And here’s the thing: according to a new survey covered by Fortune, it mostly doesn’t pay off. Only 8% of workers said being available after hours won them a promotion.

So why do so many workplaces still run on it? And why is it Gen Z, the generation we keep being told lacks commitment, that is the first to question the deal?

What the new research on performative availability says

On November 2, Jeff LeBlanc, a lecturer at Bentley University, wrote a column for Fast Company titled “Gen Z is challenging ‘performative availability.’ Why aren’t Millennials and Gen X doing the same?” He defines performative availability as the compulsion to demonstrate commitment through visibility rather than through the value of your work, and he puts it plainly: “If you respond to a message at 9 p.m., you’re a dedicated employee.” That’s the unwritten rule he says too many workplaces still follow.

His column draws on a survey of 1,006 American workers from Software Finder, a software comparison platform. In that survey, 71% of respondents said they felt pressured to be available outside of working hours. The pressure was higher for Millennials and Gen X (72%) than for Gen Z (65%).

Then on November 8, Fortune’s Cordell Jones reported more of the same survey’s findings. 69% said after-hours availability has not meaningfully improved their careers. Only 8% credit it with a promotion and 12% with a raise or bonus. Meanwhile, 40% said it worsened their work-life balance, 38% said it raised their stress, and 32% said it worsened burnout. Workers the survey describes as “always on” were 2.8 times as likely as boundary-setters to report worsened burnout.

To be fair to the other side of this, the always-on group was much more likely to say availability helped them: 57% said so, compared with 8% of boundary-setters, and 17% of always-on workers credited availability with a promotion. And 49% of all workers said they worry that setting boundaries could hurt their careers. That worry isn’t irrational. Fortune also pointed to a 2025 study in which managers rated employees who unplugged after hours as more productive, but less committed and less deserving of promotion, even when their performance reviews were identical.

A quick honest note on the data: this is one survey from a software company, and the coverage doesn’t give much detail on methodology. I wouldn’t build a policy on any single number in it. But the pattern lines up with something much larger. Fortune notes that Deloitte’s 2026 Gen Z and Millennial Survey, with more than 22,500 respondents in 44 countries, found 48% of Gen Zs and 45% of Millennials saying they feel burned out.

Gen Z isn’t lacking commitment. They’re questioning the proof.

I hear some version of this in almost every session I run with leaders: “Young people just don’t want to put in the time.” I understand where that comes from. Many of us built careers in workplaces where being seen was part of the job. Answering fast was how you showed you were serious.

But look at what the data actually says. The group feeling the least pressure to perform availability is Gen Z, and the people LeBlanc says may be reinforcing the expectation, often without meaning to, are the Millennials and Gen X leaders now running teams. His conclusion is one I agree with: “It’s a managerial issue.”

That’s not a knock on Millennials or Gen X. It’s a knock on a system that taught all of us to use responsiveness as a stand-in for quality, because quality is harder to see.

In The Next Turn, I argue that this is exactly what’s breaking right now. When AI can produce a draft, a summary or a slide deck in seconds, effort and activity stop being reliable signals of value. Being online at 9 p.m. tells you even less. What leaders actually need to see is judgment: what someone decided, why, and what happened because of it. “The standards remain. The proof system changes.” Performative availability is an old proof system, and a lot of people are still paying for it in burnout.

And yes…. this is also why I keep saying “Gen Z is not the problem. Gen Z is the clearest signal.” When the youngest people in your organization push back on a norm, they are often just the first ones to say out loud that the value exchange doesn’t add up.

This starts long before the first job

I can’t write about this without thinking about schools. For years I’ve argued that we need to teach students when to connect and when to disconnect, and to talk with them about why. I wrote about it back in 2016 in The power of disconnecting. Disconnecting isn’t anti-technology. It’s a skill, and it’s one adults in workplaces are clearly still learning.

Here’s my question for schools: are we teaching students that the quality of their work is what matters, or that being responsive is? When a teacher replies to a student at 11 p.m., or a learning platform pings a kid on a Saturday night, what habit are we modeling? Our students are watching how the adults around them handle being always reachable.

Preparing students for their future, not our past, means helping them build healthy boundaries with technology and the confidence to show the value of their work, so they don’t walk into their first job believing a fast reply is the same as a good one.

What leaders can do this week

• Name the real after-hours needs. LeBlanc’s advice is to separate actual performance needs from performative expectations. Write down which situations truly require a response outside working hours. Everything else can wait until morning.
• Set and say team communication norms. Put them in writing. If you send messages late because that’s when you think, tell your team you don’t expect a reply until the next workday. Better yet, schedule the send.
• Audit what you praise. Look at the last few times you publicly thanked someone. Was it for the quality of a decision or a contribution, or for being quick and available?
• Make contribution visible. Give early-career employees clear ways to show their thinking: short project debriefs, decision logs, portfolios of work. If you want them to stop performing availability, give them a better way to be seen.
• Check your promotion conversations. If “always there when we need them” is showing up as a reason for promotion, ask what results sit behind it.

Frequently asked questions

What is performative availability?

Performative availability is the pressure to show you care about your job by being visible and reachable, such as answering messages late at night or on vacation, rather than through the value of the work itself. Bentley University lecturer Jeff LeBlanc used the term in a November 2026 Fast Company column.

Does answering work messages after hours help your career?

For most workers in a recent Software Finder survey of 1,006 U.S. employees, no: 69% said it hadn’t meaningfully improved their careers and only 8% linked it to a promotion. Workers who were “always on” were more likely to say it helped, but they were also far more likely to report worse burnout.

How should managers handle Gen Z employees who set boundaries?

Treat boundaries as a conversation about expectations, not a sign of low commitment. Be clear about which situations truly need an after-hours response, and evaluate people on the quality of their contributions. Clear expectations help every generation on the team, not only the youngest employees.

The bottom line

Being available isn’t the same as being valuable. It never was, but in a world where AI is changing what work even looks like, the gap between the two is getting harder to ignore. Gen Z just happens to be the first to say it out loud.

If your school or organization is working through how to lead across generations while AI changes how work happens, this is the work I do with leaders every week. You can find me at JeffUtecht.com.

So let me ask you: what does your organization actually reward, the work or the reply time?

Sources

• Gen Z is challenging ‘performative availability.’ Why aren’t Millennials and Gen X doing the same? — Fast Company, Jeff LeBlanc, November 2, 2026
• Gen Z pushes back on ‘performative availability’ as only 8% of workers say it won them a promotion — Fortune, Cordell Jones, November 8, 2026

The post Availability Isn’t Performance. Stop Rewarding It Like It Is. first appeared on The Thinking Stick.

Same researcher. Same general idea. Opposite outcomes.

Here’s the thing… if you only read one of those studies, you could write a very confident headline either way. Read them together and the story isn’t about the tool at all. It’s about design.

What the two AI tutor studies found

Jing Liu directs the Center for Educational Data Science and Innovation at the University of Maryland. According to Barshay’s Proof Points column, Liu wanted the two studies released together precisely to show that AI in education is neither all good nor all bad. I appreciate that. It’s rare to see a researcher put a positive and a negative result side by side on purpose.

