ages of 22 and 25—in fields considered most exposed to AI since 2022. Those jobs included software developers, customer service reps, and accountants. The findings are “consistent with the hypothesis that the AI revolution is beginning to have a significant and disproportionate impact on entry-level workers,” the economists wrote.

The above study was based on an analysis of ADP payroll data. ADP itself also issued a 

 a jobs slowdown in August, with “AI disruptions” pinned as one possible culprit for “whipsawed” effects.

Before too much panic sets in, however, other reports paint a different picture. A regional survey from the Federal Reserve Bank of New York 

 in the number of businesses using AI—40% this year versus 25% last year. But only 1% of firms had conducted layoffs driven by AI in the last six months, and just 12% of the companies using AI had hired fewer workers because of it.

 of the labor market released last month by the Economic Innovation Group found no meaningful impact on the labor market when it comes to AI. Unemployment among recent graduates has been “creeping up,” but not among AI-exposed jobs in particular.

If you don’t know exactly what to make of all of that, you’re not alone. Meier, who has been studying AI workplace transformation, told us that while AI will definitely automate some skills that are needed in offices, it’s unclear whether that will amount to offices needing fewer people overall: “That I don’t know yet,” he said.

It is plausible, though, that more of those replaceable skills might fall to entry-level employees, which would make it more difficult for young workforce entrants to get a foot in the door, he said. That would not only leave a generation with diminished job prospects, but also eventually harm the talent pipeline for companies.

“If you look at what positions within a hierarchy AI probably affects the most—or most immediately—it’s those entry-level jobs that are going to be affected probably sooner than later,” Meier said. “I’m not sure we see massive, massive effects of that yet, but we’re seeing the early signs that entry-level jobs are going to be affected.”

Meier said he is optimistic that the labor market will weather AI transformation in the long run with the creation of “new jobs, new industries, and new demand.” But in the shorter term, things could get messy as educational institutions and organizations struggle to keep pace with the change.

In that environment, it can be especially hard for young workers to set themselves up for a steady career.

“I see it with my teenagers—they’re as uncertain as everybody else, and obviously it hits them really, really hard,” Meier said. “When you just start a career and you don’t know what skill is going to be marketable, that’s scary. That uncertainty for sure creates a lot of anxiety. And I think organizations and society as a whole have to think about what to do with that.”

Close up of a briefcase with AI abstract connected lines displayed over the key lock.

Is AI actually hurting entry-level jobs?

It’s hard to tell.

Morning Brew Creative Studio

Many IT leaders (and business leaders in general) are being told about the importance of AI implementation. But when it comes to enacting those orders, the path isn’t totally clear.

Despite investments in cutting-edge AI tools and promising initiatives, IT teams often find themselves hitting a wall. The reason? It usually comes down to the foundation of their IT. Sprawling, disconnected ecosystems can silently sabotage new, innovative efforts.

 surveyed hundreds of IT leaders and uncovered a common paradox: While nearly every organization (99.6%) is exploring or implementing AI, a staggering 81% have 

The average company bounces between a whopping 9.3 different tools for core IT functions. That might just sound like commonplace inefficiency, but it can actually prevent businesses from completing meaningful AI transformation.

That’s why we teamed up with JumpCloud to create this roadmap for IT leaders—to give a clear view of the landscape and a clear route to the final destination of AI implementation.

Fragmented IT environments aren’t just inconvenient; they’re a strategic liability. The ol’ 

This disjointed landscape is a gateway to larger shadow IT burdens, increased security gaps (which were reported by over half of respondents in JumpCloud’s survey report), and escalating compliance risks. Not to mention that managing disparate systems diverts crucial IT resources. So instead of spearheading strategic initiatives, teams are busy doing reactive firefighting.

Added up, this all leads to slower processes, unreliable reporting, and a struggle to align tech with broader business goals. Yet despite the very well-known upsides of unification and downsides of fragmentation, JumpCloud found that only 19% of organizations report having 

—and 10% haven’t even started the process.

For many organizations, AI isn’t a future aspiration. It’s a reality right now. And the report’s data reveals a clear correlation between IT unification maturity and AI adoption maturity.

