Technology Trends 2027: 15 AI Shifts That Will Define Next Year

These are the technology trends 2027 will actually be built on, sorted by what is already scheduled, what is still a forecast and what is mostly hype. However, most “top 15” lists for next year mix fusion, 6G and flying cars into one pile. So we did the opposite. We read the official roadmaps, the new analyst reports and the energy data, then kept only trends with a date, a number or a product behind them. Finally, each of the 15 ends with our call: Real, Watch or Hype risk.

Two reports frame the year. Gartner published its Top Strategic Technology Trends for 2027 on October 20, 2026, and it is almost entirely about AI. A few weeks earlier, the State of AI Report 2026 showed something more unsettling: in August, Anthropic’s own model led 26% of measured AI research work inside the company, up from under 1% in February. AI is starting to help build AI, and that thread runs through everything below.

The model race is now a three-lab contest between Anthropic, OpenAI and Google, according to the State of AI Report 2026. The more important trend for 2027 is price. The cost of hitting a fixed benchmark score has fallen roughly 47% every quarter since 2023, about 13 times cheaper per year (Epoch AI data).

That is also why the 2026 launches came in tiers. OpenAI shipped GPT-6 Astra in September, then cheaper Sol and Luna versions. Similarly, Google made Gemini 4 Argon generally available on October 13 with a one million token context. Meanwhile, Meta replaced Llama with its Muse models and released an open-weight version in November. Chinese open models such as DeepSeek V4 and Qwen, for their part, keep closing the gap. In fact, Stanford’s AI Index 2026 found the best US model led the best Chinese model by only 2.7%.

As a result, in 2027 expect the same capability at a fraction of the price, plus small models that run on phones and laptops. However, there is a catch. Labs are releasing their strongest systems more cautiously: OpenAI cancelled GPT-6.1 Astra after safety tests, and Anthropic keeps Mythos-class models restricted to partners. Of all the technology trends for 2027, cheaper intelligence is the one that touches every other item on this list.

Our call: Real. Falling prices are measured, not promised. The open question is which top models the public is allowed to use.

2026 was the year agents got their own computers. OpenAI launched Dots at DevDay, always-on assistants with a cloud browser of their own. Meta pushed its Muse AI agent onto phones and even the Apple Watch, and Anthropic entered the personal assistant race in November.

At the same time, the capability curve is steep. METR measures how long a task an AI can finish with 50% success, and the best model in 2026 reached about 16 hours of human work, the upper limit METR can reliably measure. In addition, Gartner lists “AI agent identity” among its 2027 trends and warns that ungoverned agents will cause 1 in 4 enterprise breaches by 2028.

The reality check is just as clear. Gartner also predicts that more than 40% of agentic AI projects will be cancelled by the end of 2027, and that only a small fraction of “agent” vendors are real. Agents are also expensive: Musk called Grok Bot costs unsustainably high, and OpenAI admits Dots are compute heavy. For builders, our agentic AI frameworks roundup is a good place to start.

Our call: Watch. Agents will do real work in 2027, but most company pilots will fail on cost, security and trust before they scale.

AI video is the fastest moving creative category. ByteDance’s Seedance 2.5 and Kling 4.0 now generate native 4K clips up to 30 seconds in a single pass, with dozens of reference images for consistent characters. Meanwhile, Google replaced Veo with Gemini Omni, which already runs inside YouTube Shorts. Research labs, in turn, are pushing toward real time: one system produced a 5 second clip in under 3 seconds and streamed at 24 frames per second.

The 2027 shift is from clips to scenes. In other words, longer shots, synced sound and editing by text prompt mean small creators can produce work that needed a crew two years ago. If you want to see where the quality is today, try Kling’s latest video model or read our Kling AI review.

The legal side is heating up too. Disney and Universal are suing Midjourney, and labels keep filing new suits against AI music firms. In Europe, AI-generated content must carry machine-readable markings from December 2, 2026. Finally, deepfake fraud is the dark side: Deloitte estimates US losses from generative AI fraud could reach $40 billion by 2027.

Our call: Real. The tools already exist. 2027 decides the rules: labeling, licensing and who gets paid.

Developers in Sonar’s 2026 survey say about 42% of the code they commit is AI-generated, and they expect that to reach 65% in 2027. A separate study published in Science measured the US share at about 29% by the end of 2025. Either way, the direction is not in doubt.