Study one: a middle school math tutor. About 6,000 middle schoolers in Deer Valley, Arizona, used an AI math tutor called Goblins during the 2025-26 school year. It offered step-by-step help through text chat, a virtual whiteboard and spoken conversation, and could work in Spanish and six other languages. Students who solved at least two problems a week scored significantly higher on a year-end math test than similar students who used it less or not at all. Accelerate, the nonprofit that commissioned the study, estimated the 0.11 standard deviation difference at roughly three extra months of learning.

Important caveats, and the researchers say them out loud: students weren’t randomly assigned, so more motivated students may have both practiced more and scored higher. Accelerate is planning a randomized controlled trial. And only 6% of students used the tool for at least half an hour a week. Most of the use came through work teachers assigned.

Study two: a college course assistant. Before rolling out an AI course assistant to about 40,000 students, University of Maryland Provost Jennifer King Rice asked Liu to test it. In fall 2025, 15 of 30 professors were randomly assigned to add the assistant to their courses. It was available 24/7 inside Canvas and trained on the syllabus, readings and assignments. The result, written up in a randomized trial posted to EdWorkingPapers: about 1,100 students with the assistant earned lower grades than about 1,200 students without it, by an average of 0.11 points on a four-point scale. They also engaged less with course materials and were less likely to go to office hours or meet with instructors and peers. The negative effects were larger for first-generation students.

Only 15% of students in those classes used the assistant, and most asked it for answers rather than tutoring. Liu and Rice suspect the tool’s constant presence signaled that AI use was encouraged, which may have pushed students toward outside chatbots too. They are clear that they can’t confirm that.

AI tools “could exacerbate inequities in learning outcomes.”

Jennifer King Rice, University of Maryland provost, quoted in The Hechinger Report

Let’s give credit where it’s due. Maryland tested the tool before rolling it out to everyone, and then made the bad news public. That’s exactly what we should want from every school and university buying AI right now.

Here’s what the headline leaves out

If you’re someone who believes AI is making students lazy, the college study looks like proof. And I want to be fair here: it’s a randomized trial, it’s a real negative result, and the finding that first-generation students were hurt most should worry all of us. I’m not going to wave that away.

If you’re someone who believes AI tutors will finally personalize learning for every kid, the middle school study looks like proof. But it’s correlational, and most students barely used the tool.

Neither camp gets to declare victory. Also worth saying: these are different students in different settings, middle school math and college courses, so this isn’t a clean head-to-head comparison. What we can do is look at what was different about how each tool showed up in students’ lives.

In one, teachers decided when and how to use it, assigned the problems, and the district recommended it as a supplement, not the core. In the other, the tool was simply there, all day and all night, next to every assignment, and students were mostly left to figure out what it was for. So they used it for what most of us would use it for when no one has taught us otherwise… getting the answer.

That’s not a technology finding. That’s a teaching and design finding. I wrote about this back in 2009 in What’s the purpose of going 1:1, when schools were handing out laptops and hoping learning would change on its own. It didn’t then. Handing out an AI tutor and hoping won’t work now either.

This is why I keep saying, and why I wrote Human Still Required for school leaders: AI didn’t break school — it exposed it. If our courses already let students get by on answers, an always-on answer machine will expose that fast. The tool can explain, summarize and give feedback. Deciding what the learning is for, and designing the task so students actually have to think, is still human work.

The question is the skill

A second piece in The Hechinger Report this week connects right to this. Hiranya K. Nath, an economics professor at Sam Houston State University, wrote a Teacher Voice essay on teaching students to ask better questions. He asked his students to act as financial journalists and write three questions for a senior Federal Reserve official, and told them he would grade the questions, not the answers. Students who were comfortable explaining concepts hesitated. Others thought harder than they had all semester.

His point is that AI’s output depends on the quality of the questions we bring to it, so asking good questions becomes more valuable, not less. Two lines from his essay stuck with me:

“The tool does not define the problem. We do.” … “We are preparing students for a world of answers while they are entering a world of questions.”

Hiranya K. Nath, The Hechinger Report

Put that next to the Maryland result. Students who asked the assistant for answers got answers, and grades went down. That’s not a surprise. It’s what happens when we never teach the difference between asking for an answer and asking for help understanding.

Preparing students for their future, not our past, means teaching that difference on purpose. Their future includes AI tutors, AI assistants and AI everything. Banning the tools doesn’t teach that skill. Leaving them lying around doesn’t either. Teaching does.

AI tutors in schools: what to do this week

• Ask who decides when the tool is used. In the study with positive results, teachers assigned the work. If your AI tutor is just “available,” ask what students are actually using it for.
• Pilot before you scale, and measure it. Maryland tested before a 40,000-student rollout. Pick a few classes, compare, and be willing to share what you find, good or bad.
• Look at who is helped and who is hurt. The college study found bigger negative effects for first-generation students. Break your own data down by student group before you call anything a success.
• Teach the “help, not answers” move explicitly. Model prompts like “Don’t give me the answer, ask me a question that helps me find my mistake.” Have students reflect on how they used the tool.
• Grade a question. Borrow Nath’s idea. Once this week, assess the questions students write instead of the answers they give.

Frequently asked questions

Do AI tutors improve student learning?

The evidence is mixed. A study of about 6,000 Arizona middle schoolers linked regular use of an AI math tutor to higher test scores, but it can’t prove the tool caused the gains. A randomized trial at the University of Maryland found an always-available AI course assistant was linked to lower grades and less engagement.

Why would an AI tutor make grades go down?

In the Maryland study, most students who used the assistant asked it for answers rather than tutoring, and students engaged less with course materials and office hours. The researchers suspect the tool’s constant presence signaled that AI use was encouraged, but say they can’t confirm that.

Should my school stop using AI tutors?

Not necessarily. These studies suggest the design matters more than the tool: who assigns the work, what the tool is for, and whether students are taught to use it for understanding. Pilot carefully, measure results by student group, and adjust.

The tool was never the point

We’ve had this conversation with every new technology I’ve seen come into schools in my 27 years in education. Interactive whiteboards, laptops, tablets, now AI. The tool gets the headline. The design decides the result.

I’d love to see more schools do what Maryland did: test, measure, and share the results even when they’re uncomfortable. If your school or district is trying to figure out where AI fits, this is the work I do with leaders every week. You can find me at JeffUtecht.com.

So here’s my question for you: if you looked at how AI tools are showing up in your classrooms right now, would you say they’re designed in, or just left lying around?

Sources

• Same researcher, opposite results — Jill Barshay, The Hechinger Report (Proof Points), November 2, 2026
• The Effects of Course-Integrated AI Tutoring on Student Performance and Engagement: A Randomized University Trial — Jing Liu, Jennifer King Rice et al., EdWorkingPapers, October 2026
• TEACHER VOICE: In the age of AI, we are teaching the wrong skills. Let’s shift to teaching them more about how to think — Hiranya K. Nath, The Hechinger Report, November 2, 2026

The post Two AI Tutor Studies, Opposite Results. The Tool Wasn’t the Point. first appeared on The Thinking Stick.