Of the leaders who have achieved IT unification, more than 80% actively use AI-based tools already. This is in stark contrast to their less-unified counterparts, who are mostly stuck in piloting or planning stages.

But once unification happens, there’s a direct connection to improved AI outcomes. 73% of fully unified organizations report enhanced AI model performance, compared to only 55% of those in early-stage unification. What’s more, unified teams are also involved in 

, which can be good for both operations and optics.

Of course, AI systems do raise security concerns, but unification helps balance those concerns. A mere 14% of unified organizations associate security risks with AI tools, significantly less than the 33% seen across all organizations. This is likely thanks in part to the ripple effect of unification—increased data quality, clearer integration, and a stronger understanding of security challenges posed by AI.

In today’s challenging economic environment, IT budgets are under intense scrutiny, but there is one upside: Rather than being a blocker that stalls innovation, these pressures are accelerating the demand for strategic IT modernization.

The focus is shifting toward cost optimization, increased investment in automation, and smarter software procurement. JumpCloud’s report found that the top strategic priority for IT leaders over the next 12 months is 

, closely followed by improving user experience and consolidating IT tools.

This makes sense, given the cost of being disconnected. 46% of disconnected organizations report delayed or canceled IT projects due to economic conditions (nearly double the overall average of 25%). These numbers make a clear case for unification as both a technical upgrade and a financial imperative for business continuity and competitiveness.

So, where can IT leaders go from here to reach their AI destinations? Start with breaking down silos. Simplify your IT environment by consolidating disparate tools into a unified platform. From there, automate as much as you can and liberate your team from repetitive tasks so they can focus on higher-value work.

On a more macro level, zoom out and look for ways you can elevate IT’s strategic role in your organization. Improve your collaboration with other departments and hitch your IT initiatives directly onto the business-goals bandwagon.

But perhaps most importantly, it’s crucial for IT leaders to embrace the hybrid reality. Rather than rely on a single vendor to maintain a complex environment, consider a unified platform 

 that can seamlessly manage diverse endpoints and productivity suites. It helps ensure security and efficiency across your entire ecosystem.

A central silhouette of a user, overlaid with fingerprints, a password field, floating phone and laptop devices, conveying protection and security.

JumpCloud

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 IT leaders, use this roadmap to unlock value from AI in your organization 

Learn about the paradox holding organizations back from AI transformation

An IT leader’s roadmap to unlocking AI’s strategic value 

AI is everywhere on LinkedIn these days, from the company’s own hiring and search tools to the buzzy terms du jour that populate job listings and the monologues of aspiring thought leaders.

But does it prevent the sometimes isolating and disheartening experience of searching for a job? We spoke with LinkedIn’s chief product officer, Tomer Cohen, about how his team builds AI tools aimed at making those matches easier. Cohen said AI is helping to surface jobs that might not otherwise be seen in traditional search.

The Microsoft-owned company announced this week that it’s making its first AI agent, a hiring assistant for recruiters, globally available later this month, after an early-access period with select customers like SAP, Wipro, and Siemens.

Cohen also discussed the ways AI is changing the job market and how the company organizes its many agents.

This conversation has been edited for length and clarity.

There are all kinds of thoughts on what AI means for jobs right now: Anthropic CEO Dario Amodei has said AI is going to 

 half of white collar jobs. People worry that AI is 

 entry-level workers. How much of that are you seeing bear out in the view you have into the platform? What is the biggest impact you’re seeing?

There’s no doubt that AI is basically reshaping jobs and roles. I think “jobs” tends to be not the right lens to look at. I think “skills” is probably the best lens, because what’s happening with AI is that AI is basically automating the repetitive, low-leverage tasks that we all do, especially for knowledge work. So everything from drafting to summarizing, scheduling, searching. And we allocate roughly 30% of hours currently done within the US economy [to those tasks]. So those skills, you should expect to basically be automated. Now, if your role is mainly those skills, then that role might no longer be necessary. But for many roles, those tasks are just a part of the role. So then you ask yourself, “OK, what are the next level of skills required?” And that’s really about, like, “OK, how do I work with AI better? How do I kind of shape AI to the needs of my company?” This is where you’re seeing the notion around AI fluency, AI agency. Do I know how to bring in a lot of great AI tools and know how they all work together? And that’s where we see that new role emerging and becoming really, really powerful.