At the same time, the work is moving from autocomplete to agents. For example, Claude Code passed $2.5 billion in run-rate revenue early in 2026, and Google says Gemini 4 refactored six million lines of Chrome code. Gartner names the “agent coding harness” a 2027 trend: a control layer that plans, tests and reviews what coding agents produce. It also lists “disposable applications”, small apps built for one job and retired on a schedule.

Still, there is a risk attached. Forrester predicts that a bug written by AI will cause a global, multi-industry outage in 2027, and 96% of developers say they do not fully trust AI code. Beginners can start with vibe coding and builders like Lovable, while teams should compare the best AI coding tools.

Our call: Real. AI-written code is the default in 2027. Code review and testing become the scarce skill.

The chip roadmap for 2027 is unusually concrete. Nvidia’s Vera Rubin started shipping in August 2026 and became its fastest ramp ever. Next on the roadmap is Rubin Ultra in the second half of 2027, in a 576 GPU “Kyber” rack, although industry analysts report a possible slip into 2028. AMD says its MI500 arrives in 2027, and Meta signed up for as much as 6 gigawatts of AMD GPUs.

Underneath it all, of course, sits TSMC. Its A16 process, at 1.6 nanometers and the first node with backside power delivery, moves into volume production in 2027. On top of that, Google split its eighth-generation TPU into training and inference chips, and Anthropic has about 3.5 gigawatts of TPU capacity lined up from 2027. Arm is building its own “AGI CPU” for Oracle Cloud in fall 2027.

Overall, the quiet trend is diversity. Forrester expects a quarter of AI infrastructure tenders in 2027 to require options beyond Nvidia. For people buying hardware today, our guides to the best GPU for AI and the best desktop for AI cover what works now.

Our call: Real. These are scheduled products. Delays of a few quarters are normal, cancellations are not.

No list of 2027 technology trends makes sense without the buildings that run AI. Goldman Sachs expects the five largest US cloud companies to spend about $1.2 trillion on AI infrastructure in 2027, up from roughly $800 billion in 2026. Gartner forecasts data center systems spending to grow 55% in 2027. Alphabet says its capex “will increase significantly”, and Microsoft expects spending to accelerate in the first half of 2027.

As a result, companies now measure these sites in gigawatts, the output of a large power plant. xAI calls Colossus 2 the first gigawatt training cluster, and Meta’s Hyperion is planned for millions of GPUs. Even so, building one still takes about two years, and not everything is on time. Bloomberg reported that Oracle moved several OpenAI data centers from 2027 to 2028, while Stargate’s Abilene site runs at about half of its planned 1.2 gigawatts.

Above all, local resistance is the new constraint. On November 3, 2026, voters approved data center restrictions in 40 of 41 local ballot measures across 10 states. We covered the trend in AI data center public opposition, and it will shape where 2027 capacity gets built.

Our call: Real. The money is committed. Power, permits and voters decide how fast it turns into capacity.

This is the trend most videos skip. According to the IEA, data centers used about 415 TWh of electricity in 2024 and about 485 TWh in 2025, a 17% jump in one year. The agency projects roughly 945 TWh by 2030, more than double, with AI-focused sites growing about four times. In the US, the Electric Power Research Institute expects data centers to reach 9% to 17% of all electricity by 2030.

Company reports, for instance, show the cost. Google’s electricity use rose 37% in 2025, its emissions rose 18% and its water use rose 34% to 10.9 billion gallons. Microsoft’s emissions rose 25%, and Amazon’s rose 16%. On top of that, researchers behind the “Making AI Less Thirsty” study estimate AI could withdraw 4.2 to 6.6 billion cubic meters of water in 2027, about four to six times what Denmark uses.

In response, the industry is betting on nuclear and on-site power. The restart of the Three Mile Island unit for Microsoft is targeted for 2027. Other promises are slipping, though: Oklo missed its 2026 reactor goal and the Amazon-backed X-energy permit moved to 2028. In short, 2027 still runs mostly on gas and the existing grid.

Our call: Real. Rising power and water use is measured in company reports. Clean supply arrives later than the demand.

In 2027, regulation finally stops being a debate and becomes a calendar. In the EU, the AI Act’s transparency duties have applied since August 2, 2026. After the Digital Omnibus deal, the strict rules for stand-alone high-risk AI systems (hiring, credit, education and similar uses) now start on December 2, 2027, and rules for AI inside regulated products follow in August 2028. General-purpose models that were already on the market must comply by August 2, 2027.

