Google Study Reveals AI Use in 800 Occupations Across 150 Countries

It's a blue collar tool alright! Seeing the stats for how users are learning to adapt AI into their lives is awesome. I have personally used AI to manifest a backyard mechanic out of my pocket to help me fix an overheating 350Z with a coolant bleed procedure that would work on the fly. Walked be through diagnostics in 15 minutes. I absolutely love it even with the Algorithmic Bias bugs.

We need to use AI as an augmenter, and at times as an automator, and Google's new ATLAS study backs that up. Analyzing 15 million interactions, it found most AI use is collaborative (ideation, troubleshooting, learning), with under 10% of interactions fully automating tasks, across both office and manual trades. Adoption tracks GDP per capita globally, but some middle-income countries are closing the gap fast. And then there is Kimi-K3 😁 https://lnkd.in/geKCHFdF

How are people using AI at work and in their day to day? That’s the question Google set out to answer in the first iteration of the AI & the Economy ATLAS (Activity, Task, Landscape, and Adoption Study) – an ongoing, large-scale, aggregated and de-identified study of how people use Google’s AI products and tools across more than 150 countries, 140 languages, 800 occupations, and 4000 tasks. Some highlights: 1. Workplace AI adoption spans all industry sectors – and 68% of all occupations – but is overwhelmingly used as a tool for ideation, strategy, and learning, with full automation accounting for less than 10% of interactions. 2. Workers in manual and technical trades, like auto techs or industrial mechanics, are using AI on the job for real-time diagnostics, troubleshooting, and learning (ex. interpreting complex test results, debugging electrical wiring, and inspecting machinery for wear). 3. AI usage has diffused globally. ATLAS data shows AI usage in over 150 countries and territories that represent 99% of the world's population. English represents only about 1/3 of global AI conversations, and users do not systematically abandon their native languages for complex tasks. AI’s capabilities and applications are advancing, with profound potential upside – and maximizing it requires collective action across the public and private sectors and civil society, with a focus on protecting against the downside. This report is intended to provide an early view of a quickly evolving landscape and is the beginning of ongoing research to support researchers, policymakers, businesses, and workers in shaping the ways AI can better support people in their lives. Explore the findings here: https://lnkd.in/gbReXMcq https://lnkd.in/gtCSSYtP

𝐆𝐨𝐨𝐠𝐥𝐞’𝐬 𝟏𝟓 𝐌𝐢𝐥𝐥𝐢𝐨𝐧-𝐂𝐡𝐚𝐭 𝐒𝐧𝐚𝐩𝐬𝐡𝐨𝐭: 𝐀𝐈 𝐈𝐬 𝐖𝐢𝐝𝐞𝐬𝐩𝐫𝐞𝐚𝐝, 𝐛𝐮𝐭 𝐍𝐨𝐭 𝐘𝐞𝐭 𝐃𝐨𝐢𝐧𝐠 𝐌𝐨𝐬𝐭 𝐉𝐨𝐛𝐬 Google’s Zanna Iscenko and Scott Strand introduced ATLAS, a continuing study of 15 million aggregated, de-identified interactions with the Gemini App, AI Mode and Gemini API. The first dataset covers more than 150 countries, 140 languages, 800 occupations and 4,000 tasks. Its early findings include: • AI appeared in 68% of occupations representing 90% of U.S. employment, but a typical occupation used it for only about 21% of its tasks. • Most workplace use involved brainstorming, strategy, research and learning. Fewer than 10% of work interactions fully automated a task. • Manual and technical workers also used AI. Auto technicians and industrial mechanics used it for diagnostics, wiring problems and equipment inspection. These workers were twice as likely to use “multimodal” AI, which can work with images, video or other formats beyond text. • More than 86% of measured interactions happened outside work, including shopping research, appliance help and navigating taxes, licenses and fines. • Usage per person generally rose with GDP per capita—the average economic output per person—suggesting a continuing digital divide. Some middle-income countries in South America and the Middle East were exceptions. The results are not a complete map of AI use. They cover selected Google tools and exclude products including Workspace, Translate, AI Overviews, enterprise platforms and emerging agentic coding systems. Google also describes its own privacy safeguards, so independent research will remain important. Google acknowledged report contributors Dame Diane Coyle and Dr. David Autor. The wider ATLAS team includes Yiyuan C. , Guillaume Aimard, Mihai Codreanu, Vivek Sampathkumar, Alex Imas, Julian Jacobs, Evalyne M., Juan Mateos-Garcia, Jia Jen Ng, Samirah Javed, Joshua Martin, Omar Ajmeri, Denis Calin, Andrew Kim, Fabien Curto Millet and James Manyika. 🤔 𝐍𝐨𝐰 𝐏𝐨𝐧𝐝𝐞𝐫 𝐓𝐡𝐢𝐬: How are you using AI to adapt and thrive, not to be replaced? 𝐂𝐫𝐞𝐝𝐢𝐭𝐬 Original authors: Zanna Iscenko and Scott Strand This summary was written by #ChatGPT with some human help by Jacob Walker Actually Useful AI Training provides these summary of AI related news as a free service. If you want to dig deeper into how to use AI more effectively, consider taking one of our trainings. https://lnkd.in/g7ygcZK9

