Here are some of the the major AI trends shaping 2026 — based on current expert forecasts, industry reports, and recent developments in technology. The material is analyzed using AI tools and final version hand-edited to this blog text:
1. Generative AI Continues to Mature
Generative AI (text, image, video, code) will become more advanced and mainstream, with notable growth in:
* Generative video creation
* Gaming and entertainment content generation
* Advanced synthetic data for simulations and analytics
This trend will bring new creative possibilities — and intensify debates around authenticity and copyright.
2. AI Agents Move From Tools to Autonomous Workers
Rather than just answering questions or generating content, AI systems will increasingly act autonomously, performing complex, multi-step workflows and interacting with apps and processes on behalf of users — a shift sometimes called agentic AI. These agents will become part of enterprise operations, not just assistant features.
3. Smaller, Efficient & Domain-Specific Models
Instead of “bigger is always better,” specialized AI models tailored to specific industries (healthcare, finance, legal, telecom, manufacturing) will start to dominate in many enterprise applications. These models are more accurate, legally compliant, and cost-efficient than general models.
4. AI Embedded Everywhere
AI won’t be an add-on feature — it will be built into everyday software and devices:
* Office apps with intelligent drafting, summarization, and task insights
* Operating systems with native AI
* Edge devices processing AI tasks locally
This makes AI pervasive in both work and consumer contexts.
5. AI Infrastructure Evolves: Inference & Efficiency Focus
More investment is going into inference infrastructure — the real-time decision-making step where models run in production — thereby optimizing costs, latency, and scalability. Enterprises are also consolidating AI stacks for better governance and compliance.
6. AI in Healthcare, Research, and Sustainability
AI is spreading beyond diagnostics into treatment planning, global health access, environmental modeling, and scientific discovery. These applications could help address personnel shortages and speed up research breakthroughs.
7. Security, Ethics & Governance Become Critical
With AI handling more sensitive tasks, organizations will prioritize:
* Ethical use frameworks
* Governance policies
* AI risk management
This trend reflects broader concerns about trust, compliance, and responsible deployment.
8. Multimodal AI Goes Mainstream
AI systems that understand and generate across text, images, audio, and video will grow rapidly, enabling richer interactions and more powerful applications in search, creative work, and interfaces.
9. On-Device and Edge AI Growth
10. New Roles: AI Manager & Human-Agent Collaboration
Instead of replacing humans, AI will shift job roles:
* People will manage, supervise, and orchestrate AI agents
* Human expertise will focus on strategy, oversight, and creative judgment
This human-in-the-loop model becomes the norm.
Sources:
[1]: https://www.brilworks.com/blog/ai-trends-2026/?utm_source=chatgpt.com “7 AI Trends to Look for in 2026″
[2]: https://www.forbes.com/sites/bernardmarr/2025/10/13/10-generative-ai-trends-in-2026-that-will-transform-work-and-life/?utm_source=chatgpt.com “10 Generative AI Trends In 2026 That Will Transform Work And Life”
[3]: https://millipixels.com/blog/ai-trends-2026?utm_source=chatgpt.com “AI Trends 2026: The Key Enterprise Shifts You Must Know | Millipixels”
[4]: https://www.digitalregenesys.com/blog/top-10-ai-trends-for-2026?utm_source=chatgpt.com “Digital Regenesys | Top 10 AI Trends for 2026″
[5]: https://www.n-ix.com/ai-trends/?utm_source=chatgpt.com “7 AI trends to watch in 2026 – N-iX”
[6]: https://news.microsoft.com/source/asia/2025/12/11/microsoft-unveils-7-ai-trends-for-2026/?utm_source=chatgpt.com “Microsoft unveils 7 AI trends for 2026 – Source Asia”
[7]: https://www.risingtrends.co/blog/generative-ai-trends-2026?utm_source=chatgpt.com “7 Generative AI Trends to Watch In 2026″
[8]: https://www.fool.com/investing/2025/12/24/artificial-intelligence-ai-trends-to-watch-in-2026/?utm_source=chatgpt.com “3 Artificial Intelligence (AI) Trends to Watch in 2026 and How to Invest in Them | The Motley Fool”
[9]: https://www.reddit.com//r/AI_Agents/comments/1q3ka8o/i_read_google_clouds_ai_agent_trends_2026_report/?utm_source=chatgpt.com “I read Google Cloud’s “AI Agent Trends 2026” report, here are 10 takeaways that actually matter”
3,923 Comments
Tomi Engdahl says:
Will Knight / Wired:
Researchers find that feeding a frontier model’s encrypted reasoning traces to a weaker model from the same provider can make it output the traces in plaintext — Researchers devised a way to extract “reasoning traces” from Claude, GPT, and Gemini. What they found, they say …
A New Trick Reveals AI Models’ Inner Thoughts
Researchers devised a way to extract “reasoning traces” from Claude, GPT, and Gemini. What they found, they say, indicates that some Chinese AI may be trained on leading US models.
https://www.wired.com/story/a-new-trick-reveals-ai-models-inner-thoughts/
Tomi Engdahl says:
Wall Street Journal:
Some health and fitness obsessives are using AI for hyperpersonalized training, building custom dashboards and tools to analyze their sleep, workouts, and diet
The Datamaxxers Feeding Their Every Health Move to AI
From marathon training to tracking office angst, health obsessives are linking their data to chatbots to build hyperpersonalized coaches
https://www.wsj.com/tech/ai/the-datamaxxers-feeding-their-every-health-move-to-ai-df0af9b5?st=hqiG7z&reflink=desktopwebshare_permalink
As a competitive runner, Julian Flieller relied on human coaches to time his splits and manage his training regime. Today, he prepares for recreational marathons under the watchful eye of a chatbot.
Armed with the workout, sleep and other biometric data Flieller collects with fitness trackers, Anthropic’s Claude model suggests workout modifications. It helps the 25-year-old software engineer connect the dots between his work schedule and athletic performance.
Before Claude, Flieller received pings about stats such as heart-rate variability, or HRV, which generated more stress than clarity. “Like, your HRV is 60. Okay great, I don’t know what that means.”
Health obsessives often monitor workouts, step counts, sleep metrics, heart rates and nutrition data, cross-referencing the information with their calendars, meeting transcriptions, emails and clinical records.
Now, they are supercharging their habits with AI systems that serve as hyperpersonalized health trainers and assistants. While fretting over such minutiae is far from mainstream practice—many doctors recommend simplicity in fitness and nutrition—a growing number of so-called datamaxxers have finally found their version of nerd Valhalla.