Award-winning author Amy Sarig (A.S.) King joins Tricia to discuss her latest novel, It Came From the Creek, and what it truly means to foster rebels, revolutionaries, and creative thinkers in a world dominated by standardized testing. From students overturning a massive 3,000-book ban in Pennsylvania to late-night FOIA document deep-dives into 1970s chemical dumping, King pulls back the curtain on how real-world outrage transforms into middle-grade fiction.

Key Takeaways:

• Youth Activism in Action: How students in Central York School District succeeded in reversing a massive school board book ban when adult appeals fell flat.

• The Creative Crisis in Classrooms: Why standardized testing pushed creative writing out of 90–95% of American public schools—and why viewing writing as “puzzle-solving” gives young people lifelong agency.

• The Anatomy of an Idea: How a demolished haunted house, childhood friendships, and an EPA chemical dump converged to form It Came From the Creek.

• Digging Up the Truth: King’s obsessive research process, scouring thousands of pages of EPA records and uncovering toxic waste cover-ups to mirror the realities young readers face.

• The Power of Lifelong Friendships: Why navigating friendships across gender lines, growing through self-doubt, and nurturing authentic bonds remains at the core of human storytelling.

Resources & Mentions:

• Books mentioned: It Came From the Creek, Attack of the Black Rectangles, and Me and Marvin Gardens by A.S. King; The Pigman by Paul Zindel

• Central York School District student-led book ban challenge

• EPA toxic waste reporting and Freedom of Information Act (FOIA) research

Check out this episode of Shifting Our Schools

The post Raising Rebels one Great Read at a Time | A.S. King first appeared on The Thinking Stick.

What can a collapsible water bottle, a portable washing bag, and a multi-iteration laptop stand teach students about the future of work? In this episode, Jeff Utecht and Tricia Friedman reconnect in person to break down their favorite travel and remote-work gear—and explain how educators can use these everyday innovations to inspire authentic student entrepreneurship, design thinking, and marketing lessons.

From analyzing packaging design and social listening to projecting the gear needed for emerging careers like drone pilots, Jeff and Tricia share practical ways to bridge the gap between classroom inquiry and real-world innovation.

Want to check out the special page for our Business/Entrepreneurship learning?

https://www.shiftingschools.com/pack-for-a-job

What We Discuss in This Episode:

• Real-World Innovation in a Bag: How the Scrubba wash bag and Matador flat-pack bottles demonstrate sustainable design and solve modern traveler pain points.

• The Iteration Journey: What students can learn from the Roost Laptop Stand’s evolution from a Kickstarter project to version 3.

• Branding & Consumer Signals: Why packaging, hidden messages (like Bellroy’s internal tags), and temperature retention (Fellow Carter Move Mug) create loyal brand fans.

• Classroom Challenge: How to challenge students to identify niches, reverse-engineer viral products (like Dutch Bros or Takis), and price their own solutions.

• Future Literacy & Emerging Jobs: Anticipating the travel and productivity tools required for the next generation of careers.

Check out this episode of Shifting Our Schools

The post From Kickstarter to Classroom: Teaching Entrepreneurship Through Everyday Gear first appeared on The Thinking Stick.

What will it actually take—mentally, physically, and socially—to send humans to Mars and bring them back?

In this episode, host Tricia sits down with Dr. Mark Shelhamer, former Chief Scientist of NASA’s Human Research Program, Professor at Johns Hopkins University, and author of Are We Ready for Mars?. Dr. Shelhamer shares his journey from biomedical engineering to astronaut healthcare, diving deep into the unexpected psychological and behavioral hurdles of long-duration space travel. Together, they explore why technical engineering is only half the battle, what the “Earth out of view” effect does to the human mind, how crew autonomy is forged under intense isolation, and why learning to deal with the unexpected in deep space holds profound lessons for human resilience right here on Earth.

In this episode, we discuss:

• The path to space healthcare: Moving from pacemakers and vestibular balance research into NASA human spaceflight .

• The commercial space era: Why private and government collaboration has shifted Mars from science fiction into serious mission planning .

• Expanding the human experience: The philosophical and scientific incentives behind tackling a multi-year planetary mission .

• The “Earth out of view” effect: How profound isolation, communication delays, and total autonomy reshape astronaut psychology .

• Resilience & the unexpected: Why preparing for what you cannot predict is the single biggest operational lesson of spaceflight .

• Generalists in extreme environments: How music, calculated risk-taking, and interdisciplinary thinking foster adaptive teams .

About the Guest: Dr. Mark Shelhamer is a Professor of Otolaryngology–Head and Neck Surgery at Johns Hopkins University School of Medicine and the former Chief Scientist of NASA’s Human Research Program . His upcoming book, Are We Ready for Mars?, examines the critical biomedical and psychological challenges standing between humanity and the Red Planet .

Check out this episode of Shifting Our Schools

The post What Sending Humans to Mars Teaches Us About Human Resilience first appeared on The Thinking Stick.

Then, three days later, Harvard published a piece that looked at the same problem and came back with a much longer list of causes. Same crisis. Very different story.

Here’s the thing… both of these can be true at the same time. And if we only listen to the first one, we’re going to fix the wrong thing.

What’s happening with reading decline and technology

The Connecticut story, written by Livi Stanford for the Hartford Courant and republished on October 26, draws on a Connecticut Education Association survey of 113 teachers. More than half agreed it is harder to get students to finish a chapter book than it was five years ago; only 10 disagreed. Teachers described students who lack the stamina for longer texts and the vocabulary for complex ones. One called some students “functionally illiterate.” Another said AI is “sealing the deal” on reading problems that started with phones.

CEA president Kate Dias put it plainly: “We cannot produce students that can read and understand if they don’t actually read.” English teacher Meghan Hatch Geary said that “putting kids on screens, from phones to devices, has really had a detrimental impact.”

I want to be fair here. These are experienced teachers describing what they see every day, and I believe them. The article also notes some encouraging signs: nearly nine in ten of these teachers still assign three or four books a year, and Connecticut’s average English Language Arts score edged up, from 64.7 to 65.0, still short of the state target of 75. But it is worth being clear about what the piece is: teacher perceptions and open-ended comments. It is not a study that tested what is causing the problem.

On October 29, the Harvard Gazette’s “U.S. literacy crisis keeps getting worse” by Liz Mineo talked with researchers at the Harvard Graduate School of Education. The numbers are sobering. NAEP reading scores have trended down since 2013 for eighth graders and since 2015 for fourth graders. Only 31% of fourth graders were proficient or advanced readers on the 2024 NAEP. And the share of eighth graders reading for fun almost every day fell from 27% in 2012 to 14% in 2025.

When the Gazette lists the causes, it says the decline “has myriad causes,” including “pandemic disruption, chronic student absenteeism, fewer resources to support struggling readers,” “and the rise of smartphone technology and artificial intelligence.” Professor Phil Capin says “smartphones are taking opportunities away from children to read” and that “AI, when used inappropriately, replaces opportunities to read and write.” Professor Paola Uccelli points out that the students who read for fun almost every day and the students who miss no days of school score highest on national reading assessments.