Google just published the largest real-world study of how people actually use AI - and the findings challenge a lot of assumptions. 🧵 Google released the first ATLAS report (Activity, Task, Landscape, and Adoption Study) — built from 15 million de-identified conversations across Gemini App, AI Mode, and the Gemini API. It covers 150+ countries, 140+ languages, 800 occupations, and 4,000 tasks. Here's what caught my eye: 𝗔𝗜 𝗮𝘁 𝘄𝗼𝗿𝗸 𝗶𝘀 𝗯𝗿𝗼𝗮𝗱 𝗯𝘂𝘁 𝘀𝗵𝗮𝗹𝗹𝗼𝘄: People use AI in 68% of job types, covering 90% of all US workers. But in any single job, AI is only used for about 21% of the daily tasks. So AI isn't replacing jobs — it's helping with small parts of them. 𝗜𝘁'𝘀 𝗮𝘀𝘀𝗶𝘀𝘁𝗶𝗻𝗴, 𝗻𝗼𝘁 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗻𝗴: Less than 10% of AI use at work fully finishes a task on its own. Most of the time, people use it to brainstorm, plan, research, or learn something new. It's more like a helpful teammate than a replacement. 𝗜𝘁'𝘀 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗳𝗼𝗿 𝗱𝗲𝘀𝗸 𝗷𝗼𝗯𝘀: Even car mechanics and factory technicians are using AI — to figure out wiring problems, read test results, or troubleshoot machines on the spot. These workers are twice as likely to use AI with images and videos compared to the average user. 𝗠𝗼𝘀𝘁 𝗔𝗜 𝘂𝘀𝗲 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 𝗼𝘂𝘁𝘀𝗶𝗱𝗲 𝘄𝗼𝗿𝗸: 86% of all AI conversations happen outside of work — things like comparing products before buying, or figuring out confusing paperwork like taxes or government forms. This kind of everyday help doesn't usually show up in economic reports, but it clearly matters to people. 𝗥𝗶𝗰𝗵𝗲𝗿 𝗰𝗼𝘂𝗻𝘁𝗿𝗶𝗲𝘀 𝘂𝘀𝗲 𝗔𝗜 𝗺𝗼𝗿𝗲 — 𝗯𝘂𝘁 𝗻𝗼𝘁 𝗮𝗹𝘄𝗮𝘆𝘀: In general, wealthier countries use AI more per person, which raises fair concerns about who gets left behind. But it's not a strict rule — some middle-income countries in South America and the Middle East are using AI just as much as richer nations. And it's not just an English-speaking trend either: English makes up only about a third of AI conversations worldwide. People are using AI in their own language, even for complicated tasks. Big takeaway: AI's impact on jobs and the economy isn't automatic — how it plays out depends on real choices. Studies like this give us actual data instead of guesses, which is exactly what's needed to make good decisions going forward. Full report here 👇 🔗 https://lnkd.in/d_qjaQVM #AI #ArtificialIntelligence #FutureOfWork #GoogleAI #Gemini

Super interesting! "Google’s AI & Economy ATLAS v1.0: Mapping Gemini Usage in the Economy" "This paper introduces the AI & Economy ATLAS (Activity, Task, Landscape, and Adoption Study), an ongoing economic research initiative using Google AI usage data. The first iteration of ATLAS is built on 15 million de-identified interactions across the Gemini App, Google AI Mode, and Gemini API. Using privacy-preserving algorithms as well as established and bespoke classification methods, we map AI usage to over 800 occupations, 4000 tasks, 300 household activities, 150 countries, and 140 languages. We then make a number of observations on what the data reveals about AI’s diffusion, and its usage at work and in day-to-day life. In the workplace, we show that while AI adoption spans occupations covering just above 88% of US employment, penetration remains shallow and overwhelmingly collaborative in nature, with end-to-end task automation limited in scope. Outside of work, AI spans activities making up about 98% of Americans’ non-sleep time, with disproportionately high use in high-friction tasks such as engaging with government and professional service providers, likely delivering economic value that standard national accounts may miss. Globally, adoption scales with national wealth and has broad linguistic distribution, with English queries representing only around a third of volume. As we build upon ATLAS and expand its scope and capabilities, we will continue to provide large-scale empirical evidence to inform the public, policy and academic questions about the ongoing AI transformation." https://lnkd.in/et3SFEvn

Fascinating insights from Google on the evolving AI economy! As AI adoption accelerates, understanding its broader economic impact, productivity shifts, and future potential is more crucial than ever for leaders and innovators. Check out the full read here: 👇 #ArtificialIntelligence #AIEconomy #Innovation #FutureOfWork #TechTrends

Across 15M AI interactions, consumer purchases now make up 5.2% of all conversations, running about 3x ahead of the time people actually spend shopping. Researching purchases has become one of the most common everyday use cases, and comparison shopping is heavily over-represented. More than 86% of all AI usage happens outside of work. It's conversations, not conversions, so read it as direction rather than proof. But the direction is unmistakable: discovery and consideration are moving into AI. And that is exactly where the agentic commerce battle for brands and retailers begins. Thanks to the Google team for releasing this dataset!

Proud to share this snapshot from the new AI & Economy ATLAS (v1.0) study, led by our brilliant Research leaders James Manyika Scott Strand Andrew Kim . It provides much-needed data on how AI tools are actually being used across 4,000+ tasks and 140 languages. Analyzing real-world usage across 800+ occupations, this is a massive step forward in understanding how people are actually leveraging AI in their work and daily lives today. Worth a read for anyone thinking deeply about the future of work and the economy! 👇