CONSUMER

OpenAI challenges Google on its home turf

Not long ago, ChatGPT hit a wall the moment a question fell outside its training data. Today, it searches the web to answer almost anything, and that shift is winning over users.

At a fireside chat in New York City, Adam Fry, ChatGPT’s consumer product lead, shared that an internal OpenAI analysis found ChatGPT now handles roughly one fifth as many queries as Google, which has dominated search for decades. To put that in perspective, Google dominates about 90% of the worldwide search market, while its closest rival, Bing, has just over 5%. That means ChatGPT’s query volume would be more than three times Bing’s.

"What people came to ChatGPT to start, if you go back about two years, was really like writing help and coding help, and those wouldn't be things that you really search for, but what we've seen over the last year is people have really sort of grown into all these other topics," added Fry. 

That growth is indicative of ChatGPT's overall popularity, which has grown from one billion to 1.2 billion users in the last two months. Other features OpenAI has developed to continue to improve the ChatGPT experience have also continued to gain traction, such as voice mode, allowing users to naturally hold conversations with ChatGPT, which now has 250 million weekly active users, and image generation, which generates 1.5 billion images per week. 

While the Voice Mode experience isn't widely adopted, with only 20% of users relying on it, Fry explained it is important for the team to continue to build on it as users who start using voice mode continue to use voice mode and dictation for interacting with ChatGPT. A big bottleneck, Fry explains, is simply the user's ability to  discover the tool, which OpenAI hopes to improve. Additionally, on Tuesday, OpenAI announced that Voice Mode is expanding to the ChatGPT Finances experience. 

The improvements don't end there, including the long awaited change in the works: finally combining the "Chat" and "Work" tabs. Currently, the two tabs add a layer of friction to make users choose between a conversation and a task, which can be confusing. Fry shared that OpenAI plans to bring them together into one interface, with the model inferring whether you want a quick reply or a longer, agentic task. TechCrunch has already reported that OpenAI is rolling out this redesigned experience to select users for feedback before it is rolled out widely, meaning that it could be coming to users soon.

While ChatGPT's growth is likely due to the constant improvements that OpenAI makes to the user experience, it's also worth mentioning a major change that could have had the opposite effect: ads. Realistically, nobody likes when ads are shoehorned into a platform, but OpenAI's' rollout of ads in ChatGPT has not seemed to hurt its user numbers. As a matter of fact, Fry explained that many people are finding it useful in certain settings, such as for hotel bookings, as it's helping them find what they need more quickly. Part of this success, and what OpenAI has done really well, is putting a lot of thought into user intent, privacy and ad placement integrity, as my colleague Nat Rubio-Licht explains in a recent feature. For instance, the company claims it does not share any of your data with the ad companies, and ads are only shown on queries that seem appropriate, not of a sensitive matter. Ultimately, OpenAI understands what rivals like Meta seem to be missing: User trust is hard won and easily lost, and no amount of ad revenue is worth that cost. Getting ads right by nailing user trust and utility from the start only serves to aid OpenAI on its path to upending Google's search dominance and becoming the go-to for consumer-facing AI. 

TOGETHER WITH HUMAN

Meta Muse Is Changing Holiday Shopping. Are You Ready?

AI agents are entering the holiday shopping season. Meta’s Muse is 25% more likely than other AI agents to reach checkout pages. What does that mean for retailers?

Join HUMAN to explore the latest data and learn:

• What’s happening: What HUMAN’s October data reveals about Muse.

• Why it matters: How Muse could reshape product discovery, customer acquisition, and fraud.

• What to do next: How to welcome legitimate AI shoppers while stopping malicious automation.

SAVE YOUR SEAT

WORKFORCE

How agents led a sea change in AI coding in June

Building software looks completely different than it did a year ago, and the implications are becoming clear.

In GitHub's 15th annual Octoverse report unveiled last week at the GitHub Universe event, the Microsoft-owned developer platform revealed that 40% of all GitHub pull requests, a major part of the technical process for updating software, started with an agent in September, up from 17% just six months ago. 

And the use of AI coding agents is dramatically increasing overall software development activity. GitHub recorded 17.9 billion code pushes during its annual reporting period ending in September 2026. That's more than it reported in its 2024 and 2025 reports combined. And the activity hit another gear in June of this year, as the chart below shows.

That momentum means the human role in software development is evolving toward deciding what to build, choosing the right models and tools to build with, and judging the results. That is going to change the skills developers need. It will put more weight on analysis, critical thinking, ideation, and evaluation. As AI accelerates the speed of development, it becomes more important than ever to be able to judge which work deserves to move forward. 

Tala Karadsheh, GitHub's senior director of business insights, told The Deep View that the report showed we're moving to a world where agents will write the first draft of the code while professionals developers will develop a process to review the outputs and manage quality and risk.  

Other interesting takeaways from the report include:

• Use of Copilot’s cloud agent grew 230% year over year, compared with 85% for agent chat, which is more evidence of developers shifting from using AI to answer questions to delegating entire tasks to it.

• Paid Copilot users drew on 47 distinct models in September, and none carried more than 25% of requests, which show no one model or lab is winning and model use is diversifying.

• Over 60% of paying Copilot users tried automatic model selection at least once in September, which shows the huge opportunity for model routing and making AI more efficient.

• Both AI-assisted code review and GitHub Advanced Security grew more than 90% year over year, indicating that demand is also growing for using AI to double-check and secure software.