Notice that phones and AI are on the Harvard list. I’m not going to pretend they aren’t. But they are on a list.

Here’s what the headline leaves out

When the story becomes “technology is destroying reading,” we end up with one villain and one fix: take the devices away. I understand the appeal. It’s visible, it’s simple, and you can announce it at a board meeting.

But look at what else is on that Harvard list.

Pandemic disruption. The students in middle and high school right now were learning to read, or learning to read to learn, when school went sideways.

Chronic absenteeism. A student who isn’t in the room isn’t reading in the room. I wrote about this a few weeks ago in Before We Blame Screens, Let’s Count the Empty Desks, and Uccelli’s point about attendance lands right on it.

Fewer resources for struggling readers. If a 7th grader can’t decode a grade-level text, no phone policy fixes that. Reading specialists, interventions and time do.

And one more thing worth sitting with: NAEP scores started sliding in 2013 and 2015. Smartphones were spreading among teens around then too, so I get why the timing feels convincing. Timing is a reason to ask the question. It isn’t the answer.

Here’s the distinction I keep coming back to. Back in 2010 I wrote about Active vs Inactive Screen Time. Scrolling short videos for three hours and reading a long article on a tablet are both “screen time.” They are not the same thing. When we lump them together, we lose the ability to teach the difference.

Yes… students are choosing short over long. Adults are too, most of us included. The reading habits kids see modeled at home and in the world matter, and that’s not a school problem schools can solve alone.

Reading is a skill we have to teach, not a habit we can protect

What strikes me most about the Connecticut teachers is what they are already doing about it. They’re breaking books into smaller sections, reading aloud, partner reading, and using shorter texts to build up. That is teaching. That’s the work.

Taking a device away doesn’t build stamina. It removes one distraction. Stamina gets built the way it always has, by reading, a lot, with support, in school, where we can see it happen.

And if students are going to spend their lives reading on screens (they are), then reading well on a screen is a skill we have to teach too. I argued back in 2014 in Replacing Skills that schools need to be intentional about the skills we’re adding as the world changes. Digital reading, knowing when to slow down, knowing when to close the tabs and go deep: those are skills. Banning teaches nothing. Teaching does.

The same goes for AI. Capin’s words matter: “when used inappropriately.” If a student uses AI to skip the book, that’s a problem with the task as much as the tool. In Human Still Required, I make the case that AI didn’t break school — it exposed it. Assignments that could be completed by reading a summary were always a little fragile. AI just made that obvious faster.

It comes back to the line I keep returning to on this blog: Preparing students for their future, not our past. Their future has more text in it, not less. Much of it on screens. Much of it written or summarized by machines. The kids who can read deeply, and who know when they need to, will have an enormous advantage.

What schools can do this week

• Protect real reading time in the school day. If most reading is assigned for home, find out how much is actually getting done, and move some of it back into class where you can support it.
• Look at your attendance data next to your reading data. Which students are missing the most days, and how are they reading? Start there.
• Ask what your struggling readers need. Is it decoding, fluency, vocabulary or motivation? Each one has a different fix, and none of them is a phone policy.
• Teach digital reading on purpose. Have students compare reading the same piece on paper and on a screen, and talk about what changes and how to focus.
• Redesign one assignment that a summary or an AI tool could complete without reading. Ask students to do something with the text that only a reader could do.

Frequently asked questions

Is technology causing the reading decline?

Technology is one factor researchers name, but not the only one. The Harvard Gazette lists pandemic disruption, chronic absenteeism, fewer resources for struggling readers, and smartphones and AI together. The evidence supports a multi-cause explanation, not a single villain.

Should schools ban phones to improve reading?

A phone policy can reduce distraction during the day, but it does not teach reading. Stamina, fluency and comprehension are built by reading a lot with support. If a school adopts a phone policy, it still needs a plan for reading time and help for struggling readers.

What can parents do at home?

Make reading visible and normal: read in front of your kids, talk about what you’re reading, and give them time and space to read things they choose. Pay attention to the difference between passive scrolling and active reading, on paper or on a screen.

I’m grateful to the Connecticut teachers for saying out loud what so many teachers feel. The frustration is real. My worry is that we answer a complicated problem with a simple fix, then wonder in five years why the scores didn’t move.

If your school or district is working through reading, AI and device decisions right now, this is the kind of work I do with leaders every week. You can find me at JeffUtecht.com.

So I’ll ask you: when your school talks about reading, how much of the conversation is about what to take away, and how much is about what to teach?

Sources

• “‘It is disheartening’: Teachers say technology is destroying students’ academic ability”, Livi Stanford, Hartford Courant (via Jefferson City News-Tribune), October 26, 2026
• “U.S. literacy crisis keeps getting worse”, Liz Mineo, Harvard Gazette, October 29, 2026

The post Teachers Say Tech Is Killing Reading. The Story Is Bigger. first appeared on The Thinking Stick.

Here’s the thing. For a long time K-12 schools have treated experience as something that happens later. College will handle it. The first job will handle it. But what if the line for that first experience is now so long that a lot of students never get to the front of it?

What’s happening with internships right now

Three pieces landed this week that, read together, tell one story.

First, Lisa Chambers’ October 14 Forbes piece on why internships matter for every major looks at Bennington College, where students have done a required Field Work Term since 1932. The article pulls together some strong data. NACE found that 43% of graduating seniors who applied for jobs this spring had at least one offer before graduation, compared with 55% of those who had completed a paid internship. Research from the Burning Glass Institute and Strada found students who completed internships in college were nearly 50% less likely to be underemployed five years out. And then there’s that Handshake number: 27 applications per internship posting in 2025, up from eight in 2022.

Second, Times Higher Education reported on October 14 on the Institute of Student Employers’ annual survey in the UK. Applications for university-level internships rose 27% in 2025-26 and applications for undergraduate placements rose 15%, while internship and placement hiring fell 8%. To be fair to the full picture, overall graduate hiring in that survey actually rose 4% this year after an 8% drop the year before, and the ISE described the early-career market as showing “some signs of recovery but remains challenging.” The survey also found 92% of employers suspected or confirmed students were using AI in assessment and selection, up from 85% the year before.

Third, Getting Smart’s October 13 recap of its New Pathways convening in Chicago profiles schools that aren’t waiting. At Oak Park and River Forest High School, students in entrepreneurship classes build business pitches through Uncharted Learning’s INCubatoredu program and use consumer research to test their ideas against competitors and customer needs. Student projects ranged from ski apparel to an AI highlight-reel tool for coaches. A culinary class runs a student restaurant and food delivery service. At Fenton High School, students can combine AP classes, work-based learning and dual enrollment with the College of DuPage.

So on one side: demand for experience is going way up and the number of formal slots isn’t keeping pace. On the other: some high schools are creating experience instead of waiting for someone to hand it out.