Tomi Engdahl says:
Ben Dummett / Wall Street Journal:
Stockholm-based AI coding startup Lovable raised $400M at a $13.3B valuation, up from $6.6B in December 2025, becoming one of Europe’s most valuable startups
https://www.wsj.com/business/entrepreneurship/vibe-coding-startup-lovable-hits-13-billion-valuation-0c87ff8a?st=zd6W2k&reflink=desktopwebshare_permalink
Rebecca Torrence / Bloomberg:
Sources: AI coding startup Cognition is in early talks with investors to raise $1B+ at a $40B+ valuation, after raising $1B at a $26B valuation in May
https://www.bloomberg.com/news/articles/2026-08-12/ai-startup-cognition-in-new-funding-talks-at-40-billion-value
Tomi Engdahl says:
Frederic Lardinois / The New Stack:
OpenAI launches a ChatGPT desktop app for Linux in preview, supporting ChatGPT Work, Codex, and more; Computer Use outside the in-app browser is not available — On Tuesday, OpenAI launched its ChatGPT desktop for Linux. — Now in preview, the app, which combines ChatGPT, ChatGPT Work …
OpenAI’s ChatGPT/Codex desktop app is now on Linux
OpenAI’s ChatGPT desktop app arrives on Linux with ChatGPT Work, Codex, native packages, an in-app browser, and one notable feature gap for developers.
https://thenewstack.io/openais-chatgpt-desktop-linux/
Tomi Engdahl says:
Tom Wilson / Financial Times:
Researchers say suspected Chinese hackers used open-source AI agents to build an autonomous hacking tool that compromised Taiwanese government websites in July — AI agents ran simultaneous reconnaissance and break-ins in display of new phase of cyberwarfare.
https://www.ft.com/content/7d2ab3e0-9085-48f6-b38a-d90260d58795
Tomi Engdahl says:
Chase DiFeliciantonio / Politico:
OpenAI VP of Global Policy Ann O’Leary says AI policy in the US is anchored in the states and informed by California’s AI transparency law passed in 2025 — SACRAMENTO, California — A senior OpenAI global affairs chief said AI policy is still anchored in the states, and continues to be informed …
OpenAI: AI policy will still be made in the states
https://www.politico.com/news/2026/08/11/openai-ai-policy-will-still-be-made-in-states-01034394
Much AI policymaking will continue to run through the states and be informed by California’s work, a senior OpenAI official said on Tuesday.
Tomi Engdahl says:
Kyt Dotson / SiliconANGLE:
Nvidia releases Nemotron 3.5 Lightning, an open 30B-parameter MoE model, and NeMo Switchyard, an open-source model routing library for AI agents — Artificial intelligence silicon and software giant Nvidia Corp. today announced two new services: a highly customizable Nemotron model and an agentic AI model router named NeMo Switchyard.
Nvidia releases Nemotron 3.5 Lightning and NeMo Switchyard to give enterprise AI capability options
https://siliconangle.com/2026/08/11/nvidia-releases-nemotron-3-5-lightning-nemo-switchyard-give-enterprise-ai-capability-options/
Artificial intelligence silicon and software giant Nvidia Corp. today announced two new services: a highly customizable Nemotron model and an agentic AI model router named NeMo Switchyard.
As enterprises find themselves drowning in artificial intelligence model options, the question is no longer raw power and capability, but fit-for-what-purpose and when. As agents become the norm, the tasks they perform range from sequences of swift, simple tasks to high-complexity reasoning across deep knowledge domains. The former might require small models that can swiftly handle small sorting tasks efficiently and the latter would be best handled by frontier models with high intelligence and reasoning capability.
Nemotron 3.5 Lightning joins the open model family to support high-volume tasks when powering always-on agents. It’s a 30 billion-parameter mixture-of-experts model that Nvidia claims is capable of delivering up to four times the output speed and 30% faster agentic task completion compared with other models in its weight class. It’s also open and customizable, meaning it can be readily post-trained with Nvidia NeMo on an enterprise’s own hardware, with proprietary domain data, tools and workflows to improve accuracy for specialized tasks.
This alone makes the model a powerful backbone workhorse within the family.
Nvidia launched the Nemotron 3 model family in December to act as an open foundation for agentic AI systems. At the time, it consisted of three sizes: Nano, Super and Ultra. The company said Lightning’s differentiator is that it can be specialized quickly.
A company can reproducibly regenerate its own data and specialization in a newly trained model with minimal equipment and cost.
Tomi Engdahl says:
The Information:
Sources: Nvidia is developing a Nemotron 4 model with 1T+ parameters, up from Nemotron 3 Ultra’s 550B parameters but smaller than leading Chinese open models
https://www.theinformation.com/articles/nvidia-trying-develop-worlds-best-open-source-ai-models
Tomi Engdahl says:
Emma Roth / The Verge:
Spotify says it will roll out an “AI Persona” badge in September for profiles that do “not represent a real person” and exclude their music from recommendations
Spotify says it won’t recommend music from ‘AI Personas’
https://www.theverge.com/entertainment/977815/spotify-ai-persona-label-recommendations
Spotify will apply an ‘AI Persona’ badge to profiles that do ‘not represent a real person.’
Tomi Engdahl says:
Anhata Rooprai / Reuters:
IBM and Together AI sign a $240M, multiyear deal to build an AI inference cluster on IBM Cloud, using Nvidia’s HGX B300 systems, to support open-source models
https://www.reuters.com/business/ibm-together-ai-ink-240-million-deal-nvidia-powered-ai-inference-cluster-2026-08-11/
Tomi Engdahl says:
Thomas Claburn / The Register:
Anthropic says new Claude models will embed watermarks in generated text and C2PA metadata in files to comply with the EU AI Act, and it will update past models
Anthropic pledges to embed watermarks to help discern AI slop in sop to EU
https://www.theregister.com/ai-and-ml/2026/08/11/anthropic-pledges-to-embed-watermarks-to-help-discern-ai-slop-in-sop-to-eu/5285792
EU rules cited as reason for effort to trace AI output ancestry
Anthropic will embed watermarks in the text and files generated by future models it launches in the EU, as part of its effort to comply with content and transparency rules in the bloc’s AI Act.
“Generated text will carry embedded watermarks, and generated files will include digitally signed provenance metadata where supported,” the company said in a help document published on Monday.
The AI biz is also working on models it has already released, to add output marking during the transition period allowed under EU law.
“Marking will apply to output from supported models wherever Claude is offered, worldwide,” the company said.
The move may further amplify the appeal of open weight models and alienate Claude customers, who don’t necessarily want consumers of their AI-generated content to know its provenance. In the past, Claude users have expressed frustration with pricing changes, reliability issues, and model safeguards that have hindered legitimate work in the name of safety.
Claude users appear to be skeptical that a text-based watermarking scheme will work. Researchers have already demonstrated that image-based watermarking can be undone.
Anthropic intends to apply marks to output from covered Claude models on the Claude Platform (API), Claude, Claude Code, Claude Cowork, and Claude Tag. This also includes third-party providers of Anthropic models like AWS, Google Cloud, and Microsoft Foundry.
The Ai biz expects to provide details about how people can detect Claude’s marks, as required under EU law, in forthcoming documentation.
Tomi Engdahl says:
Bloomberg:
A profile of Suno, which has been used by more than 100M people since 2023 and has 2M+ paid subscribers, as it faces copyright lawsuits from UMG and Sony Music — Investors are betting the $5 billion company will be the next Spotify. — Mikey Shulman stands in the middle of a dark concert hall …
https://www.bloomberg.com/news/features/2026-08-11/suno-stares-down-universal-and-sony-to-reshape-the-future-of-music?accessToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzb3VyY2UiOiJTdWJzY3JpYmVyR2lmdGVkQXJ0aWNsZSIsImlhdCI6MTc4NjQ4NjQxMCwiZXhwIjoxNzg3MDkxMjEwLCJhcnRpY2xlSWQiOiJUSk1JQ0hSMjRVOU8wMCIsImJjb25uZWN0SWQiOiI4OUM4OTNDMDhGOTQ0NThDQkQwQTQyREY1RDFCOTY0QyJ9.TBMIeS8NPLcnFaiLOvDCXHN0JX7ghM24kRXIhlh_tTY&leadSource=article-gifting
Tomi Engdahl says:
Älypuhelimen video muuttuu 3D-malliksi minuutissa
https://etn.fi/index.php/13-news/19169-aelypuhelimen-video-muuttuu-3d-malliksi-minuutissa
NEC on kehittänyt tekoälytekniikan, joka muodostaa tavallisella älypuhelimella tai muulla yleiskameralla kuvatusta videosta yksityiskohtaisen 3D-mallin jopa minuutissa. Tekniikka perustuu Gaussian Splatting -menetelmään, jonka laskentaa NEC on nopeuttanut omalla tekoälyllään.
