AI Has Freed Interns From Grunt Work. Now Companies Have a New Problem

Internships have long been considered a valuable steppingstone toward future full-time jobs, often because many companies hire people they previously mentored. But a number of recent workplace trends—notably increasing business deployment of AI tools—are creating new challenges for many younger apprentices as they seek to effectively learn the corporate ropes. Frequently, those changes are leaving interns with little or even none of the administrative grunt work they’d been traditionally given, and which AI applications have now automated. Even if that sounds like a good thing, it can strand many trainees in what business consultancy Korn Ferry called “a new kind of boredom.” In an effort to respond, companies are now assigning novice workers weightier workplace responsibilities they haven’t been trained to assume and are often terrified to take on. Consider it a feast-or-famine scenario for post-AI workplace apprenticeships. Under it, the workflow management and decision-making skills interns previously learned through repetitive and boring administrative tasks are being swapped for far more consequential roles usually reserved for more seasoned employees. “Thanks to AI, the drudgery that typically accompanies an internship—data entry, report drafting, meeting tracking—is being replaced by a different kind of cognitive burden that requires more fact-checking than judgment or critical-thinking,” a Korn Ferry blog post on the change said. “Companies expect [interns] to arrive fully proficient in AI so that they can spend more time developing their problem-solving and other human skills.” Unmentored interns The problem with this shift isn’t merely the bigger risks and higher costs of trainees stumbling while making decisions previously reserved for experienced staff. Interns may also lack the ongoing supervision they’d previously benefitted from, in part because of the effects of now common remote working arrangements or the manager-depleting effects of hierarchy “flattening” strategies. Indeed, a survey by the National Associations of Colleges and Employers (NACE) found nearly 20 percent of 2025 interns said they didn’t have a mentor, “which is a key anchor point to and sounding board for an organization.” Having a mentor is also critical in preventing trainees from being too terrified to make the decisions they’ve been assigned, or making costly errors after plucking up that courage. Alternatively, in many cases where workplace mentors were either never or infrequently present, novice workers were told to carry out work using the same AI bots that had already automated the administrative tasks earlier generations fulfilled. A far duller form of that came with younger trainees being instructed to monitor output of those apps—essentially an updated form of earlier grunt work that now keeps watch for slop the tech produces. Why should the shifting skills and experiences interns are learning be of concern to employers? According to Korn Ferry, a big reason is that companies frequently recruit the same young people they’ve helped train. Its post said last year that fully 63 percent of former interns received a full-time job offer from either employers they apprenticed with, or other companies that appreciated those training efforts. Fully 89 percent of businesses say they rely those programs on to identify future full-time employees, with NACE data showing nearly half of internship veterans received at least one employment offer before graduating from college this year. Internship programs need a big AI update Meanwhile, the size of the talent pipeline is huge, with an estimated 3 to 4 million people interning for U.S. companies each year. That flow of trainees is becoming an even bigger recruitment focus for businesses, now that AI has eliminated many traditional entry-level jobs for college graduates don’t have similar hands-on experience. But as important as internship programs have become, employers need to revise and refocus them in order for both youthful participants, and the employers themselves, to continue getting maximum benefits from them. With apps and AI replacing the administrative tasks trainees previously performed, businesses must find a middle ground between the contrasting alternatives many have adopted in the post-AI era. That means enriching roles situated somewhere between vetting chatbot output for slop, and the often terrifying responsibility of making decisions typically reserved for managers. “Firms are going to have to be more deliberate about teaching and coaching the skills they actually want interns to develop,” Mark Royal, a Korn Ferry senior client partner who specializes in employee engagement, said in the blog post. That means employers should focus less on the immediate, pragmatic concerns about assigning interns whatever work remains available that AI hasn’t taken over yet. Instead, they need to aim for the longer, strategic objective of identifying the tasks, experiences, and roles that will shape the kind of young workers they’d be eager to hire as employees. “Internships aren’t really about the output,” said Jerry Collier, leader of Korn Ferry’s EMEA assessment and succession practice. “They’re supposed to be about developing people.” BY BRUCE CRUMLEY @BRUCEC_INC