Experience is the new entry ticket. Why are we handing it out so late?

I want to be careful here. The data doesn’t say the entry-level job market has collapsed. The UK numbers show graduate hiring recovering. Most of the internship data is about college students, not high schoolers. And part of the jump in applications may simply be that applying has gotten easier. When you can apply to a posting in a few clicks, or let an AI tool help you churn out applications, the count goes up whether or not the number of serious candidates does. That ISE figure on AI use in applications is a hint that something like that is going on.

But even if you take all of that into account, the direction is clear. Employers are leaning harder on proof of experience, and the formal doors where students get that experience are crowded.

Here’s my question for K-12: if the first real experience is the thing that opens doors, why do we wait until students are 20 to start offering it?

I wrote about this back in 2013 in Millennials and the Job Market. My argument then was that a public digital portfolio and real work for real audiences would matter more than a paper resume. I think that’s even more true now. When a hiring manager is looking at 27 applications, or 141 for a UK graduate role, a list of courses doesn’t stand out. Work does. A business pitch tested against real customer research does. A restaurant service you helped run does.

And with AI in the picture, the bar for “real” goes up. If an AI tool can polish a cover letter, the cover letter stops telling an employer very much. What it can’t fake as easily is a track record: projects you built, people you worked with, problems you solved and can talk about. That’s the part of the work that’s still very human. In Human Still Required, I argue that judgment, relationships and trust are the work machines can’t do. Those are exactly the things students learn by doing real work alongside real people, and they’re hard to learn from a worksheet.

This is what I mean by “Preparing students for their future, not our past.” In our past, experience came after school. In their future, it may have to come during school, or a lot of students won’t get it at all.

High school internships aren’t the only door. Schools can build experience.

When I talk with school leaders about work-based learning, the conversation almost always goes straight to internships. And then it stops, because placements are hard. There aren’t enough employers. Transportation is a problem. Liability is a problem. Schedules are a problem. All true.

What I like about the Chicago examples is that they don’t start with “Where can we place a few hundred students?” They start with “What real work can students do from here?” A student business that has to compete for customers is real work. A student-run restaurant is real work. A pitch that gets tested against customer data is real work. None of those require a company to find hundreds of internship slots.

That matters for equity too. Internships have always leaned toward students who already have networks, transportation and the ability to work unpaid. The Forbes piece notes that Bennington gives need-based stipends to make its field work possible. If high schools build experience into the school day, every student gets a turn, not just the ones whose parents know someone.

I’m not saying every high school needs to become a startup incubator. I’m saying “experience” is a much bigger category than “internship,” and schools have more control over it than we tend to think.

What schools can do this week

• Audit your experience gap. Ask: how many of our seniors will graduate having done work for a real audience outside the classroom? Not “could have,” but did. Get a real number.
• Turn one existing project into a client project. Pick one course and find one local business, nonprofit or city office with a real problem students can work on. Start small.
• Count student-run work as experience. A school store, a media team, a tech help desk or a student restaurant is work. Help students document it and talk about it like work.
• Start the portfolio in ninth grade. Have students collect evidence of what they’ve built and done, with reflection on what they learned. By senior year they should be able to show, not just tell.
• Talk to employers about what they actually look for. Ask your local hiring managers what proof of experience they trust now that AI can polish an application. Then build backward from their answer.

Frequently asked questions

Are high school internships worth it if they’re hard to find?

Yes, but an internship isn’t the only way to get experience. Research cited by Forbes shows college internships are linked to more job offers and less underemployment. High schools can build similar experience through work-based learning, client projects and student-run businesses, which don’t depend on finding an outside placement for every student.

Why are internships so competitive right now?

Handshake data cited by Forbes shows the median internship posting got 27 applications in 2025, up from eight in 2022. In the UK, the Institute of Student Employers reported a 27% rise in internship applications alongside an 8% drop in internship and placement hiring. Easier online applying and AI-assisted applications may also be pushing the numbers up.

What counts as real work experience for a high school student?

Work done for a real audience with real stakes. That can be an internship or apprenticeship, but it can also be a student business, a project for a local organization, a school help desk or a student-run restaurant. What matters is that students can show what they did and explain what they learned.

The line is long. Let’s get them in it sooner.

The young people heading into this job market aren’t the problem. They’re doing what we told them to do, and then finding out the door is more crowded than anyone warned them. We can keep telling them experience will come later. Or we can start building it now, inside the schools we already run.

If your school or district is working on career-connected learning and wants to think it through together, that’s the kind of work I do with leaders every week. You can find me at JeffUtecht.com.

So I’ll ask you: what is one piece of real work your students did this year that you’d want an employer to see?

Sources

• Many Humanities Majors Shun Internships, But Not At This College, Lisa Chambers, Forbes, October 14, 2026
• Employers cut student work experience roles as demand rises, Georgia Luckhurst, Times Higher Education, October 14, 2026
• Bridging Passion and Possibility: Chicago’s Approach to New Pathways, Getting Smart Staff, Getting Smart, October 13, 2026

The post The Internship Line Is Getting Longer. High School Can’t Wait. first appeared on The Thinking Stick.

Here’s the thing. We keep framing this as a Gen Z problem. I think it’s a leadership problem. If young people can’t hop their way up, and AI is doing the tasks they used to learn on, then the ladder has to be built inside the organization. On purpose.

What happened this week

First, Fortune’s Muskaan Arshad reported on October 7 that the raise young workers get from job-hopping is shrinking. Using Bank of America Institute data, job switchers saw pay rise nearly 18% in 2022 compared with 7% for people who stayed. By the first quarter of 2026, that was 8% versus 5%, the smallest gap in seven years. (A September update showed switching premiums ticking back up to their highest in more than three years, though still below pre-pandemic levels.) The quits rate sat at 1.9% in August, near its lowest since 2020. Fortune describes a “low-hire, low-fire” labor market, and notes that the average age of a new hire rose to 42 in 2025, from 40.5 in 2022, according to Revelio Labs. Employers are hiring experience.

Second, Fast Company’s Peter Saalfield wrote the same day that young workers are turning toward AI-proof jobs. Citing Stanford Digital Economy Lab research using ADP payroll data, he reports that employment among 22- to 25-year-olds in the most AI-exposed professions is 19% lower than it would be had it kept pace with the same age group in other professions since 2022. More experienced workers show no such gap. The piece also cites PwC: entry-level postings in AI-affected fields are seven times more likely than in 2019 to require traditionally senior-level capabilities. And Pew found 73% of people under 30 now believe AI will lead to fewer jobs.

Third, The San Francisco Standard’s Jillian D’Onfro reported on October 10 that Gen Z is moving toward hands-on careers in the trades. She cites National Student Clearinghouse data showing vocational school enrollment up roughly 20% since 2020, and ADP research showing the median age of trade workers has dropped five years since 2020. An ADP executive, Kit Dickinson, told her people are starting to call Gen Z the “tool-belt generation.”