The US, by contrast, is a patchwork. California’s SB 53 on frontier AI transparency has been in force since January 2026. New York’s RAISE Act and Colorado’s rewritten AI law both take effect on January 1, 2027. A December 2025 executive order set up a federal task force to challenge state AI laws, and the new Congress that takes office in January 2027 has made AI guardrails a campaign theme. Meanwhile, China has required labels on AI-generated content since September 2025.

For companies, therefore, 2027 is the first year compliance costs show up in budgets. For users, on the other hand, it means more labels, more disclosures and more “this was made with AI” notices.

Our call: Real. Lawmakers have already written the dates into law. Expect more delays at the edges, not a reversal.

“AI 2027” is a forecast scenario published in 2025 by Daniel Kokotajlo and the AI Futures Project. It described AI systems that automate AI research by 2027 and then improve themselves faster than humans can follow. The phrase stuck, and it is one of the most searched AI topics heading into the year, the most debated of all 2027 technology trends.

Here, however, is the update most coverage misses. In April 2026, the authors revised their own estimates for an “automated coder”: Kokotajlo now says mid-2028 and co-author Eli Lifland says mid-2030. So even the people who wrote AI 2027 no longer expect the full scenario in 2027. What they do see, though, is acceleration: METR’s task length doubles about every four months, and AI already does a growing share of lab research.

The CEOs, however, are more aggressive. Demis Hassabis now talks about AGI in two to three years. Dario Amodei describes a “country of geniuses in a datacenter” around 2027. Likewise, Sam Altman’s goal is a fully automated AI researcher by March 2028, while Elon Musk says AI will be smarter than all humans combined around 2030. On the other side, lawmakers introduced a bill to ban superintelligence in the US Congress in September 2026.

Our call: Hype risk. Expect visible AI-builds-AI progress in 2027. A clear, agreed AGI moment next year is unlikely.

First, games are becoming the test bed for world models, AI systems that generate an interactive 3D world you can move through. Google DeepMind opened Genie 4 to testers in October 2026 with sound and dialogue built in. Roblox already lets creators generate interactive objects with its Cube model. Epic says Unreal Engine 6, with built-in AI model support, reaches early access by the end of 2027.

Similarly, AI characters are arriving in shipped games. Nvidia’s ACE tech powers AI squadmates that listen and talk back in titles like PUBG. Gartner puts world models in its 2027 list, beyond games, for simulating factories and cities before they are built.

Developers, however, are not convinced. In the GDC 2026 survey, 36% of game professionals used generative AI at work, but 52% said it is harming the industry, up from 18% two years earlier. Steam had to change its rules after a flood of low-effort AI games, as we covered in Valve’s stance on AI games. If you want to try it yourself, see our best AI game maker picks.

Our call: Watch. Great demos, real tools for creators, but full AI-generated hit games are still years away.

The State of AI Report says robotics is approaching its “GPT-2 moment”. The numbers are still small, but they are growing fast. TrendForce expects more than 50,000 humanoid robots to ship worldwide in 2026, and an earlier Goldman Sachs forecast put 2027 at about 76,000 units.

Moreover, the 2027 dates are specific. Tesla targets Optimus deliveries to outside companies in late 2027 and says its Fremont line is designed for a million units a year. Boston Dynamics opens production Atlas to new customers from early 2027, and Hyundai plans capacity for 30,000 robots a year by 2028. 1X plans a wider rollout of its $20,000 NEO home robot in 2027. Reports also say Apple is working on a tabletop home robot for 2027.

Robotaxis, by comparison, are further ahead. Waymo passed 220 million driverless miles and more than 500,000 paid rides a week, while Tesla aims to let customer cars join its network unsupervised around mid-2027. Smaller robots are already in homes, as our best AI robot dog guide shows. Among the physical technology trends for 2027, robotaxis are the most mature.

Our call: Watch. Factory and warehouse humanoids are real in 2027. A robot folding laundry in most homes is not.

The next AI device fight is about leaving the phone in your pocket. OpenAI and Jony Ive’s first device will ship no earlier than February 2027, according to a court filing, and reports suggest a speaker-like device with a camera. Bloomberg reports that Apple will unveil its first smart glasses at WWDC in June 2027 and ship them late in the year. Reports also point to Meta’s first true AR glasses in 2027.