Apple Finally Fixed Siri—and It May Be Your New Favorite AI Tool

Apple’s Siri is the OG personal AI assistant. It debuted so long ago that the entire class of these voice-activated systems has been renamed “chatbots.” Siri, which launched as an integrated service on Apple devices in 2011, was useful for basic hands-free stuff—it could set timers, add calendar entries for business meetings, tell you awful jokes, even play music on request. But despite being improved gradually through the years, it remained limited. When ChatGPT arrived in 2022, Siri looked outdated overnight. Apple promised a dramatic revamp of Siri in 2024, but blundered through the process, earning Apple some rare media bruises when it was slammed for its failure to deliver. But now the new Siri—also known as Siri AI—has finally arrived, ready for public consumption. And boy, was it worth the wait. For many tech-wary execs, it may even become the AI that you interact with most often. What can Siri AI do? Available on newer iPhones, Macs, and even Apple Watches, Siri is now a true chatbot like many others, but it makes the most of being integrated into Apple’s devices in ways that rivals like ChatGPT or Claude can’t beat. Apple’s own blurb explains that new Siri will be a “truly helpful AI that’s centered around you and your needs” because it’s “integrated into your apps, grounded in your context, and private at every step.” It works across lots of different aspects of your phone or computer, so you can ask Siri to show you photos from a finance meeting in Berlin in one request, text your partner in the next, and finally ask it to create a summary of a document so you can quickly give your PR team some guidance. There’s no need to leap between apps manually—you can just activate Siri and make these kinds of requests whenever you need. Reviewers have pointed out that though Siri is now comparable to market-leading AI chatbots like ChatGPT, it has some quirks. It may come across as a little more serious-sounding than ChatGPT, and you can’t interrupt its replies in the way that you may be used to with OpenAI’s product. You probably won’t rely on this general-purpose chatbot to write lots of high-end code for you either. Specialized AIs are still going to be better for developers. Why should you use Siri more now? Because Siri can now process natural language requests, you can task it with more sophisticated duties, including useful prompts like “set up a regular Monday meeting with Miriam and add it to the calendar.” You should also be able to ask it the kind of “why does X work the way it does?” questions that you may have asked of other AIs if you need to quickly learn something new. And because it’s built into Apple’s devices, you don’t even have to touch the keyboard or screen to get the chatbot’s attention—the classic “hey, Siri” request still works. That means the AI is just a second away anytime you need an answer or a quick digital task completed. Essentially, Apple’s made Siri a hundred times more useful than it was before, both for home tasks and many workplace-centric duties. Siri and privacy This is where Apple’s devotion to user privacy may pay off. We’ve all read reports of how chatbots can leak sensitive information that users type into it, and noted the horrifying percentage of workers who blithely share confidential company secrets like financial reports with these third-party companies, not caring a bit about the legal ramifications. Companies like OpenAI and Anthropic also use your prompts to train their future models, and you may have let them do this without even being aware. Apple promises Siri won’t do any of that. Much of the new Siri service works on your devices, so nothing gets sent off to a distant digital cloud. And when your AI queries do need this extra compute power, Apple handles it so that the cloud data isn’t kept or associated with you. Siri is “aware of your personal information without collecting your personal information,” Apple promises. For many executives, this will be a key selling point. And for some companies, Apple’s privacy rules may allow use of Siri AI on company hardware in ways that have been banned or restricted for employees until now. The reviews are good Because Apple also places a premium on making its services simple and easy to use, MacWorld suggested that the new Siri is like “ChatGPT for people who hate AI.” The reviewer noted it was “dependable for quick questions, digging up personal data, and controlling your iPhone,” remarking that it was a little more simplified than more established chatbots. A reviewer on tech news site The Verge explained that “Siri AI is already changing the way I use my iPhone,” noting that “it’s practically stopped me from opening my browser for most things, since it’s easier, faster, and more enjoyable” to engage with Siri, either by voice or by swiping down on the phone’s screen and typing in a query. Even many commenters on Reddit, often a critical and snarky bunch, have been largely positive in a thread about the new Siri. One said: “It’s amazing. For everyday queries I haven’t touched the ChatGPT app in days.” Another wryly referenced some of the supply, trust, and pricing woes affecting rival chatbot makers by remarking: “Apple is the only company not in an AI crisis.” Important things to remember about the new Siri While Siri is now publicly available, it’s only as part of a beta OS release for Apple’s devices—and not all older devices can power the advanced services the new iOS and Mac software offers. You’ll also have to put up with the occasional bug while it’s still in testing. And while Siri AI is free, to access some of the more powerful cloud compute features you’ll need to subscribe to Apple’s services. There’s also a waiting list to activate Siri AI, but in my case, the waiting period was less than half an hour. Interested in trying out the beta release on one of your devices? Go to Settings on your iPhone, iPad, or Mac, then General, and under the “Software Update” heading, find the options list and select “iOS 27 Public Beta” for your iPhone, “iPadOS 27 Public Beta” for your iPad, and “MacOS 27 Golden Gate Public Beta” for your Mac. BY KIT EATON @KITEATON