Now, to be fair, these stories don’t all point at AI. Fortune notes that Apollo chief economist Torsten Slok sees interest rates, trade uncertainty, slowing immigration and the low-hire market itself as likelier drivers than AI. The Stanford work, as Fast Company describes it, found no evidence of widespread, economy-wide job displacement. The decline for young workers comes mostly from companies hiring fewer of them, not firing them. That matters. This isn’t a robot apocalypse story. It’s a story about who gets a first chance.

Training entry-level employees used to happen by accident

Think about how most of us learned our jobs. Not in onboarding. Not in a training module. We learned by doing the small stuff. The first draft. The data cleanup. The meeting notes. The lesson plan someone more experienced tore apart and helped you rebuild. That grunt work was the training. Nobody designed it that way; it just happened.

AI is very good at the small stuff. So when an organization hands the first draft to a tool, it isn’t only saving time. It’s quietly removing the place where beginners used to build judgment.

And then we post an entry-level job that asks for senior-level skills. Seven times more likely than in 2019, if the PwC figure holds. Where exactly is a 23-year-old supposed to have picked those up?

I understand why employers are doing this. When the economy feels uncertain, hiring someone who can contribute on day one feels safer than hiring someone you have to teach. And there’s a real fear underneath it: why spend a year developing someone who might leave? I hear versions of that question from leaders all the time. It’s a reasonable question.

But look at what the Fortune data is telling us. Leaving isn’t paying off the way it used to. The exit door is narrower. That changes the math. If young employees are more likely to stay put right now, this is exactly the moment to invest in them…. not the moment to stop.

The trades kept the apprentice model. White-collar work let it slip.

Here’s what I find interesting about the trades story. Young people aren’t only drawn to the trades because AI can’t easily do the work. They’re drawn to a clear path. You show up, you’re paired with someone who knows the job, you do real work from early on, your skills are checked, and you move up as you prove them. It’s structured. It’s visible. Everyone knows what the next step looks like.

They have this pathway to economic mobility and some of the stability that white-collar jobs used to afford you.

Kelcie Wong, JVS, via The San Francisco Standard, October 10, 2026

“Used to” is doing a lot of work in that sentence.

Office work had its own apprenticeship once; we just didn’t call it that. The junior analyst, the associate, the first-year teacher down the hall from a veteran. What AI is doing is forcing us to decide whether we keep that learning or let it disappear with the tasks.

In The Next Turn, I argue that the structure of work is changing at the same time as the definition of work, and that one of the biggest shifts is the collapse of effort as a signal. When a tool can produce a polished draft in seconds, a polished draft no longer tells you much about the person. What matters is judgment: can they tell a good answer from a bad one, and explain why? Or as I put it in the book: “The standards remain. The proof system changes.” The standard for a junior employee hasn’t dropped. But how they build toward it, and how we see that they’ve met it, has to be redesigned.

I wrote about a version of this back in 2014 in Replacing Skills. When something new takes over an old skill, the question isn’t only what we stop doing. It’s what we replace it with. Organizations are asking the first question about AI and junior work. Very few are asking the second.

It’s the same question we ask in schools. We talk about preparing students for their future, not our past. Employers have that job too, just on the other side of graduation.

What leaders can do this week

• Map the lost learning. List the tasks your newest employees used to do that AI now handles. Next to each one, write what that task used to teach. That second column is your training gap.
• Use “attempt, then compare.” Have a junior employee do a piece of work on their own first, then compare it with what the AI produced, then talk through the differences with a manager. That conversation is where judgment gets built.
• Pair every new hire with a named person. Not a buddy for the first week. Someone whose job includes teaching them for the first year, with time set aside to do it.
• Make the next rung visible. The trades can say exactly what an apprentice has to show to move up. Can you? Write down what proof of readiness looks like for your entry-level roles.
• Rewrite one job posting. If an entry-level posting asks for skills only an experienced person has, either it isn’t an entry-level job or your training plan is missing.

Frequently asked questions

Is AI eliminating entry-level jobs?

Not across the whole economy, at least not yet. Stanford research reported by Fast Company found no widespread displacement, but employment for 22- to 25-year-olds in the most AI-exposed jobs is about 19% lower than expected, mostly because companies are hiring fewer of them. Economists also point to interest rates and a slow hiring market as major factors.

Why should employers invest in training junior employees if they might leave?

Because the pipeline of experienced people has to come from somewhere. If no one trains beginners now, there are fewer skilled mid-career people later. And with the pay premium for job-hopping shrinking, as Fortune reported this week, young employees have more reason to stay where they are growing.

What can office employers learn from apprenticeships in the trades?

Apprenticeships pair beginners with experienced workers, put them on real work early and make each step of progress clear. Knowledge-work employers can borrow that structure: named mentors, real tasks with feedback, and a visible definition of what someone has to show to move up.

The ladder doesn’t build itself

For a long time, organizations could count on the career ladder building itself. Juniors did the small work, learned along the way, and eventually weren’t junior anymore. AI is breaking that accident. That’s not all bad. It forces us to be intentional about something we were never very intentional about.

The trades never stopped training their beginners. Young people noticed. Maybe the rest of us should too.

If your organization is working through how to grow early-career talent while AI changes the work, this is what I do with leaders every week. You can find me at JeffUtecht.com.

So here’s my question for you: in your organization, where does a new hire learn judgment now that AI is doing the first draft?

Sources

• Job-hopping got workers an 18% raise in 2022. Now it’s 8%—and Gen Z is hurt the most — Fortune, Muskaan Arshad, October 7, 2026
• Young workers are turning toward AI-proof jobs — Fast Company, Peter Saalfield, October 7, 2026
• Touch grease: Gen Z ditches office work for hands-on careers — The San Francisco Standard, Jillian D’Onfro, October 10, 2026

The post The Trades Never Stopped Training Their Juniors. Why Did We? first appeared on The Thinking Stick.

Here’s the thing. One story says the first rung of the ladder is getting harder to reach. The other says some leaders are still building rungs. That tells me the first job isn’t only something that happens to young people. It’s something leaders decide.

What happened this week

On October 13, Fortune’s Preston Fore reported on IMF chief Kristalina Georgieva’s warning that AI is a “slow-moving tsunami” for jobs. Speaking at an event tied to the IMF and World Bank annual meetings in Bangkok, Georgieva put it plainly:

The people to worry about first and foremost are young people that are coming into the labor market.

Kristalina Georgieva, IMF Managing Director, as reported by Fortune, October 13, 2026

The Associated Press coverage of the IMF’s new World Economic Outlook (Elaine Kurtenbach, October 13) adds the bigger frame. Georgieva estimated AI’s global job impact at about 40%, with jobs “augmented or downgraded or eliminated,” and said “we are already seeing some of this impact.” Fortune notes that workers with AI-related skills are earning more, but that hasn’t turned into broad job growth, while some lower-paying roles are growing.

Georgieva was also careful about something I want to be careful about too. She said AI is not shrinking demand for people right now; it is shifting it. In her words, “That may not be the case in the future.” Singapore’s President Tharman Shanmugaratnam, at the same event, named where that shift lands first: “The first rung in employment, your first job upon graduation, is now seeing less demand.”