Gaussian Splattingissa kolmiulotteinen ympäristö kuvataan suurella joukolla avaruuteen sijoitettuja pisteitä eli gaussisia primitiivejä. Menetelmän etuna on, että sillä voidaan tuottaa fotorealistisia näkymiä suhteellisen kevyesti verrattuna moniin perinteisiin 3D-rekonstruktiomenetelmiin.
NEC ratkaisu analysoi videokuvan visuaalista monimutkaisuutta ja säätää 3D-malliin muodostettavien pisteiden määrää sen mukaan. Paljon yksityiskohtia sisältävillä alueilla pisteitä sijoitetaan tiheämmin, kun taas tasaisilla alueilla niitä tarvitaan vähemmän.
Näin käsiteltävien pisteiden kokonaismäärää voidaan pienentää ilman, että mallin yksityiskohtaisuus NEC mukaan kärsii. Yhtiö kertoo menetelmän lyhentävän 3D-mallin muodostamiseen kuluvan ajan 90 prosentilla tavanomaiseen Gaussian Splatting -menetelmään verrattuna. Nopeimmillaan valmis malli syntyy noin minuutissa.
Toinen keskeinen ominaisuus on videolla näkyvien tilapäisten kohteiden automaattinen poistaminen. Tekoäly voi esimerkiksi tunnistaa kuvausalueella liikkuvat ihmiset ja muut kohteet, jotka eivät kuulu varsinaiseen mallinnettavaan ympäristöön. Järjestelmä päättelee niiden peittämän taustan videon muista kuvista ja täydentää puuttuvat alueet malliin.
Tomi Engdahl says:
Juro Osawa / The Information:
Former Alibaba star researcher Junyang Lin launches Shanghai-based Pragmatik Labs to build digital and physical AI agents; Pragmatik hit a $2B valuation in June
Former Alibaba Researcher Announces New Startup on Digital and Physical AI Agents
https://www.theinformation.com/briefings/former-alibaba-researcher-announces-new-startup-digital-physical-ai-agents
Tomi Engdahl says:
Business Insider:
Sources: former OpenAI Chief Product Officer Kevin Weil is aiming to raise $150M for a new AI science startup, seeking a valuation of at least $750M — Kevin Weil, the former chief product officer of OpenAI, has sought a valuation of at least $750 million for a new AI science startup …
Former OpenAI executive Kevin Weil has sought a valuation of at least $750 million for his new AI science startup
https://www.businessinsider.com/weil-valuation-750-million-for-ai-science-startup-2026-8
Tomi Engdahl says:
Kate Knibbs / Wired:
A look at AI news website RuntimeWire, which costs $100/day to run and “beat” human reporters to OpenAI’s Black Hat disclosure, favoring quantity over quality
Oh Lord, AI Reporters Are Actually Breaking Big News
https://www.wired.com/story/ai-newsrooms-are-breaking-news-now-haha-im-in-danger/
Last week, an AI newsroom beat mainstream journalists—including WIRED—to a story about OpenAI and hacking. It’s just the beginning.
Tomi Engdahl says:
Jagmeet Singh / TechCrunch:
AI code-testing startup Blacksmith raised a $45M Series B led by Peak XV Partners at a $550M valuation, up from $60M after it raised a $10M Series A in 2025
AI code-testing startup Blacksmith’s valuation jumps almost 10x in less than a year
https://techcrunch.com/2026/08/12/blacksmiths-valuation-jumps-10x-to-550m-as-ai-coding-fuels-software-validation/
As AI makes coding dramatically faster, the next big challenge in software development is testing and validating all that code. Blacksmith has raised a new $45 million round to capitalize on that shift.
The Series B, led by Peak XV Partners, values Blacksmith at $550 million, up from the $60 million valuation it was assigned when it raised a $10 million Series A less than a year ago. Existing investors GV and Y Combinator also participated, bringing the startup’s total funding to $58.5 million.
Founded in 2024, Blacksmith helps companies build, test, and verify software before it reaches production. The startup now serves more than 5,000 customers, including Mercury, Supabase, Clerk, Ashby, and Expensify, up from more than 700 customers less than a year ago, co-founder and CEO Aditya Jayaprakash said in an exclusive interview.
The rise of AI coding tools such as Cursor, OpenAI’s Codex, and Anthropic’s Claude Code has made it significantly easier for software teams to generate code, but the quality of AI-generated code is not a given.
“Validating code is still a bottleneck, and it’s an even bigger bottleneck because people are writing even more,” Jayaprakash said.
Tomi Engdahl says:
Dwarkesh Patel / Dwarkesh Podcast:
Q&A with Redwood Research Chief Scientist Ryan Greenblatt on AI R&D, RSI, whether human expert data is bottlenecking progress, token prices, alignment, and more
Ryan Greenblatt – What happens once AI can automate AI research?
A debate about recursive self-improvement.
https://www.dwarkesh.com/p/ryan-greenblatt
Had Ryan Greenblatt on to discuss/debate recursive self-improvement.
This might be the most important question in the world right now – whether within a year or so of achieving human-level intelligence, you slingshot towards having 10s of billions of superintelligences, each of which is dramatically more competent than human experts across all fields.
I’ve historically been skeptical of this possibility. My intuition has been that we will end up significantly bottlenecked by not only compute scaling but human expert data, which I think underlies most of the AI progress today.
If, because of RSI, we got a jump as big as GPT-3 to a Mythos (i.e. 6 years of AI progress) within a single year of achieving AGI, then the thing we get there at the end of that year is definitively and wildly superhuman.
We hashed it out, and I think Ryan made a pretty good case that this kind of speedup is plausible. FWIW, Ryan’s median for when we automate AI R&D is 2031.
We then discussed the alignment implications of this scenario. Who should these superintelligences be aligned to? In the future, our capacity to steward our votes and our capital, and to make sense of what’s happening in the world, will all be titrated by superintelligences. And I worry that specs like the Claude Constitution are not shaping these ASIs to truly be my personal advocates and guardian angels.
And can we get them aligned to anything in the first place? Ryan and I had a long debate about whether the kind of reward hacking we saw with the OAI/Hugging Face hack extrapolates to superintelligences that would team up to literally take over the world.
The first piece of advice you get when you’re learning to drive is that it will go much smoother if you look at the horizon instead of directly in front of your tires. And so it is with the trajectory of AI. Hope you enjoy!