A New Harvard Study Reveals Why Some Young Workers Turn AI Into Results—and Others Don’t

When people talk about AI and entry-level jobs, they usually fret about the threat the tech embodies to workers just starting to climb the career ladder. But while these youngsters are noted for being tech-savvy, and are often relied on for their skills as the first “digitally native” generation, many are reportedly deeply skeptical about AI. When you look around your workplace, you’ll see some who are excelling at leveraging it to make their job faster or better, while plenty more are struggling. New research in the Harvard Business Review may help you get a handle on this and bring all your young workers up to the same speed. The new study centered on why some junior staff seem to do so well when using AI to further a company’s goals, and yet others don’t. It turns out the best differentiator between young workers who excel at using AI and those who don’t isn’t the individual AI skills the workers have. Instead it’s more about how each worker tackles their tasks that matters. This runs counter to all sorts of narratives about AI literacy levels and what specialties young workers bring from their higher education. Some young workers, for example, have the AI skills but fail to use them in a way that delivers value for their employer. Others can appear competent, because they know how to rely on AI’s core systems to get to a deliverable answer, but they’re actually hiding their foundational business knowledge weaknesses. Meanwhile, here’s what sets successful young AI users apart: According to the study, the best users combine their “strong domain knowledge, critical thinking, and AI literacy” into every step of using AI to complete a task, including initial queries, shaping the outputs, and then delivering the required product. It’s a holistic skill, rather than a collection of shallow abilities. The business researchers note that it makes perfect sense for business leaders to prioritize hiring entry-level workers for their critical thinking skills and AI literacy. But because their study found “employees with similar levels of foundational skills and knowledge can generate dramatically different outcomes when working with the same AI agent,” savvy companies may rethink this policy. The problem is that being AI-savvy isn’t the same as knowing how to use an AI tool to solve a tricky business problem. Here’s what you can do The study suggests that company leaders keen to get all their young staff using AI in the most productive way possible should worry less about what their workers know, and instead train them in a way that emphasizes “how employees frame problems, interrogate AI outputs, refine results, and integrate insights into decisions.” Essentially, instead of taking it on trust that your Gen-Z and Millennial staff know what they’re doing, you need to actually teach them best practices. This involves leading them step-by-step through prompting an AI with first thoughts, evaluating its replies, tweaking what they’ve asked it, and incorporating the output into meaningful products. Then, when you give them an AI tool to use, it should translate into more meaningful impacts for your company. There’s another piece of advice: The researchers say companies should treat AI learning as “an ongoing development model rather than a one-time training intervention.” This probably holds for training older employees, too. Personalizing this training to plug up an individual’s skills gaps is an even better idea. And to really nail the solution, companies could actually embed AI learning into the tasks and decisions that workers face each day. Why all this matters AI boosters promote AI as being able to save companies time, effort and money—no matter what individual AI tools are designed to do, they all have this overall goal. These promises are why this tech is ubiquitous. But you can’t just “fire and forget” AI, nor can you assume that Gen-Z workers will just immediately master the tech, in the same way you wouldn’t trust them to run your PR office just because they’re already proficient with using TikTok or Instagram for fun. You need to train your young workers on an ongoing basis, ensuring that you work out where they’re strong and weak on knowing how to use AI in an impactful way, and plugging gaps through learning. The same goes for older staff too, especially if you’re hoping that the young Gen-Z whippersnappers will help drag your Gen-X workers into the AI era. BY KIT EATON @KITEATON