And then he said the line that stuck with me all week:

You lose a whole set of intangible attributes, and you lose trust in the future.

Tharman Shanmugaratnam, President of Singapore, as reported by Fortune, October 13, 2026

Three days later, Fortune’s Muskaan Arshad reported on which business owners are still planning to hire. In the Q3 2026 Small Business Index from Justworks and the U.S. Chamber of Commerce, 46% of Gen Z and Millennial owners expect to add staff in the next year, compared with 19% of owners who are Baby Boomers or older. Younger owners are also more likely to plan to increase investment (50% vs. 18%) and to expect revenue growth (71% vs. 51%). Across all owners, only 36% expect to add staff, down from 44% a year earlier.

Justworks CEO Mike Seckler told Fortune, “Young entrepreneurs, like Gen Z and millennial entrepreneurs, are much more bullish about how their businesses look.” ZipRecruiter labor economist Nicole Bachaud described the other side of it, from the job seeker’s view: “The old model was: Graduate, find an entry-level job, climb from there.” Now, she said, “Grads are piecing together experience through internships, side work, stepping-stone roles.”

Here’s what the headline leaves out

The easy way to read the small business numbers is as a generational fight: young bosses hire, older bosses don’t. I don’t buy that, and I don’t think the data says it.

I’ll admit the gap is big. But the U.S. Chamber’s own executive summary of the index also notes that businesses that have been operating for less time hold more positive views of the future than older businesses. So how much of this is about the owner’s generation, and how much is about where a business is in its life? A newer business is often in growth mode. A business that’s been around for 30 years might be steady, or planning a succession, or just being careful in a cooling economy. Those are all reasonable places to be. The survey, as reported, doesn’t tell us which is driving the gap, and I’m not going to pretend it does.

What I will say is this: the gap is a signal worth paying attention to. Whoever is doing the hiring is deciding who gets the first rung. And right now, at least in this survey, the leaders most willing to make that bet on young people are, more often, people who were young workers themselves not that long ago.

Which leads to the question I think every leader should sit with. If AI is shifting demand away from the first job, who is going to decide to keep making first jobs anyway?

Hiring young workers is a decision about trust

Tharman’s line about trust is the part of this week’s news I don’t think we talk about enough. When we talk about AI and entry-level work, we talk about tasks. Which tasks can the machine do? What’s left for the junior employee? Anthropic CEO Dario Amodei, quoted in the same Fortune piece, put it this way: “If you automate 90% of the job, then everyone does the 10% of the job.”

That’s a useful way to think about the work. But a first job was never only about tasks. It’s where you learn how a workplace runs, how to take feedback, how to recover from a mistake in front of people. Those are the “intangible attributes” Tharman was talking about. You don’t get them from a course. You get them from someone deciding to give you a shot.

In The Next Turn, I write about the value exchange between young employees and the organizations they work for, and how quickly young workers re-evaluate when that exchange stops making sense. One line from the book keeps coming back to me this week: “Organizations do not get loyalty upfront. They get scrutiny upfront.” Here’s the part I think leaders miss. That scrutiny doesn’t start on day one. It starts with whether you’re hiring at all. A generation that watches the first rung disappear, while hearing that AI is the reason, is forming its view of employers right now. Before they ever fill out an application.

So when an organization pauses all entry-level hiring because “AI can handle it for now,” it’s not just making a staffing decision. It’s making a trust decision. And trust is a lot harder to rebuild than a job posting.

I wrote back in 2013, in Millennials and the Job Market, about how young people needed to be able to show their work, not just list it on a paper resume. I still believe that. But this week reminded me there’s another half to that sentence. Young people can show up with a portfolio full of real work, and it doesn’t matter if nobody on the other side is willing to look at it.

We say we’re about preparing students for their future, not our past. The leaders hiring them are part of that future too.

What leaders can do this week

You don’t need a new program to start. Here are five moves any manager or executive can make before Friday:

1. Look at your last 12 months of hires by career stage. How many were someone’s first or second job? If the answer is zero, was that a decision someone made, or something that just happened?
2. Name the 10%. Pick one entry-level role. If AI took the routine tasks, what judgment, relationship or customer work would be left? Rewrite the role around that, and keep the role.
3. Protect one first rung. Commit to at least one paid internship, apprenticeship or entry-level role this year, even in a slow market. Put a name next to it as the person responsible for that new hire’s learning.
4. Ask your youngest managers what they see. If the survey is right that younger owners are more bullish, the people closest to that view may already work for you. Ask them where they’d hire and why.
5. Make your hiring visible. Young job seekers are watching who’s still hiring. Tell schools, colleges and your community what entry-level paths you offer, and what you look for.

Frequently asked questions

Is AI really taking entry-level jobs?

It’s mixed. The IMF estimates about 40% of jobs worldwide will be affected by AI, but that means augmented, downgraded or eliminated, not all lost. Georgieva said AI is shifting demand for people right now rather than shrinking it, and Singapore’s president said first jobs after graduation are seeing less demand. The honest answer is that the first rung is changing, and how much is AI versus a cooling economy is still being studied.

Why should my company keep hiring young workers if AI can do junior tasks?

Because a first job builds more than task skills. It’s where people learn judgment, workplace norms and how to handle feedback, which is the pipeline for your future mid-level and senior staff. Skipping it saves money now and can cost you trust and talent later.

Are younger business owners really more likely to hire?

In the Justworks and U.S. Chamber of Commerce Q3 2026 Small Business Index, as reported by Fortune, 46% of Gen Z and Millennial owners expected to add staff in the next year, compared with 19% of Baby Boomer or older owners. The Chamber also notes newer businesses are more optimistic than older ones, so business age may be part of the gap, not just the owner’s generation.

The question for leaders

I keep thinking about Tharman’s word: trust. Young people aren’t asking for a guarantee. They’re asking whether anyone is still willing to bet on them while they learn. Some leaders clearly are. The rest of us get to decide.

If your organization is trying to figure out what entry-level work looks like now that AI is part of the job, this is exactly the work I do with leaders. You can find me at JeffUtecht.com.

So here’s my question for you: when was the last time your organization hired someone into their very first job, and what did you learn from it?

Sources

• IMF chief warns AI’s ‘slow-moving tsunami’ is coming—and it could leave Gen Z graduates stuck making lattes at Starbucks — Fortune, Preston Fore, October 13, 2026
• IMF says AI boom driving world growth, but warns it’s a ‘slow-moving tsunami’ for jobs — The Associated Press (via NBC New York), Elaine Kurtenbach, October 13, 2026
• Gen Z founders are hiring as boomers’ corporate America freezes them out — Fortune, Muskaan Arshad, October 16, 2026

The post The Youngest Bosses Are Hiring. What Do They See That We Don’t? first appeared on The Thinking Stick.

That should be the headline of every AI conversation in every district this fall. Instead, most of the AI headlines I see are about what to ban, block or detect.

Here’s the thing…. Getting time back is only half the story. The other half is who gets to keep it.