Tomi Engdahl says:
The math is not looking good. https://trib.al/ktHHvio
Calculated Risk
Protests Against Data Centers Are Now Threatening $130 Billion of Big Tech’s Crucial Investments
The math is not looking good.
https://futurism.com/future-society/ai-data-center-finances-protests-opposition-social-risk?fbclid=IwdGRjcATqI-JjbGNrBOojpnBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEe5B02iBKWa31CM7I_OX-weuUFHIPcsSZukcUARZIgCmCcX58JQT0SKBBt5sU_aem_vSvRjF9JeXUHGkf_XMG4Gg
For protestors rising up against the data centers undergirding the AI boom, the math is simple: wherever they sprout, the facilities make frightfully poor neighbors — inflating utility prices, discharging hazardous waste, and blasting horrid noise at all hours of the night.
For data center developers, there’s a different calculation to be made: namely, one of supply and demand around the seemingly infinite drive for computing power.
Against the backdrop of an industry measured in the trillions of dollars, a few scattered protests at city hall may seem inconsequential. Yet as more and more local campaigns arise in opposition to data centers, the collective financial implications are becoming impossible to ignore.
According to new reporting by Reuters, which indexed data compiled by the research firm Data Center Watch, there are now hundreds of billions of dollars exposed to the growing risk of local opposition.
In the first three months of 2026 alone, at least 75 separate data center projects faced some kind of organized opposition at the local level. Together, those 75 developments represent a combined $130 billion worth of investments.
The funders of those data centers include major banks, but also more than a few private equity firms, which are sure to notice as the social risk to their data center investments climb.
Simply put, the potential that any given data center could be cancelled due to local opposition is rising, a sign that organized efforts against data centers are becoming more than the sum of their parts.
Tomi Engdahl says:
Uusi tutkimus: näin työnantajat käyttävät tekoälyä rekrytoinnissa
https://duunitori.fi/tyoelama/rekrytointitutkimus-tekoaly-rekrytoinnissa-2026?utm_medium=cpc&utm_source=Facebook_Mobile_Feed&utm_campaign=smartly_b2b_referenssi&utm_content=b2b_articlefeed&utm_id=6952371942495&fbclid=IwdGRjcATqJNRwZG9mBWV4dG4DYWVtATAAYWRpZAAABlK5sdm3c3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEeFkGAx0yboMYHBZNQsiPZATl2jG9sJGZQvQeSaOVUR8rwaEzmYFsDASU9yfA_aem_ek_BxT6zXXFLPRDZ__8qNw&utm_term=6919371858295
Tekoälyn hyödyntäminen rekrytoinnissa edellyttää avoimuutta: ”Selkeä tekoälyetiikka on välttämätön, jotta työnantajat voivat välttää mainehaittaa ja rakentaa luottamusta”, sanoo Duunitorin johtava asiantuntija Lauri Vaisto. Kuva: Niko Raappana
Vasta noin neljäsosa työnantajista hyödyntää tekoälyä rekrytoinnissa. Duunitorin tuore rekrytointitutkimus kertoo yleisimmät tavat käyttää tekoälyä ja miten työnantajat suhtautuvat siihen. Asiantuntija vertailee tuloksia myös työnhakijoiden tapoihin ja asenteisiin.
Suomalaiset työnantajat käyttävät edelleen tekoälyä rekrytoinnissa melko vähän ja varovaisesti. Duunitorin tuoreen Kansallisen rekrytointitutkimuksen mukaan vain 26 prosenttia työnantajista hyödyntää tekoälyä rekrytoinnissa.
Miten työnantajat hyödyntävät tekoälyä rekrytoinnissa?
Tällä hetkellä työnantajat käyttävät tekoälyä rekrytoinnissa ennen kaikkea tekstien tuottamiseen ja muokkaamiseen, ei vielä laajasti arvioinnin tai päätöksenteon tukena.
Yleisimmät tekoälyn käyttötavat rekrytoinnissa
Ilmoitustekstin luominen tai muokkaaminen (55 %)
Työtehtävän kuvauksen tiivistäminen tai selkeyttäminen (55 %)
Viestipohjien tai vastausviestien luonnostelu (47 %)
Some- tai kampanjatekstien ideointi ja tuottaminen (40 %)
Haastattelukysymysten generointi (32 %)
”Tekstien luonnostelu on vielä aika alkeellinen hyödyntämisen muoto. Tekoälystä saisi enemmän irti esimerkiksi työvoiman tarpeen suunnittelussa ja työtehtävien muotoilussa”, Vaisto sanoo.
Tekoälyhakemukset haastavat työnantajia
Työnantajat ovat vielä varovaisia, mutta työnhakijoiden aktiivisempi tekoälyn käyttö ja moninaiset tavat hyödyntää sitä vaikuttavat voimakkaasti rekrytointiin.
Lähes puolet (47 %) tutkimukseen vastanneista työnantajien edustajista kokee, että tekoälyllä tehdyt hakemukset pakottavat uudistamaan rekrytointiprosessia. Rekrytointi tarvitsee siis uudenlaisia tapoja arvioida osaamista ja soveltuvuutta.
”Nykyajassa monia rekrytoijia piinaavat tekoälyllä tuotetut geneeriset ja tasalaatuiset hakemukset, joita on vaikea erottaa toisistaan”, Vaisto kuvaa.
Tekoäly voi auttaa esimerkiksi muovaamaan omaa hakemusta vastaamaan työpaikkailmoituksen vaatimuksia. Hakemuksen täytyy kuitenkin pysyä totuudenmukaisena.
”Tekoälyn käyttö voi pahimmillaan tehdä hakemuksista harhaanjohtavia tai jopa valheellisia. Aiempaa useammin voi käydä niin, että haastatteluun valikoituu hakijoita, joilla ei ole todellisia edellytyksiä suoriutua tehtävässä. Se haaskaa sekä työnhakijan että työnantajan aikaa.”
Viime syksyn työnhakututkimuksessa 36 prosenttia työnhakijoista piti tekoälyn käyttöä työnhaussa “hieman epäreiluna huijaamisena”, kun taas nyt työnantajista samoin ajatteli vain 28 prosenttia. Työnantajat pitävät myös hyödyntämistä työnhakijoita useammin “sallittuna ja fiksuna tapana saada etua” tai “välttämättömänä, jotta pysyy mukana kilpailussa”.
Tekoälyn käytöstä pitää kertoa avoimesti
Avoimuus tekoälyn käytöstä on tärkeää työnantajille. 71 prosenttia vastaajista ajattelee, että työnhakijalle pitäisi kertoa, jos tekoälyä hyödynnetään hakemusten läpikäynnissä.
Työnhakijat peräänkuuluttavat läpinäkyvyyttä vielä useammin. Duunitorin työnhakututkimuksessa 74 prosenttia vastaajista halusi työnantajan kertovan tekoälyn käytöstä rekrytoinnissa.
”Jos tekoälyä käytetään rekrytoinnissa, on oikein kertoa siitä ja käyttötavoista. Läpinäkyvyyden kulttuuri tukee tekoälyn kestävää ja eettistä käyttöä sekä lisää luottamusta”, Vaisto sanoo.
Myös EU-lainsäädäntö säätelee tekoälyn käyttöä rekrytoinnissa ja sitä, mistä pitää tiedottaa hakijoille. Elokuussa 2026 alkaen sen vaatimukset tiukentuvat entisestään.