AI is making your life more expensive. Here’s how

AI is raising prices for Americans – and not just electricity bills. Major technological innovations carry the potential to transform economies by creating opportunities, jobs and even new industries while supercharging productivity and growth. However, that promise of longer-term gains often is preceded by short- and medium-term pain. In the case of artificial intelligence, that has included job losses, slower wage growth, widening wealth inequity and, especially in recent months, higher inflation. Recent data shows that the gargantuan interest and investment in AI adoption (estimated to be around $750 billion for this year alone) have pushed a variety of prices higher, lifting overall inflation in the process. “The higher inflation means that households must spend just over $375 more to purchase the same goods and services as they did this time last year due to AI’s inflationary impact,” Mark Zandi, chief economist at Moody’s Analytics, wrote in an email to CNN. The good news: AI is still just a minor contributor (an estimated 0.2 percentage points) of overall inflation, and the impacts are currently limited to a handful of categories. But the not-so-good news: AI is pushing inflation higher and further compounding longstanding affordability concerns in the process. Plus, these price pressures aren’t expected to go away anytime soon, and they very well could broaden. That potential dynamic has Federal Reserve officials, including the central bank’s new chairman, on alert. Here’s a look at where AI has already shown up in inflation and where it could crop up next. Electricity AI data centers can have voracious appetites for energy (notably electricity and water), and the rapid expansion of these monoliths threaten to strain grids and drive prices up further. That’s largely because demand is outrunning supply. Data center facilities can be built or expanded at double or triple the pace of new electricity generations systems needed to serve them, PJM Interconnection, America’s largest grid operator, noted recently. Combine those needs with retiring coal plants, increased electrification needs, extreme weather and aging infrastructure, and it further widens the gap between supply and demand. “Data centers are demanding huge amounts of power, and that’s tending to crowd out the electricity available to distribute to residents; it’s also led to wholesale electricity prices being bid up, because data centers are willing to pay the price that providers ask them for, and that ends up also raising the prices for residential electricity costs,” Pooja Sriram, US economist at Barclays, told CNN. US Consumer Price Index data shows that residential electricity prices rose about twice as fast in 2025 as compared to the average seen in years prior, she noted. And through the first five months of this year, electricity prices were climbing even faster than in 2025, Bureau of Labor Statistics data shows. “I think that is one of the clearest imprints of AI data center demand driving up residential electricity costs,” she said. Electricity prices unexpectedly fell 1% in June but continue to outpace overall inflation and are up 4% from a year ago, the latest CPI data shows. Memory chips The data centers’ appetites, however, aren’t fully sated with power alone. The massive buildouts also led to a surge in demand for memory chips, which has benefited manufacturers handsomely, Sriram said. “The issue is not just the demand; the issue is the supply side for those memory chips has been very constrained,” she said. The trillions of dollars chasing AI-related components now have storage and memory suppliers prioritizing their wafer-manufacturing capabilities toward high-bandwidth and high-speed (and highly profitable) memory products commanded by data centers, she said. “What that does has basically diverted (the production of) the memory chips that you need for consumer products toward very specific high-performance memory chips that the data centers need,” she said. The pricing pressures of these and other components have been most evident at the producer level. The Producer Price Index chart semiconductor and other electronic component manufacturing industry looks like a hockey stick. As of June, that category’s wholesale prices were up 26% from a year ago – a stark shift from June 2025 when prices were falling 0.8% on an annual basis, PPI data shows. “Why this matters for the end consumer is, at the end of the day, our laptops, computers, iPhones, iPads all have some sort of memory chip embedded in that hardware, and those chips have become quite expensive,” she said. Computer hardware and software Late last month, Apple hiked the prices for some of its most popular products by roughly 20%. In a statement, the company noted that AI data centers created an “extraordinary surge” in demand for memory and storage. Sony upped the price of its PlayStation console earlier this year, and Microsoft last month raised the price of its Xbox consoles by about 25% for similar reasons. “The entire consumer electronics industry is struggling with the current components crisis, but the effects are particularly hard on consoles,” Microsoft wrote in a statement. Computers and related hardware have typically been a highly deflationary product category in the CPI: Because of technological advancements, consumers can get more bang for their buck. (For example, a $1,500 computer in 2025 was likely more powerful than a $1,500 year-ago model, and as such, the BLS treats this as a price drop) For the first half of 2026, however, computers and related products have experienced price inflation, BLS data shows. “We’re in the early innings of these consumer price pressures and the pass-through from higher producer prices, higher import prices and greater demand, especially for AI-led investment,” said Gregory Daco, chief economist at EY-Parthenon. Adding AI features in business applications also affects the price of software. For example, Microsoft raised personal Office 365 prices by 43% in February (30% for a family plan) after keeping them steady for a decade. The new feature: Copilot, Microsoft’s new AI tool. Construction costs, wages Data centers also are impacting the supply of other key construction inputs such as copper and electrical wiring, as well as workers. “If you’re looking for data that was conclusive (about AI’s effect on the economy and inflation), albeit a bit more subtle, you would look and see whether wages in construction were going up more than wages in the rest of the economy,” said Thierry Wizman, Global FX and rates strategist at Macquarie Group. “Because if in fact there is upward pressure, straining resources of the economy because of the AI data center buildout, you would see it in wages as well – specifically in the wages of labor that would be working these projects,” he added. So far, the available national-level wage data is showing a “robust divergence” between the construction sector and the aggregate, he noted. Regional data could prove even more telling, he said, noting the importance of tracking construction wages in areas with a high concentration of data centers. (That will take more patience, however, as that more localized data is lagged due to collection and modeling needs). “We’re having a problem with housing in the country these days; people talk about it as being unaffordable,” Wizman said. “It could be the case that the fact wages in construction have been rising a lot is putting upward pressure on houses as well.” By Alicia Wallace