What the new survey on teachers using AI found

On October 14, Gallup’s Megan Brenan published the latest Walton Family Foundation and Gallup findings on teachers and AI, part of a larger report called The Mattering Gap Among K-12 Educators, done with The Mattering Institute. The survey reached 1,952 U.S. K-12 educators on the Gallup Panel between July 28 and August 14, 2026.

The numbers that stood out to me:

• 59% of educators used AI tools such as chatbots and adaptive learning systems during the 2025-26 school year. Use was highest among educators ages 40 to 49 (67%) and lowest among those 60 and older (46%).
• Among those AI users, 13% said it gave them “a lot more time” for the parts of teaching that matter most to them, and 51% said “somewhat more time.” Another 29% said it had no effect, and 7% said it actually cost them time.
• 85% said helping a student through something difficult makes them feel they matter “a great deal.” Only 9% said that about completing administrative or required paperwork.
• Only 35% said they matter a great deal at their school.

Two days later, Naaz Modan at K-12 Dive put the survey in context. Teachers reported using AI to create lessons and assignments, grade, give feedback and handle administrative tasks. She also noted how fast this has moved: a 2024 RAND survey found only 18% of teachers using AI tools in their classrooms. And she pointed to a gap I hear about in almost every session I lead: an earlier Gallup and Walton survey from May found that more than 60% of teachers had received no guidance on using AI for things like analyzing student learning patterns, tutoring and one-on-one instruction, and nearly 60% had no guidance on using it for grading and feedback.

The same week, Edutopia’s Paige Tutt and Stephen Merrill published five “good” AI uses that may actually be bad for students: brainstorming, thesis writing, research, summarizing and first drafts. Their argument is a strong one and I want to state it fairly. For K-12 learners, the finished product matters less than the mental work of producing it. If AI does that work, students can end up with a polished product and a false sense of understanding. They quote cognitive scientist Daniel Willingham:

The point of the mental processes is learning.

Daniel Willingham, quoted in Edutopia, October 16, 2026

I agree with that. And I think it is exactly the lens we should put on the Gallup numbers too.

Take the paperwork, not the thinking

Put these two stories side by side and you get one simple principle: let AI take the work that isn’t the point, and protect the work that is.

For a teacher, paperwork isn’t the point. The survey says so pretty loudly. Nine percent. Helping a kid through something hard? That’s the job. That’s why people go into teaching in the first place. If AI can draft the parent newsletter, reformat the unit plan or take a first pass at the rubric so a teacher can spend that time sitting next to a student who is stuck, that is a trade I will take every single time.

For a student, the thinking is the point. A student who lets AI write the thesis statement skipped the learning. That’s the Edutopia argument, and it holds up.

So the question in both cases is the same: what is the work that matters here, and who should be doing it?

This is the core of what I wrote about in Human Still Required. Tools can draft, summarize and analyze. Judgment, relationships, trust and accountability have to stay human. Different tools. Same leadership work.

I’ll admit the survey has limits. It’s self-reported, and “I feel like I have more time” is not the same thing as a time study. Nearly three in ten AI users said it made no difference, and 7% said it cost them time. That matters. Badly designed tools, or tools teachers were never trained on, can create work instead of saving it. With the guidance gaps K-12 Dive described, I’m not surprised some teachers are spending more time, not less.

But here’s what worries me more than the 7%….

Saved time has a way of disappearing

Every teacher reading this knows what happens to “found” time in a school. It gets filled. A new initiative. Another data meeting. One more form.

If teachers using AI are clawing back an hour a week and the system quietly hands them an hour of new tasks, we didn’t gain anything. We just moved the paperwork around. And the survey suggests that is a real risk, because only 35% of educators say they matter a great deal at their school. People who don’t feel valued notice when the time they earned gets taken.

That’s a leadership problem, not a technology problem. Which is why I keep saying AI didn’t break school, it exposed it.

We have a choice. They don’t.

There’s one more piece of the K-12 Dive story I can’t stop thinking about. New York City has put a one-year moratorium on student-facing AI tools from preschool through 8th grade for the 2026-27 school year, affecting about 600,000 students. K-12 Dive notes that no similar restrictions have been announced for teachers.

I understand why a district would pause. There are real questions about privacy, about which tools are safe for young kids, and about the kind of offloading the Edutopia piece describes. Caution about elementary students using chatbots isn’t unreasonable.

But think about what we’re setting up. The adults get to learn how to use these tools to make their work better. The students wait. I wrote about this back in 2016 in We have a choice, They don’t: adults can choose whether technology is part of their lives. Our students don’t get that choice, because their future requires it.

A pause can be fine. A pause with no plan for teaching students when to use AI, when not to, and why, is just postponing the learning. Preparing students for their future, not our past means the adults who are figuring out these tools have to bring students along, not just protect them from it.

What school leaders can do this week

• Ask teachers where the time went. If your teachers are using AI, ask them a simple question: what did you do with the time it saved? Then listen.
• Protect it on purpose. Before adding any new task or meeting this semester, ask what you are taking off teachers’ plates to make room for it.
• Close the guidance gap. Give teachers clear, practical guidance on using AI for grading and feedback, including where a human must review the output before it reaches a student.
• Sort the work. In a staff meeting, have teams list their tasks in two columns: “the point” and “not the point.” Use AI on the second column first.
• Have the same conversation with students. Use the Edutopia list as a discussion starter: when does AI help you learn, and when does it skip the learning for you?

Frequently asked questions

How many teachers are using AI?

According to the Walton Family Foundation and Gallup survey released in October 2026, 59% of U.S. K-12 educators used AI tools during the 2025-26 school year. A 2024 RAND survey had found only 18% of teachers using AI tools in their classrooms.

Does AI actually save teachers time?

Most teachers using AI say it does. In the Gallup survey, 64% of AI users said it gave them more time for the parts of teaching that matter most to them. But 29% saw no effect and 7% said it cost them time, so training and the quality of the tools matter.

Should students be allowed to use AI if teachers do?

The tasks are different. For teachers, AI can take on administrative work so they can focus on students. For students, the thinking is the learning, so the question is which uses support that thinking and which replace it. Students need to be taught that difference, not just kept away from the tools.

The time is the gift. Don’t waste it.

If a tool can give a teacher back even a little time for the moments that make them feel like they matter, that is worth protecting. The tool did its part. Now leaders have to do theirs.

If your school or district is trying to figure out how to make AI give teachers time back, and keep it, this is the work I do with leaders every week. You can find me at JeffUtecht.com.

So let me ask you: if AI saved you an hour this week, what would you do with it, and would your school let you keep it?

Sources

• Teachers Using AI Say It Frees Up Time for What Matters Most — Gallup, Megan Brenan, October 14, 2026
• Educators who use AI say it frees up time to interact with students — K-12 Dive, Naaz Modan, October 16, 2026
• 5 ‘Good’ AI Use Cases That Are Actually Bad for Students — Edutopia, Paige Tutt and Stephen Merrill, October 16, 2026

The post AI Gave Teachers Time Back. Who Gets to Keep It? first appeared on The Thinking Stick.