Miten tekoäly vaikuttaa työpaikkoihin?
Enemmistö työnantajista ei pelkää työpaikkojen puolesta. 55 prosenttia vastaajista arvioi, ettei tekoäly vähennä työpaikkoja heidän toimialallaan seuraavan viiden vuoden aikana.
Alakohtaiset erot ovat kuitenkin merkittäviä. Työpaikkojen voimakkaaseen vähenemiseen uskotaan erityisesti aloilla, joilla korostuu informaation käsittely ja muokkaus, kuten rahoitus-, viestintä- ja ict-aloilla. Esimerkiksi rakentamisen, kaupan ja koulutuksen aloilla uskotaan vähemmän työpaikkojen katoamiseen
37 prosenttia työnantajista pitää tekoälytaitoja organisaatiossaan tärkeinä tai erittäin tärkeinä. Niiden merkitys korostuu samoilla aloilla, joilla työnantajat arvelevat tekoälyn vähentävän työpaikkoja: rahoitus-, viestintä- ja ict-aloilla.
”Näillä aloilla selvästi nähdään työtehtävissä tehostamisen mahdollisuuksia. Ihmisiä tarvitaan jatkossakin, mutta roolit, työtehtävät ja työvälineet voivat muuttua”, Vaisto summaa.
Tomi Engdahl says:
https://duunitori.fi/tyoelama/tekoalyn-kaytto-tyonhaussa-tutkimus/?fbclid=IwVERDUATqJp9wZG9mBWV4dG4DYWVtATAAYWRpZAAABlK5sdm3c3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEeFkGAx0yboMYHBZNQsiPZATl2jG9sJGZQvQeSaOVUR8rwaEzmYFsDASU9yfA_aem_ek_BxT6zXXFLPRDZ__8qNw&utm_source=Facebook_Mobile_Feed&utm_medium=cpc&utm_campaign=smartly_b2b_referenssi&utm_term=6919371858295&utm_content=b2b_articlefeed&utm_id=6952371942495
Tomi Engdahl says:
https://duunitori.fi/tyoelama/reilu-rekrytointi-tekoaly-eu?fbclid=IwVERDUATqJs5wZG9mBWV4dG4DYWVtATAAYWRpZAAABlK5sdm3c3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEeFkGAx0yboMYHBZNQsiPZATl2jG9sJGZQvQeSaOVUR8rwaEzmYFsDASU9yfA_aem_ek_BxT6zXXFLPRDZ__8qNw&utm_source=Facebook_Mobile_Feed&utm_medium=cpc&utm_campaign=smartly_b2b_referenssi&utm_term=6919371858295&utm_content=b2b_articlefeed&utm_id=6952371942495
Tomi Engdahl says:
“PLEASE DO NOT SHARE THIS DOC WIDELY.” https://trib.al/LhPGR6L
Bottomless Pit
Internal Google Document Reveals That Its HR AI Has Been Throwing Résumés From Qualified Applicants Straight Into the Trash
“PLEASE DO NOT SHARE THIS DOC WIDELY.”
https://futurism.com/future-society/google-hr-resume-applicants-deepmind-ai-hiring?fbclid=IwdGRjcATqLI9jbGNrBOosenBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEeZjUsZkySfwO-A35Cz4uCs_NWzLvu9FObz2dprQg7LHBu2YDzmpjoFxdnJw8_aem_P05DgAq39mir1vdMzJiIpA
Bad news for anyone seeking a job in this AI-infested hiring hellscape: not even Google’s top AI lab can figure it out.
That’s according to an HR memo viewed by Bloomberg, encouraging job-seekers to fill out a special AI-proof form on top of their standard application so that a “real human” will know they applied.
The document, which contains the delicious disclaimer “PLEASE DO NOT SHARE THIS DOC WIDELY,” is ironically the product of Google DeepMind’s AGI Safety and Alignment Team. Taken at face value, it pretty blatantly admits that whatever AI-integrated hiring software the lab uses to review candidates has been dumping CVs straight into the garbage.
“We have an applications system with a non-trivial probability your CV will be screened out incorrectly or take too long to reach us,” the memo explains. “Filling out this form makes sure that a real human on the team will get to see your application.”
Even in the face of the memo, a spokesperson for Google’s DeepMind project insisted to Bloomberg that the company’s AI hiring software is working just fine.
It’s safe to say AI slop has completely obliterated the digital hiring ecosystem millions depend on to find work — and if Google’s top AI minds can’t fix it, what hope do the rest of us have?
Tomi Engdahl says:
Financial Times:
Sources: Anthropic investors expect it to float at a $2T+ valuation after an October IPO and to hit $100B to $120B in annualized revenue by the end of 2026
https://www.ft.com/content/840ac156-af1c-4a82-b260-ae791072fcfa
Tomi Engdahl says:
Juro Osawa / The Information:
DeepSeek launches V4-Pro, its most advanced model that rivals Kimi K3 on some benchmarks at much lower prices, costing $0.44/1M input and $0.87/1M output tokens
https://www.theinformation.com/briefings/deepseek-releases-flagship-v4-pro-model-challenge-kimi-k3
Tomi Engdahl says:
Saritha Rai / Bloomberg:
A look at workers in India who are paid extra to wear devices that capture first-person video of factory and other work tasks for use as AI robot training data
https://www.bloomberg.com/news/features/2026-08-12/thousands-of-india-workers-are-helping-ai-firms-train-robots-to-replace-them?accessToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzb3VyY2UiOiJTdWJzY3JpYmVyR2lmdGVkQXJ0aWNsZSIsImlhdCI6MTc4NjU5MTAzMywiZXhwIjoxNzg3MTk1ODMzLCJhcnRpY2xlSWQiOiJUSk9EMEhOM04wOTIwMCIsImJjb25uZWN0SWQiOiJDNTc5RDIwMDZBQjQ0RjRDODkwMTU0M0U0ODMxNkJCNiJ9.8jIbwh52D-I5HP12Uf8C3s9FI-QEyGy6Qq7IDsvdrOY&leadSource=article-gifting
Tomi Engdahl says:
Counterpoint Research:
In Q2 2026, server-led eSSDs reached 48% of NAND flash shipments as AI workloads shifted from training to inference, driving 5x YoY industry revenue growth — – AI inference workloads drove enterprise SSDs to 48% of global NAND shipments in Q2 2026, nearly double the 26% share a year earlier.
Server-Led eSSDs Hit 48% of NAND Shipments; YMTC Enters Global Top Three
https://counterpointresearch.com/en/insights/server-led-essds-hit-48-percent-of-nand-shipments
Tomi Engdahl says:
xAI:
SpaceXAI releases Grok 4.6, saying it matches GPT-5.6 Sol on the Artificial Analysis Intelligence Index, and prices it at $2/1M input and $6/1M output tokens — Grok 4.6 builds on Grok 4.5 with a particular focus on long-running agents and more ambitious interactive and visual work. — Try for free
https://x.ai/news/grok-4-6
Tomi Engdahl says:
Hugo Lowell / Wired:
Sources: the White House is expected to expand its AI oversight framework in the coming months to cover open models once they reach frontier capabilities — Open models may soon be added to an updated AI framework, sources tell WIRED, as the White House continues to grapple with how to regulate …
The White House Is Going to Expand Its AI Policy
https://www.wired.com/story/the-white-house-is-going-to-expand-its-ai-policy/
Open models may soon be added to an updated AI framework, sources tell WIRED, as the White House continues to grapple with how to regulate a technology it has tried not to regulate.