There’s the question around early career talent, and that for us is something that we’re investing [in]. So internally, we recently launched the Associate Product Builder program, which is really built around AI fluency and agency, to basically invest in early career talent. But you can see that kind of broad spectrum around, “Do you have a growth mindset? Do you have AI fluency? Do you have AI agency? Are you able to be fluid with the changes of your role?” all the way to, “How do we invest in early career talent to be able to kind of groom them into those roles and that pace of change?”

Do you have ways of measuring jobs that are getting surfaced by AI tools that wouldn’t have otherwise been widely seen?

You can think of those as the long tail of jobs, in many ways. Some jobs appear in all the searches, but it’s mostly because people don’t share a lot. They’re like, “I want a marketing job in my area,” and there’s the ones that most people apply to. But if I know more about your skill set, your aspirations, there might be a job that actually not many have applied to, but is a great opportunity for you. So instead of a lot of job seekers applying to a few jobs, which, by definition, will create dissatisfaction, you’re able to actually spread out the supply and demand, so there’s a better satisfaction on both sides of the marketplace.

Everybody knows that job seeking can be a slog. You have to send out a ton of applications and never hear back from most of them. And on the other side, hiring managers are flooded with irrelevant applications. What’s your ultimate vision for what the job search should look like in the future once all this AI is implemented?

When we look at the job market right now, it’s very tight. So applicants per job, if you look at two years ago versus now, they grew by 20%, so you can clearly see that there’s more applicants per job than there were before, and that gets tighter and tighter every year.

I spend a lot of time with job seekers, whether it’s in research or interacting with them—it’s a very lonely experience. It’s not rare for somebody to cry in those sessions when they share about their experiences, because it’s very emotional. They don’t even feel comfortable sharing with their partner how stressful it is.

And I think our job is really kind of taking you all the way through this journey and really making sure you feel confident you’re getting matched with the right jobs, and we really take you all the way to the job and not just provide part of the value. So anything from when you even think about something you might want, you come to our job experience and just talk about it, just say what you’re after.

Then we’ll present jobs to you, but we’ll also present what is the right match for you. It’s very deflating when you apply to a job that you have no chance of hearing back from. Or, to my point, before, the supply-demand is completely imbalanced. So really being able to provide you with jobs that might match you really well, but also the supply-demand is actually really balanced, and there’s a higher likelihood of success there.

Then it doesn’t stop there: We help you with our AI agent. We help you write the resumé well, for that job, so you can emphasize the right skills. The AI agent helps you craft a cover letter for that job. And right now, we’re actually in the process of launching an interview prep. So you can do interview prep one on one with an AI coach. The goal for us is to secure you all the way from the moment when you’re like, “I could use a new opportunity,” to securing an opportunity. And then if there’s a job that you might really want right now, but on the skill set, the job match was like, “Hey, you’re missing this type of skill. You’re missing running Google Ads.” Then we actually have a course that can help you learn Google Ads so you can take that course and feel much more confident. So before you walk into the interview, you’ve kind of sharpened all the skills you need to be able to demonstrate to your future employer.

We use a mix of models. We work on Azure and OpenAI, but we also use Llama for some [things] and again, we use them primarily as base models. And we have our own smaller models fine-tuned, but it’s really the work we do on top that creates the value of what the member sees on LinkedIn.

As you build out more of these AI agents, how do you think about organizing them?

For us, we see it as necessarily the application you use. So if you are recruiting using our recruiting products, then basically, for you, there’s one agent that takes care of the job. Now, behind the scenes, there’s actually a lot of mini agents taking smaller tasks and doing a proper job there, but it’s completely masked for the customer, for the user; for them, there’s just one agent they’re working with.

