AI at Work

The free-spending era of AI at work is ending

For the past couple of years, many companies let employees use AI tools with almost no limit on cost. That is changing fast: Walmart, Uber, and Microsoft have all started capping how much AI usage employees get, after Uber reportedly burned through its entire annual AI budget in just a few months. Procurement teams are now asking every team to justify what each AI tool is actually worth, not just how often people use it.

For youStart keeping a simple note of what your AI tool use has actually saved you or produced this month, in time or results, so you have a real answer ready when someone asks whether it's worth the cost.

Source: MarketScale ↗

Teach your AI where you keep your life, then hand it real tasks

One person needed a taxi booked while traveling, so he had his coding AI check his calendar for the flight, search his email for the address he used last time, then go online and complete the booking and payment itself. The trick was not a clever instruction. It was that his files already held his memories, his ongoing projects, and notes about himself, so the AI had everything it needed without him explaining from scratch.

For youStart one plain text file today that lists your recurring tasks, key facts about you, and where things live, so any AI tool you use later already knows the basics.

Source: Ben's Bites ↗

Reviewing a tax return beats typing one in by hand, and that is now the job

Accountants using OpenAI's new tax tool no longer start from a blank form. The AI reads the messy PDFs, spreadsheets, and notes, prepares a full draft, and shows exactly which document and cell each number came from. The team even found cases where the AI's number was right and the old human-entered answer was wrong, so the job shifted from data entry to checking evidence and catching what the AI got wrong.

For youNext time an AI hands you a finished draft, ask it to show its sources before you approve anything, the way you'd want to see a source anyway.

Source: OpenAI ↗

Source: The Information ↗

AI help is moving into the chat apps you already use

You used to open a separate AI website, ask your question, then copy the answer back into Slack or Teams. Anthropic is now building Claude into Microsoft Teams too, so people can tag it right inside a group chat and get help without switching tools. Microsoft and Salesforce are both letting a rival's AI operate inside their own apps, because keeping people in the app matters more to them than keeping a competitor out.

For youNext time you need help on a work chat, check if you can now tag the AI right there instead of opening a new tab.

Claude's everyday AI can now finish multi-step tasks on its own

Until now, an AI that could work through several steps on its own, browsing a page, testing a fix, filling out a form, lived behind the most expensive plan. Anthropic just brought that same follow-through to Sonnet 5, the AI most people get by default when they open Claude for free or on the cheaper Pro plan. Early testers had it investigate a bug, write a test, fix the code, and confirm the fix worked, without checking in at every step.

For youNext time you use Claude, give it one task with several steps instead of breaking it into separate messages, and see how far it gets before you need to step in.

Source: Anthropic ↗

Stop organizing your AI with files and folders, organize it with two simple tools

People setting up Claude for real work used to build a folder full of instruction files and hope the AI read the right ones at the right time. That approach breaks down once more than one person needs to use it, so the better setup now is two things: a Skill for anything you do repeatedly, and a Project for anything tied to one client or context. Teams that keep the two separate can share and reuse both without the AI dragging outdated information into the wrong conversation.

For youPick one task you re-explain to an AI every week and turn it into a saved Skill this week, instead of writing it out again from scratch.

Source: Ruben Hassid ↗

AI at Work Demographics & Labor

Writing Code Is No Longer the Hard Part. Deciding What to Build Is.

AI coding tools have made individual engineers far more productive at writing software, and companies are noticing that the constraint has shifted. The question is no longer 'can we build this' but 'should we build this'. Engineers who combine technical skills with strong product judgment and an understanding of what customers actually want are becoming more valuable than fast coders.

For youIf you are an engineer, investing time in product thinking, customer research, and code review is more valuable now than writing faster. If you manage engineers, look at your hiring and role definitions, because what you need from that team is changing.

Source: TLDR AI

People who hand more work to AI feel more secure about their jobs, not less

Anthropic tracked how people actually use Claude hour by hour, not just once a week, and paired that with a survey of thousands of users. People are turning to it for personal things too, like health questions or money worries, especially on weekends. The people who hand over more of their work to the AI are also the ones who feel better about their income and career stability, not worse.

For youIf you have been holding back from using AI at work out of worry it threatens your job, try handing it one routine task this week and see how your day changes.

Source: Anthropic ↗

Ford brought back the inspectors AI was supposed to replace

Ford leaned on AI tools to handle quality inspection on its production lines, then started seeing problems slip through that experienced engineers used to catch. The company has now rehired around 350 veteran quality engineers, and its quality rankings have improved since. Speed went up when the AI took over, but the judgment built from years on the floor turned out not to be something a company could hand off completely.

For youIf your team has automated a quality or review step, check who still double-checks the edge cases, and make sure it is a person.