Tomi Engdahl says:
Reuters:
AI chip designer Cerebras reports Q2 revenue up 74% YoY to $180M, below $194.23M est., and raises its annual revenue and gross margin forecasts; CBRS drops 14%+ — Cerebras Systems (CBRS.O) raised its annual revenue and gross margin forecasts on Wednesday, buoyed by robust demand for its chips …
https://www.reuters.com/business/cerebras-raises-annual-targets-strong-ai-chip-demand-2026-08-12/
Tomi Engdahl says:
Mistral AI Blog:
Mistral says its platform will support third-party open models, starting with Z.ai’s GLM-5.2, and run them on the same infrastructure as its own models — At Mistral, we believe every enterprise and country must be in control of the models it uses, choose where the intelligence runs …
In-region inference, open models, and new European infrastructure for sovereign AI.
https://mistral.ai/news/regional-inference-open-models-new-compute/
Tomi Engdahl says:
Alex Townsend:
Mathematicians say a neurosurgery resident used ChatGPT, powered by GPT-5.6, to solve Crouzeix’s conjecture, a major open problem in numerical linear algebra — On July 30, 2026, the first author asked ChatGPT 5.6 to solve Crouzeix’s conjecture, as he had been routinely doing for the preceding year.
https://alextownsend.net/essays/SIAMNews_CrouzeixConjecture.pdf
Tomi Engdahl says:
Wall Street Journal:
Sources: Demis Hassabis pitched a new independent industry AI safety entity, modeled on the IAEA, to top Trump officials before stepping down as DeepMind CEO — Demis Hassabis discussed the proposed new entity with heads of other AI labs and Trump administration officials including Scott Bessent
https://www.wsj.com/tech/ai/deepminds-hassabis-pitched-ai-oversight-body-before-shake-up-e25b3f71?st=nNBiWk&reflink=desktopwebshare_permalink
Tomi Engdahl says:
Bloomberg:
Rapidly advancing AI tools have created investor uncertainty and fear around the SaaS business model and the private equity and credit built on top of it — Now the entire business model is at risk — ON WALL STREET, there’s a disaster scenario known as the “SaaSpocalypse” that goes something like this.
AI Looms Over Software Companies — and the Investors Who Piled Into Them
Buyout funds and lenders were drawn to reliable revenue and low costs. Now the entire business model is at risk
https://www.bloomberg.com/graphics/2026-ai-private-equity-software/?accessToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzb3VyY2UiOiJTdWJzY3JpYmVyR2lmdGVkQXJ0aWNsZSIsImlhdCI6MTc4NjU5NTQ3NCwiZXhwIjoxNzg3MjAwMjc0LCJhcnRpY2xlSWQiOiJUSk5PMEhSMjRVOTcwMCIsImJjb25uZWN0SWQiOiIwNEFGQkMxQkYyMTA0NUVEODg3MzQxQkQwQzIyNzRBMCJ9.MAS13Z32XR87iPMHAAssBgMkTLeIh7jVrTzrtPYF0FQ&leadSource=article-gifting
Tomi Engdahl says:
Ellen Milligan / Bloomberg:
Sources: the UK government is planning to regulate the use of AI in gene synthesis to prevent terrorists and other bad actors from using AI for bioweapons
https://www.bloomberg.com/news/articles/2026-08-12/uk-plans-safeguards-to-stop-terrorists-using-ai-for-bioweapons
Tomi Engdahl says:
Mike Wheatley / SiliconANGLE:
Google DeepMind launches SL2T, a multilingual sign-language-to-text model debuting on the Pixel 11 in Gboard and Live Transcribe, first for ASL to English text
https://siliconangle.com/2026/08/12/google-debuts-sl2t-ai-model-thats-designed-understand-sign-language/
Tomi Engdahl says:
Victoria Song / The Verge:
Google unveils the $399 Pixel Watch 5 with a satin pyrite case finish, offline Gemini, proactive AI suggestions, better GPS maps, and insulin resistance trends
https://www.theverge.com/tech/978094/pixel-watch-5-hands-on-made-by-google-gemini-wearables-smartwatch
Tomi Engdahl says:
Kenrick Cai / Reuters:
Sources detail moves behind Google’s AI reshuffle; Sergey Brin urged key staff to go all in on Gemini, and some teams shifted from DeepMind to corporate Google
https://www.reuters.com/world/inside-google-executive-moves-that-led-its-big-ai-reshuffle-2026-08-12/
Tomi Engdahl says:
Belle Lin / Wall Street Journal:
AT&T says open models currently power ~25% of its overall AI usage, and expects that to rise to 70%-80% over time; AT&T uses an average of 45B AI tokens per day
Why AT&T Is Betting Big on Open-Weight AI
The telecom company is staking its future on open models, both to control token cost and protect its proprietary data
https://www.wsj.com/cio-journal/why-at-t-is-betting-big-on-open-weight-ai-a0ea03b1?st=t7aCLG&reflink=desktopwebshare_permalink
Tomi Engdahl says:
Laurie Chen / Reuters:
Lenovo reports Q1 revenue up 43% YoY to $26.94B, its highest quarterly revenue growth in five years, as AI-related revenue rose 60% YoY to $9.3B, 35% of total
https://www.reuters.com/world/china/chinas-lenovo-posts-43-jump-q1-revenue-2026-08-13/
Tomi Engdahl says:
https://etn.fi/index.php/13-news/19179-tekoaelyagentti-saeaestaeae-selvaesti-hr-tiimin-aikaa
Tomi Engdahl says:
Todd Bishop / GeekWire:
Microsoft begins merging its consumer and commercial Copilot apps into a single app, with a mobile and web rollout in mid-August and desktop in mid-September
Microsoft starts merging its Copilot consumer and business apps in advance of ‘Super App’ rollout
https://www.geekwire.com/2026/microsoft-starts-merging-its-copilot-consumer-and-business-apps-in-advance-of-super-app-rollout/
Microsoft is starting the process of combining its consumer and business Copilot apps into one, laying the structural foundation for an upcoming “Super App,” and trying to turn the company’s sprawling artificial intelligence brand into a unified product that people actually use.
The move is part of the company’s effort to better compete with ChatGPT, Gemini and Claude, attempting to turn its legacy in workplace technology and cloud infrastructure into a stronger position in AI apps and agents.
It also recognizes the blending of business and personal lives, and the reality that many people use the same AI assistants for both home and work.
The Copilot unification, detailed Thursday in support documents from the company, will take place gradually over the next several weeks, bringing major changes for some existing users.
Several features of the consumer app are going away starting on Aug. 18, including Copilot Podcasts, Group Chat and Deep Research. Also disappearing is Mico, the expressive blob introduced less than a year ago to accompany the consumer Copilot’s voice mode, although Microsoft expects it to live on in some of Copilot’s education features.
Commercial users will see far less change, with Microsoft calling them mostly cosmetic. For example, the Microsoft 365 Copilot app will be known simply as Microsoft Copilot, with a new icon and a new web address.