In the meantime, the category is already moving. Meta sells Ray-Ban glasses from $449 and a display version for $799 (prices checked on November 10, 2026), and the first Android XR glasses from Warby Parker and Gentle Monster go on pre-order on November 12, 2026. Counterpoint expects generative AI phones to reach 52% of smartphone shipments in 2027. Gartner adds “speech reasoning models” to its 2027 list: voice AI that understands tone and context, which these screenless devices depend on.

Still, privacy is the brake. Cameras on faces and always-listening assistants worry regulators and the people around the wearer. Our best AI smart glasses guide compares what you can buy now.

Our call: Watch. Several launches are rumors, not announcements. Glasses will grow, but the phone is not going away in 2027.

In many ways, the most important AI trend may be the least visible. Two drug programs discovered with AI are now in Phase 3 trials, the last step before approval. Insilico’s rentosertib, for a serious lung disease, started its Phase 3 study in July 2026 with 320 patients. AlphaFold, the protein structure tool, now has more than three million users in 190 countries.

Gartner’s number one trend for 2027 is “large quantitative models”, AI trained on physics, chemistry and numerical data instead of text, used for simulation and forecasting. AI is also starting to solve open math problems with formal proofs.

That said, the limits are real. In one evaluation of an AI “co-scientist”, hallucinations that would invalidate results dropped from 46% to 4% only after the team added extra reliability checks. In 2027, the best results will come from scientists using AI, not from AI working alone.

Our call: Real. Phase 3 trials and millions of researchers are facts. Approvals of AI-discovered drugs are the milestone to watch.

Quantum appears in almost every trend list, so it is worth being precise. IBM’s roadmap puts its Cockatoo processor in 2027, a step toward Starling, a fault-tolerant machine with 200 logical qubits planned for 2029. Quantinuum says its Sol system is on track for 2027. In addition, Google demonstrated a verifiable quantum advantage on its Willow chip in late 2025.

For its part, Forrester predicts an unexpected quantum advance in 2027 that forces companies to rethink their plans, mostly around encryption. The practical work for 2027 is moving to post-quantum security standards, not buying a quantum computer. That is why quantum sits lower than most technology trends for 2027 on our list.

Our call: Hype risk. Real lab milestones, but useful commercial quantum computing is still a 2029 and later story.

The money behind every trend above has to pay off, and 2027 is when investors start to check. OpenAI and Anthropic together grew from about $30 billion to about $105 billion in annualized revenue during 2026. Greg Brockman said OpenAI “should be ready” for an IPO in 2027, and Anthropic filed confidentially for its own listing. Even so, many investors worry about an AI bubble, and Meta declined to give 2027 spending guidance.

Similarly, jobs are the personal side of the same question. The World Economic Forum expects 170 million jobs created and 92 million displaced by 2030. Goldman Sachs estimates 6% to 7% of US workers could be displaced over a decade. Interestingly, companies that spend the most on AI grew their headcount 10.2% over two years, and Forrester expects customer service hiring to rise 20% in 2027 after companies cut too fast. In practice, the jobs that change first are entry-level office roles.

Our call: Watch. Revenue is real and growing. Whether it grows fast enough for $1 trillion a year of spending is the question of 2027.

If you only remember three technology trends for 2027, make them these. First, AI gets cheaper and more capable at the same time, so tools you pay for today will cost less next year. Second, agents and AI-written code move from demos into daily work, which makes checking AI output a core skill. Third, the physical limits of power, water, chips and law decide how fast all of it happens.

Practically, these technology trends for 2027 mean three moves. Learn one agent or coding tool well instead of trying ten. Expect more AI labels and disclosures on what you read and watch. And treat any 2027 prediction with a specific date as a target, not a promise.

Sources

*Sources: Gartner Top Strategic Technology Trends 2027, State of AI Report 2026, Stanford AI Index 2026, IEA Energy and AI, AI Futures Project timelines update, METR time horizons, Forrester Predictions 2027, Gartner on agentic AI projects, Hogan Lovells on the EU AI Act delay, Axios on Google emissions, Tom’s Hardware on TSMC A16, DCD on AMD MI500, Li et al., Making AI Less Thirsty, MacRumors on the OpenAI device, Neowin on Unreal Engine 6, eWeek on Tesla Optimus, Baxtel on data center ballot measures.* *Images: editorial illustrations made in Midjourney, not product photos.*