Source: Bloomberg ↗

Source: The Information ↗

A weekend now buys what a $20,000 team used to

A veteran software builder once paid a team about $20,000 and waited months for a working first version of his product, with specs, meetings, and rounds of changes. This year he built a similar version by himself in a single weekend using Claude. The expertise still mattered, it just moved from an expensive team effort to one person working fast with the AI beside him.

For youPick one project you always assumed needed a hired team, and try sketching a working version yourself with AI first.

AI at Work AI Governance & Regulation

California just gave a preview of AI rules coming to your workplace

California signed a deal to give state agency workers access to Claude at half price, the first time a state government has formally cleared an AI assistant for its staff at this scale. Government jobs are usually slow to adopt new tools, so this is a sign that AI use at work is moving from early adopters into standard practice everywhere. If your employer has not set official rules for using AI yet, deals like this usually arrive there next.

For youCheck whether your workplace already has an official AI tool and policy, and if not, ask when one is coming.

Source: Governor Newsom's Office ↗

AI at Work Demographics & Labor

AI Is Going Deepest Into the Most Complex, Highest-Paid Work

Anthropic's June 2026 Economic Index found that workers in high-wage, complex jobs use AI tools far more intensively than those in lower-paid roles, consuming up to two and a half times more computing per task. The conventional assumption was that AI would first replace the cheapest, most repetitive tasks. The data suggests the opposite: it is deepest in the roles that require the most expertise.

For youIf you are a professional in a high-skill field, you may already be using AI heavily without fully recognizing the shift. Map out how much of your weekly work AI is now touching, and decide what you want to reclaim versus what you are comfortable delegating.

Source: TLDR AI

AI at Work Demographics & Labor Skills & Reskilling

Young Workers in AI-Exposed Jobs Are Losing Ground Faster Now

Stanford launched a live tracker covering 4.6 million workers across 730 jobs, and the early finding is stark: people aged 22 to 25 working in the most AI-exposed roles have seen employment drop 16% since late 2022. This is not a future risk. It is a change that has already happened. The effect is getting larger each month, not smaller.

For youIf you manage entry-level staff or hire early-career talent, the tasks those roles covered are already shifting. Check which parts of your team's work has moved to an AI tool in the past year, then redesign around what is left.

Source: The Neuron

AI at Work Demographics & Labor

Microsoft's AI Work App Is Now Live. And the Free Ride Is Over.

Microsoft Copilot Cowork moved out of preview and into its paid version last week, and the billing model changed completely. Tasks now run on a credit system where heavy jobs can cost several dollars each, and scheduled tasks can run overnight without warning anyone. Admins who do not set spending caps before July 1 may face surprise bills.

For youIf your team uses Copilot Cowork, log into the Microsoft admin panel today, find the credit usage settings, and set a cap per user before the billing clock starts running.

Source: The Neuron

A live tracker shows AI is already shrinking the first rung of the career ladder

A new live tracking tool built by Stanford and ADP covers 4.6 million workers across 730 occupations. It found that hiring for 22- to 25-year-olds in the jobs most exposed to AI fell 16 percent since late 2022, and the number keeps dropping every month. Entry-level jobs are the first to shrink because AI now handles much of the learning-on-the-job work that juniors used to do, and this is already showing up in real hiring data.

For youIf you manage or mentor someone early in their career, the path into professional work is narrowing faster than most organizations realize. Helping a junior colleague build AI-era skills today may be the most valuable thing you do for them.

Source: Fortune ↗

AI at Work Frontier Models

When AI writes the code, the job that matters most is deciding what to build

A software engineer used to spend most of the day writing code. AI tools now handle much of that writing, so engineers are spending more time on judgment: what to build, which tradeoffs to make, and whether the output actually solves the right problem. Companies that tripled their engineering output with AI are now discovering they do not have enough people with the customer insight and judgment to decide what to build next.

For youIf you work on a technical team, start noticing how much of your time goes to deciding what to build versus building it. That deciding side is where the value is moving, and it is a skill you can practice deliberately.

Source: VentureBeat ↗

AI's economic growth is outpacing the internet, and automated tasks are pulling far ahead of chat

In 2023 it took six months for the AI industry to add a billion dollars in new revenue. Today that same growth takes two days, and new research shows the AI economy hit $110 billion last year, scaling three times faster than the internet did at this stage. The automated tasks that AI handles on its own, without a human asking in real time, are using 1,200 times more computing power than simple question-and-answer chat, which means the shift from AI as a chat tool to AI as a background worker has already happened at scale.

For youPay attention to which tasks your AI tools already handle automatically without you asking. That list is growing fast, and professionals who know how to set those tasks up will outpace those who still rely on asking one question at a time.

Source: Exponential View ↗