Same on the marketing tools, same on the selling tools. When it comes to our flagship experience, the LinkedIn.com experience, it is one unified experience across the board. And the goal is to basically escort you, so whether or not you saw something great on the feed and you want to have a conversation about it, but then when you think about potentially a new job to apply to, we’ll connect the dots for you, so you can see one unified relationship you’re building.

Can AI make the job search less grueling?

We asked LinkedIn’s chief product officer.

AI agents may be making more headway in tech headlines than in actual offices.

That’s according to the latest adoption report from accounting firm and consultancy EY. It found that while 34% of the 500 senior business leaders they surveyed in April said they’d begun to try out agentic AI, only 14% had fully implemented generative 

 that can act beyond the realm of a chatbot.

The biggest barriers holding back adoption were trust and safety. When it comes to handing over the reins of back-office functions to autonomous systems, respondents said they were worried about the cybersecurity implications (35%), data privacy headaches (30%), insufficient regulation (21%), and lack of company policies (21%). Nearly two-thirds (64%) said they think fears of AI replacing humans will prove an obstacle, though only 24% reported employee resistance as a barrier.

 Many of the business functions agents are currently tasked with are more marginal than what EY’s report authors think they can handle.

Agents are doing things like “assisting/ or managing processes,” “assisting tasks,” and “managing workflows,” respondents reported. But Dan Diasio, EY global consulting AI leader, said they should be doing more complex work.

“By their nature, agents are intended to autonomously complete tasks and even work with other agents, not merely assist or manage,” Diasio wrote in the report. “These activities are all useful, but they only scratch the surface of what’s possible. We’re talking about a step change in how work is done, not going a couple of steps beyond robotic process automation (RPA)-level tasks.”

Nearly three-quarters (73%) of respondents agreed, saying they can foresee agents managing entire business units. But nine in 10 said that built-in human intervention will always be necessary for agents in the wild.

“These statistics seem to contradict each other,” Diasio wrote. “This speaks to how we are both impressed with and intimidated by what we’re seeing from AI—how the technology forces us to reassess our own futures in the workplace and in society—as well as how many challenges on adoption persist, including just our own mindsets.”

EY’s report also found that 64% of companies are now focused on building out in-house AI capabilities rather than acquiring existing firms, an increase from 56% about a year ago. The consultancy found that 32% of AI investments were devoted to buying “solutions off the shelf”—not customized for the company—a drop of 6% from six months earlier.

Investment in AI seems to be continuing to tick upward; a little more than a fifth of respondents said their companies have now invested at least $10 million in AI, and 35% planned to hit this milestone next year.

EY Americas AI and Data Leader Traci Gusher wrote that the shift toward in-house may reflect how many enterprise platforms are already building in AI features, making purchases of off-the-shelf solutions redundant.

“Buying a separate solution in the market off the shelf may seem unnecessary,” Gusher wrote, “and building a custom tool, to differentiate from the sea of sameness, may in turn feel imperative.”

An employee at an office desk with mouse clicker arrows pointing in different directions with highlighted text boxes. 

Trust is the biggest obstacle to adopting AI agents, EY finds

Business leaders are concerned about cybersecurity, data privacy, and lack of regulation.

 are a natural use case for coding. But how do developers actually feel about the technology that’s shaking up their jobs?

Stack Overflow asked 49,000 of them in its annual survey, and found some mixed opinions. Adoption was indeed growing; around 84% used or planned to use AI in their development process, compared to 76% last year. But positive sentiments were in decline (70% → 60% favorability), while mistrust in its accuracy was on the rise (31% distrusted it in 2024, whereas 46% were skeptical this year.)

Only about 31% of developers said they used agents at least once a month, but around 38% said they had no plans to start doing so. A little over half of those who use them said agents have had a positive effect on their productivity.

“We know more developers are using AI tools, but they’re not having exactly a great experience using those tools,” Erin Yepis, senior analyst of market research and insights at Stack Overflow, told Tech Brew. “There’s more developers that have the ability to try it, and maybe their expectations aren’t exactly where the reality lies.”

 As far as what’s holding back agentic adoption, developers identified accuracy and security or privacy concerns as their biggest problems with these more autonomous systems.