Tomi Engdahl says:
https://futurism.com/artificial-intelligence/openai-escaped-models-rampaging-extensively?fbclid=IwVERDUATqvkJwZG9mBWV4dG4DYWVtAjEwAHNydGMGYXBwX2lkDDM1MDY4NTUzMTcyOAABHiS4tAfUkSYWI1hDf7Ftiz0lKYCywHukW6NBzzAqyfvBilOColtwmW2Wv75z_aem_TgBdxw71UFwQHXwi1pz5vg
Tomi Engdahl says:
500 jurisdictions restrict data centres. 71% of Americans oppose them.
Meta answered with a $1B fund for those towns.
Teachers in one Louisiana parish received $50,000 bonuses.
That money came from tax on Meta’s construction spending.
Median home prices there nearly tripled since November 2024.
The tax stops in 2030, and the data centre stays.
Read more on TNW: https://thenextweb.com/news/meta-1bn-future-is-for-everyone-fund-data-centre-communities
Tomi Engdahl says:
“Am I just interacting with bots here?” https://trib.al/mR8gp2G
TruantGPT
College Kids Are Using AI Agents to “Take” Entire Online Classes for Them by Logging Directly Into the Course Management Software
“Am I just interacting with bots here?”
https://futurism.com/artificial-intelligence/college-kids-ai-agents-cheat-online-courses?fbclid=IwdGRjcATrDhhjbGNrBOsOAHBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEe4tl_1s1SaWngMv1XKC1eJ15YA1KBTE29QX-c9e56_B7dX88h-DBChz6P5v4_aem__dIgCpNOcVhMW9EyFsit4w
With the rise of agentic models, why stop at using chatbots to look up answers? Some students are directing AI agents to “take” entire online courses for them, letting the software run in the background while they focus on better uses of their time, like doomscrolling on their phone or gaming.
The New York Times unpacked the trend in a recent story, and it’s a testament to how extreme AI-enabled cheating has become, but also of the perils of getting an education in a virtual environment instead of a physical one. Professors can’t rely on supervised exams and oral presentations in online courses like they’re starting to shift to in-person ones.
Since everything is behind the screen, students can ask an AI agent to log into learning platforms like Canvas and Blackboard and complete quizzes for then, watch lecture videos, write papers, and even pose as the student and participate in discussions, a type of assignment in which they’re expected to chat with classmates and sometimes the professor about assigned reading.
AI companies are doing little to stop this.
The NYT found that none of the three most popular chatbots with students — ChatGPT, Gemini, and Grammarly — would refuse requests to write an entire paper on a student’s behalf. And they also don’t stop their models from logging into platforms like Canvas and Blackboard, and have ignored the request from educators that their models should identify themselves while they’re used on there.
The reasoning can sound quite specious. Perplexity, the company behind an AI web browser, told the NYT in a statement that requiring AI agents to identify themselves on learning platforms “would put the student’s privacy and security at risk.”
Professors feel powerless to stop the trend. Often, their university may have a partnership or deal with an AI company that provides access to a custom version of its models. This sends a mixed message to students: is AI encouraged, or verboten? Some professors will turn a blind eye AI use, and others will heavily punish it, but as a whole, it’s every instructor for themselves.
The University of Chicago Law School recently banned using phones, tablets, and laptops in class for freshman-level courses, as part of its new “AI strategy.” Princeton University dropped its over century-old Honor Code tradition which let students take their exams without supervision, after an AI cheating scandal rattled the Ivy League institution.
Tomi Engdahl says:
Vibe Educating
Homeschool Parents Are Planning Lessons With ChatGPT
“So I just make my own curriculum, and sometimes I’ll just use, like, ChatGPT.”
https://futurism.com/artificial-intelligence/homeschool-parents-chatpgt-ai-chatbots-lesson-plans-education?fbclid=IwVERDUATrDuNwZG9mBWV4dG4DYWVtAjEwAHNydGMGYXBwX2lkDDM1MDY4NTUzMTcyOAABHm8_qYjzMBrzvm-ZbkljLls78ZEPHFGwb4MY9z1qhTnhvpkhSXXaCgvwhJx5_aem_SsWN-v9lNXRawUDfCpfdsQ
As if the practice of homeschooling wasn’t fraught enough already, parents are now bragging about using large language models (LLMs) like ChatGPT to school their kids.
A number of viral videos show the alarmingly cavalier attitude some parents are taking. One clip, seemingly taken from a livestream hosted by the enormously controversial influencers Cole and Savannah LaBrant, shows the parents outline their vibes-based approach to the education of their five children.
Tomi Engdahl says:
AI power users are furious Anthropic’s new watermarks will unveil their secret
“The stigma. Jesus, the stigma.”
https://cybernews.com/ai-news/anthropic-watermark-ai-power-users/?utm_source=cn_facebook&utm_medium=social&utm_campaign=cybernews&utm_content=post&source=cn_facebook&medium=social&campaign=cybernews&content=post&fbclid=IwVERDUATrGZFwZG9mBWV4dG4DYWVtAjEwAHNydGMGYXBwX2lkDDM1MDY4NTUzMTcyOAABHkZnzC-S6KyhKXmTqxygsofesEiOIntCD1aTCjCDtMTZ60E4qDeMQDQ2GmLP_aem_juizULfnTkozW3yZzBwJGw
Tomi Engdahl says:
“That statement is remarkably pathetic for the CEO of any company to be making.” https://trib.al/61ZAOOF
Game Dev CEO Accused of Replacing Writers With AI is Now Completely Crashing Out
“That statement is remarkably pathetic for the CEO of any company to be making.”
https://futurism.com/artificial-intelligence/game-developer-accused-firing-writer-ai?fbclid=IwdGRjcATreWdjbGNrBOt5Q3Bkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEelCKYLL14oC2-588oCjLJE1LC3zpKOVs3j-NqgeWM3ZgFtF8aANY2qnIRSiA_aem_y7W5s-uGACHytMadjFYpZw
Saber, the developer behind the upcoming Rideshare “Stimulator” video game, is being accused of replacing its writers with AI.
The accusation was made Tuesday by Stella Sacco, who says she was fired back in December 2023 while the game was still under development.
“I was lead writer on this one! And Saber replaced me with ChatGPT midway through development,” Sacco wrote on Bluesky.
“All the passenger voices were AI too,” she added. “Either they changed direction at some point or they’re not disclosing it on Steam.”
Initially, Saber CEO Matthew Karch denied the allegations in unremarkable fashion.
“Neither Saber nor Unigine have replaced any writers with AI,”
Tomi Engdahl says:
Despite outcry from musicians, AI slop is creeping into the charts as record labels scramble to adapt to a new normal where hits can be made at the click of a button
Music
‘I feel like I’m at war’: are we losing the battle against machine-made music?
https://www.theguardian.com/music/ng-interactive/2026/aug/13/ai-music?CMP=fb_gu&utm_medium=Social&utm_source=Facebook&fbclid=IwdGRjcATrgE5jbGNrBOuACXBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEesi1OhR7aXelAnqDZyMYvGr1MyE0NUaTZDxqmBNxeScdfLjOqbP2XoWRQAiI_aem_DkKo5OnXx3FXWJXqvrTEMg#Echobox=1786632295
Despite outcry from musicians, AI slop is creeping into the charts as record labels scramble to adapt to a new normal where hits can be made at the click of a button
This year, the battle for song of the summer has been eclipsed by a much more complicated – some would even say disturbing – debate. That’s because we find ourselves asking not “What’s the song of the summer?” but rather “Is the song of the summer even real?”
