惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Vercel News
Vercel News
博客园 - 【当耐特】
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
小众软件
小众软件
Hugging Face - Blog
Hugging Face - Blog
aimingoo的专栏
aimingoo的专栏
WordPress大学
WordPress大学
G
Google Developers Blog
博客园 - 叶小钗
大猫的无限游戏
大猫的无限游戏
P
Proofpoint News Feed
J
Java Code Geeks
U
Unit 42
云风的 BLOG
云风的 BLOG
阮一峰的网络日志
阮一峰的网络日志
N
Netflix TechBlog - Medium
宝玉的分享
宝玉的分享
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
D
Docker
V
Visual Studio Blog
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
H
Help Net Security
V
V2EX
T
Tailwind CSS Blog

PYMNTS.com

Google Accelerates Agentic AI Shift With New Enterprise Platform DeFi Security Suffers New Blow With $3 Million Volo Exploit Uninvited Users Access Anthropic’s Mythos AI Model Block and Uber Expand Partnership Across Several Global Markets OpenAI Pledges $1.5 Billion to PE Enterprise AI Project Podcast: Inside the $9 Billion DeFi Hack That’s Shaking Crypto’s Foundations Synchrony CFO Flags Momentum in Spending and Credit Banks Risk Slowing the Emerging Middle Market Firms Driving Growth Paysafe Expands Digital Wallet Availability Across 18 European Markets Bad Data Can Break Good AI in Payments 50% More Digital Shopping Days Put Parents at the Center of Retail’s Shift 65% Call Insurance Essential. Why Most Spending Isn’t So Clear-Cut Amazon Recasts Marketplace Fraud as a Broader Trust Problem Capital One’s Q1 Shifts Attention From Spending to Strategy Lawmakers Question JetBlue About Surveillance Pricing Allegations Small Businesses Stop Chasing Amazon on Delivery Speed Google Embeds AI Into Chrome for 3.5 Billion Users Adobe Plans Outcome-Based Pricing for New AI Product Suite UnitedHealth Spends $1.5 Billion on AI and Wants Double Back MiCA Forces Crypto Firms to Get Licensed or Get Out Prediction Market Kalshi Targets Crypto Perpetuals New York Sues Coinbase and Gemini Over Prediction Markets Amazon and Anthropic Deepen Ties With Investment and Hardware Pact Commercial Loans Show US Economy Defies Sluggish Forecasts The Web Is Gaslighting AI Agents and Nobody Can Tell OCC Enters the Interchange Fight and Raises the Stakes Amazon Dismisses New Evidence in California Antitrust Suit AI Finds Its Best Customer on Main Street Coinbase Opens Services Marketplace for Agentic Commerce Feds Start Processing $127 Billion in Tariff Refunds for Importers
Podcast: AI Training Gap Scares the Wrong Workers
PYMNTS · 2026-05-12 · via PYMNTS.com

Here’s the paradox nobody’s talking about in the AI-and-jobs debate. The workers most afraid of being replaced are the ones least likely to be.

Knowledge workers, including analysts, copywriters and coders are squarely in artificial intelligence’s crosshairs. AI models can already draft their memos, crunch their spreadsheets and write their code.

According to new research from PYMNTS Intelligence’s Wage to Wallet collaboration with Ingo Payments and WorkWhile, it’s the roughly 60 million front-line and hourly workers in the Labor Economy who are losing sleep.

Only about 40% of these workers said they believe they could find comparable employment if displaced. Their confidence is, to put it diplomatically, in the basement.

The question is why. Ingo Payments CEO Drew Edwards and WorkWhile CEO Simon Khalaf said on the latest Wage to Wallet podcast with PYMNTS CEO Karen Webster that the answer has less to do with the technology and everything to do with how employers are (and aren’t) communicating about it.

The Training Gap That’s Breeding Fear

The numbers tell a stark story. According to the research, 37% of Labor Economy workers said their employer has already introduced AI or some form of automation into their workplace. However, nearly 60% said they received zero training on those new tools or workflows.

Advertisement: Scroll to Continue

Employers are deploying AI and then not telling workers how to use it. That’s not a technology problem. That’s a management failure.

Only 12% of firms said they are very prepared to manage AI-driven workforce changes. Most chief financial officers identified skill gaps as the primary barrier to adoption, alongside organizational complexity and resistance to change.

Workers are hearing a steady drumbeat of commentary about automation and job loss, and without context from their own employers, they’re filling in the blanks with worst-case scenarios, Edwards said.

“If you’re a worker and what you’re hearing… is that nobody’s going to have a job in five years, that is scary stuff,” he said. “But I don’t think anybody should be naive enough to think that the job you’re doing today is not going to be impacted.”

Demand for Human Labor Is Surging, Not Shrinking

Here’s where the disconnect gets interesting. Khalaf said the picture on the ground doesn’t match the doomsday narrative for front-line workers.

“We are seeing dramatic acceleration in demand for human labor,” he said, adding that utilization across his platform remains consistently high.

The AI being deployed in the Labor Economy isn’t replacing workers; it’s reorganizing how they work. It sits behind job matching, shift assignment and daily task management. It handles the scheduling spreadsheet (or, as Khalaf said, the paper timesheet that still passes for state-of-the-art at many companies). What it doesn’t do is pick up boxes, stock shelves or show up for the shift.

Khalaf offered a telling example from WorkWhile’s own operations. A small team supports tens of thousands of workers through AI-driven systems that provide instructions and manage workflows. The AI didn’t eliminate the workers. It eliminated the middle-management overhead that used to slow them down.

From Doing the Work to Directing It

For workers willing to engage, the shift is less about losing a job and more about gaining a different kind of leverage. Edwards framed it as a move from doing the work to managing the technology that helps do it.

“My experience… is it’s giving me an entirely new team to work with side by side with these people,” he said. “If you know how to give directions, you can build software.”

That’s a provocative claim, but it points to something real. AI tools are lowering the bar for what counts as technical fluency. The premium isn’t on coding or data science. It’s on communication and problem-solving, which are skills that front-line workers already use every day.

Trust remains fragile, however. Asking workers to rely on automated systems for their livelihood, especially in platform-based environments where the decision-making process isn’t transparent, is a big ask, Khalaf said.

Webster suggested that the antidote might simply be experience. When workers use the tools and see tangible outcomes, it stimulates their imaginations. Familiarity breeds comfort, but only if workers get the chance to become familiar in the first place.

The Bottom Line

The Labor Economy doesn’t have an AI problem. It has a communication problem. The technology is making front-line work more efficient, not more obsolete. But when 60% of workers get no training and only 12% of employers are prepared, the vacuum gets filled by fear. And the fear is hitting the wrong people.

“Let’s focus on training,” Khalaf said. “Let’s focus on reskilling our people so that they cannot fear AI. They can embrace AI.”

That’s not a technology roadmap. It’s a leadership one. And the clock is ticking.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.