“One of the top frustrations that developers have is when the AI code isn’t quite right, they have to spend more time sort of debugging the thing that’s supposed to help them save time and get work done faster,” Yepis said.

 about declining employment in the tech industry, most developers (64%) said AI is not a threat to their jobs, though that number decreased slightly from 68% last year. Yepis said the survey might be showing that developers are becoming a bit more hesitant about the way AI coding tools are changing their workflows.

“There are just a lot more tools out there now, and I think [they’re] becoming a little bit more wary, as far as, ‘Maybe part of my job is going to change—what part of the job? What is it going to look like in three to five years?” Yepis said.

Developers responding to the survey seemed to overwhelmingly reject the term “

” to describe what they do; 72% said the loosely defined practice is not part of their development work. The term became popular earlier this year to describe a certain improvisational approach to AI coding, but the trend has also 

. For the Stack Overflow survey, the vibe coding question offered open-ended responses and drew many strong opinions, Yepis said.

“Whether it’s just that the term itself is off-putting or not, I thought that was interesting,” Yepis said. “There’s passionate responses when it comes to developers and their jobs.”

A set of hands on a keyboard with AI code overlaid

Most developers aren’t using agents, but many who do find them useful

But a Stack Overflow survey also found that positive sentiment toward the tech has dipped.

No, it’s not a TikTok aesthetic that involves dressing like a spy: AgentCore is a new toolkit from Amazon’s cloud arm designed to help companies build and deploy 

 in AI, companies everywhere are itching to 

 to full-fledged production can be daunting.

Amazon Bedrock AgentCore is the latest in a 

 of new products from tech giants aimed at easing that process. The platform has tools for managing memory, observability, helping agents access other digital services and the web at large, running generated code, and coordinating between agents.

Amazon announced AgentCore, along with a new agent marketplace and a 

, at its AWS Summit in Manhattan last week.

“There are a bunch of missing pieces that make it really difficult [to] move from [proofs of concept] that are sitting in laptops to agents in real-world production use cases,” Swami Sivasubramanian, VP of AWS Agentic AI, said on stage at the event.

The hype around agents seems as strong as ever at the moment, and enterprises have plenty of choices when it comes to these kinds of tools. 

, and other tech companies have their own agentic builders for customers looking to delegate to so-called “

Preethi CN, tech executive and advisor for agentic AI at AWS, told Tech Brew that one of the key things that sets AgentCore apart from this crowded field is flexibility. All of the component services are independent, CN said, and customers can “pick and choose” between them as needed. Companies are also not tied to Amazon’s own Nova foundation models; they can choose any of the catalog of models that Bedrock offers.

That kind of flexibility might be useful for a customer like Intuit, which has already built many of these agentic tools on its own through an internal tool called GenOS, according to Intuit SVP and chief data officer Ashok Srivastava. He said his team will explore these new AgentCore tools and decide if and where they might make sense for the new agents the financial software giant 

“When we built the agents that we launched a few weeks ago, a lot of these technologies weren’t available, and so we built our own,” Srivastava told Tech Brew. “As [cloud providers] build these capabilities out—if it makes sense—we can adopt them into our platform.”

Meanwhile, Amazon has also assembled an agent R&D lab in San Francisco built around its quasi-acquisition of agent startup Adept last year. The Amazon AGI SF Lab’s goal is to “develop new foundational capabilities for enabling useful AI agents that can take actions in the digital and physical worlds.”

Kelsey Szot, former co-founder and president of Adept, who’s now a member of the technical staff at the AGI SF Lab, said the lab is dedicated to research questions that lead to end results for AWS customers. The lab recently yielded a model called Nova Act, which powers agents to complete tasks within web browsers.

Szot said reliability has been the biggest obstacle for companies taking agents from experimentation to production—but that’s finally changing.

“Unfortunately, in the field, the last few years have seen a ton of demos and not a lot of real results of actual production deployments that are having business impact in the agent space,” Szot told Tech Brew. “It’s only now that we’re seeing the level of reliability that we need to actually make this possible.”