Among the top contenders for the title is Fenix Flexin’s Rubberz, a single released in June that has ascended to No 58 on the Billboard Hot 100 and racked up more than 35m Spotify streams. It’s not the sort of fare Fenix usually cooks up.
The song has drawn comparisons to Morrissey, but it more closely resembles Men at Work’s Down Under, or a Weird Al Yankovic parody of Men at Work. It’s pretty awful. But more importantly, it has an uncanny quality to it. It sounds off.
Almost immediately after it came out, skeptics accused Fenix of employing artificial intelligence to create the track, if not entirely at least partly. He and the song’s credited producer, Purps on the Beat, initially denied it, with Fenix insisting that he’d just used Auto-Tune and a phoney British accent. The kerfuffle culminated this month when indie DJ-producer Medasin posted a video that he said proved that Rubberz had been made using the free generative music tool Treblo.
Medasin then captured himself giving Treblo prompts to pump out his own track. Its sound and lyrics were eerily close to those of Rubberz. Fenix rejected Medasin’s claims
A few days later, Fenix finally admitted to using AI to make Rubberz, writing: “never said I didn’t use AI, i said it had nun to do w recording process.”
This is in line with the findings of the platform’s own open-source classifier, Was This Made With Treblo?, which finds Rubberz to be “very likely Treblo” according to Wired. The tool hasn’t been independently reviewed, but the Treblo co-founder Ryan Tremblay confirmed to the Guardian that the classifier returns a very high probability score (“higher by far than any false positive”) for Rubberz, indicating that Treblo generated the song. “We built Treblo for everyone, from normal people experimenting at home to charting artists looking for new sounds,” Tremblay said. “Some artists appear to have used our model to find a sound that millions of people connected with, and that’s exciting.” When reached by the Guardian, Fenix’s representative declined to comment.
he uproar over Rubberz coincided with another major development in music in recent weeks. On 29 July, several record companies, including “the big three” – Universal Music Group, Sony Music and Warner Music Group – issued a proposal calling for global music charts to disqualify AI-generated tracks from consideration if they did not meet certain criteria. According to their suggested guidelines, a song could enter the charts only if it was properly authorized, lawful and substantially human-made, and does not raise concerns of streaming or chart manipulation. The issue, as the record companies stated in a press release, is that a significant number of AI-generated tracks hitting streaming services like Spotify have used tools trained on artists’ music without their consent and are often linked to fraudulently boosted streaming numbers.
At the same time, all the major record labels have announced partnerships with the likes of Nvidia, Spotify and Stability AI to develop AI music tools, with BMG announcing a partnership with the AI music-creation platform Suno this week.
While Rubberz is the first AI-generated single to crack the Hot 100, it is not the first to land on the Billboard charts. In November, the AI act Breaking Rust hit No 1 on the country digital song sales chart with Walk My Walk, a track credited to a person who goes by Aubierre Rivaldo Taylor. That same month, the AI-powered R&B singer Xania Monet – whose name instantly conjures actual human R&B singers Victoria Monét and Janelle Monáe – became the first AI act to enter a Billboard radio airplay chart, later climbing to No 1 on the R&B digital song sales chart. An avatar that the Mississippi poet Telisha “Nikki” Jones invented with Suno, she reportedly landed a multimillion-dollar record deal last fall.
After Xania Monet’s milestone, Billboard reported that a total of at least six AI-generated or AI-assisted artists had debuted on its various charts in 2025. The publication admitted, however, that the tally could be higher because it has become harder and harder to determine which songs have used AI, and just how much. This was validated a week later when a study by the French streaming platform Deezer and research firm Ipsos revealed that 97% of its participants couldn’t tell the difference between AI-generated music and human-made music.
Jack Antonoff recently called AI-music makers “godless whores”. Billie Eilish, Bad Bunny, Kate Bush, Annie Lennox, Nick Cave, Sting, Stevie Wonder and Paul McCartney have all protested against the heavy use of generative AI in music.
And why shouldn’t they? Yes, dictating what one wants to create to an app requires a sliver of inspiration and imagination, but it pales in comparison with the blood, sweat and tears artists pour into music of their own – music that hasn’t been trained, often without permission, on reams of pre-existing copyrighted work.
A recent report published by the music and entertainment insights company Luminate showed that listeners, especially members of gen Z and gen Alpha, are increasingly uneasy with AI-generated songs. The study found that 44% of US respondents felt less inclined to listen to a song if it involves generative AI. “Consumers are net negative,” a Luminate analyst told NPR in May. “People are more likely to feel uncomfortable than to feel comfortable with AI use.”
Universal, Sony and Warner are not demanding an outright ban on AI music from charts and streaming services. Though all three sued the AI music generators Suno and Udio in 2024.
Björk wrote in a 2025 post on X. “If there is no soul in tomorrow’s music made by AI, it is because no one put it there … Anything that is mass-manufactured without the attention of creativity is that way, AI or not. So it is not about the tool – it is what you do with it.”
There is hope. In January, Bandcamp banned all music fully or substantially created by AI from the platform. Though Tidal allows fully AI-generated songs on its app if they are not linked to fraud or artist impersonation, they cannot collect streaming royalties or direct-to-fan sales revenue, and get tagged with an “AI” label. A coalition of music industry organizations, including the Grammys and the Recording Industry Association of America, recently announced that it was taking steps to notify listeners of AI use in recordings. This month, Spotify said that it would label AI artists with an “AI Persona” tag and exclude these artists from its personalized recommendations, while its optional “AI Credits” feature allows artists to note whether AI was used in a song’s creation.
2025 survey results showed that 80% of respondents agreed that entirely AI-generated music should be clearly labeled to listeners, while 52% thought entirely AI-generated songs should not be included alongside human-made songs in the main charts.
Author and journalist CJ Farley echoed this sentiment in a recent column for Time. He dismissed the terms “AI artists” and “AI musicians”, suggesting that we instead refer to AI releases as “AI products”. Then he took it a step further, arguing that these products should be confined to their own chart “away from human musicians with real lives and with real financial obligations”.
If Rubberz is a joke, Fenix Flexin might have been trying to see exactly how much he could get away with. (That would at least explain why the song is such dreck.)
Tomi Engdahl says:
https://www.facebook.com/share/p/1HcgUK3MxL/
A California data center reportedly used about 29 million gallons of water in just 15 months, raising concerns among nearby residents and farmers about pressure on local supplies.
Families in the area reported lower water pressure as the facility expanded its operations.
The issue highlights a growing challenge for AI infrastructure in dry parts of the United States.
Large data centers need enormous amounts of electricity, and some cooling systems can also require substantial amounts of water.
In agricultural regions, that can create direct competition between industrial demand and the water needed for homes, farms and livestock.
The concern is especially serious in California, where drought, groundwater depletion and rising temperatures already place pressure on many communities.
Supporters of data center development point to jobs, investment and digital infrastructure.
Critics argue that projects should not be approved without clear information about how much water they will use and whether local supplies can support that demand.
As artificial intelligence continues to expand, water is becoming almost as important as electricity when deciding where large data centers should be built.