• Public repositories serving construction work grew about 17x since 2022, while mining-related repositories grew about 65x (off a small base), which shows that use of AI is broadening across more specialized industries

Software development has been on the front lines of the generative AI boom. It's been the biggest beneficiary of LLM capabilities and it's also been the profession most deeply impacted by the new technology. GitHub, as the place where over 200 million developers host and collaborate on code, has been at the epicenter of the revolution. One of my biggest surprises over the past year has been people outside of tech revealing that they now have GitHub accounts and have been vibe coding solutions to some of their thorniest problems. But the rise of coding agents and the ability of AI to let a lot more people code has not led to the downfall of the software developer. In fact, many are even more in demand because there's a lot more code in the world to manage. But as this year's GitHub Octoverse report made clear, AI is changing the human skills and capabilities that are most in-demand. And software engineering may just be the beginning, with similar phenomena to come for other professions soon.

TOGETHER WITH FINGERPRINT

Meta Muse Is Sneakier Than Expected

The influx of AI agents working across the web has skyrocketed in recent years. That’s not an issue, as most agents announce themselves on arrival so you know exactly who’s visiting – but not Meta Muse. Meta’s personal AI agent purposefully circumvents and suppresses most bot detection tools… and for fraud and security purposes, that’s no good. 

Luckily, Fingerprint was designed with use cases just like this in mind. Built to identify agentic visitors (even the sneakiest ones like Muse), Fingerprint’s Bot Detection Smart Signal gives you clear responses on what agents are visiting your site and what they are doing. Their device intelligence covers everything from Meta Muse to Claude Code, Grok Bot, Perplexity, and more, so you know exactly what you’re dealing with – and that’s good for everyone.

Get all the details on identifying Meta Muse in Fingerprint’s latest blog post right here. 

RESEARCH

Can enterprise spending sustain the AI boom?

Enterprise spending continues to be the driving force behind frontier AI labs' growth. 

Data published on Tuesday by VC firm Menlo Ventures finds that enterprise AI spending has increased fivefold in the last year, hitting $177 billion. The report claims that more money is spent on enterprise AI deployment than on developing the models themselves, a cost that came to $102.5 billion this year, accounting for training compute, data and services. 

The report, which surveyed nearly 400 decision makers at US enterprises responsible for more than $4 billion in AI spend, creates tangible evidence of the skyrocketing spending that enterprises are committing to, especially as agents take an increasing number of actions. And companies are spending far more than they anticipated: Though many planned to nearly double their budget in 2026, on average, enterprises are spending 4.7 times more than they were last year. 

Here are some of the main takeaways: 

• Agents are largely driving spend, accounting for 80% of all tokens on OpenRouter, or seven times human-driven token spending. Of the AI engineers surveyed, 74% said they now use agents for workflows and tasks, with 32% using multiple agents at once. 

• Frontier labs still dominate the market, with OpenAI, Anthropic and Google capturing 69% of the market, up from 50% the prior year. Claude and Codex alone account for $24 billion in spend. Of those three, Anthropic and OpenAI are pulling ahead of Google, with Anthropic's market share hitting 55% from 40% the previous year, OpenAI's hitting 31% from 27%, and Google's falling to 9% from 21%.

• Open source models are seeing moderate gains, handling 19% of tokens, up from 11% last year. And these models are significantly cheaper, only accounting for 4% of model spend. 

• The SaaSpocalypse might be overblown. The report found that AI is causing "modestly slowing growth for traditional [Software-as-a-Service]." Only 22% of enterprises' software budgets were redirected towards AI. Of that, 13% of that cash still went to traditional software companies for new AI products, such as Microsoft for Copilot licenses. 

"Far from the SaaSpocalypse some feared, our study finds AI creates abundance in every market it touches — across frontier and open-source models, labs and independent apps," the report reads.

Though Menlo Ventures' report is likely music to the ears of frontier labs, the question remains: how long will this last? The report measured spend on deployment, rather than actual returns and value gained as a result, an open problem that many enterprises are still navigating. And though open source technology currently only makes up a fraction of usage, this report provides proof that these models are significantly cheaper, with average open source token costs dropping year on year. Additionally, while enterprise spending is currently outweighing the cost to develop expensive, frontier models, that might not always be the case, with AI giants like Anthropic poised to spend nearly $900 billion on AI infrastructure to feed the growing demand. To put it simply: Frontier labs are banking on enterprise spend, but it remains to be seen whether they eventually begin to tighten their purse strings. 

SPONSORED

LINKS

• Crowdstrike launches a killswitch for internal AI agents

• Anthropic S-1/A filing warns of imminent recursive self-improvement risk

• Nvidia instructs cloud clients to limit exposure to Chinese companies

• Salesforce to acquire Cresta, AI contact center software, for $2.7 billion

• OpenAI quadruples bug bounty rewards and adds security partners

• AI inference startup Fal raises $1.3 billion, $16 billion valuation

• Claude: Users can now auto-connect their organization's apps 

• Synthesia: ChatGPT plug-in to make on-brand videos with motion graphics, avatars, etc

• Runway: Now available on Cursor via a plugin 

• Audio Intelligence: Apple’s AI-powered Apple Watch features available in beta

• Walden Robotics: AI Engineer

• Raval West: AI Engineering & Transformation Architect

• develop: AI Software Engineer

• Superblocks: Product Manager

GAMES

POLL RESULTS

Do you regularly interact with AI through voice?

Yes (14%)
Somewhat (25%)
No (61%)