Forecast: AI’s Rise Will Cut Search Engine Traffic, Affecting Advertising

A new report from the research firm Gartner, has some unsettling news for search engine giants like Google and Microsoft’s Bing. It predicts that as everyday net users become more comfortable with AI tech and incorporate it into their general net habits, chatbots and other agents will lead to a drop of 25 percent in “traditional search engine volume.” The search giants will then simply be “losing market share to AI chatbots and other virtual agents.” One reason to care about this news is to remember that the search engine giants are really marketing giants. Search engines are useful, but Google makes money by selling ads that leverage data from its search engine. These ads are designed to convert to profits for the companies whose wares are being promoted. Plus placing Google ads on a website is a revenue source that many other companies rely on–perhaps best known for being used by media firms. If AI upends search, then by definition this means it will similarly upend current marketing practices. And disrupted marketing norms mean that how you think about using online systems to market your company’s products will have to change too. AI already plays a role in marketing. Chatbots are touted as having copy generating skills that can boost small companies’ public relations efforts, but the tech is also having an effect inside the marketing process itself. An example of this is Shopify’s recent AI-powered Semantic Search system, which uses AI to sniff through the text and image data of a manufacturer’s products and then dream up better search-matching terms so that they don’t miss out on matching to customers searching for a particular phrase. But this is simply using AI to improve current search-based marketing systems. AI–smart enough to steal traffic More important is the notion that AI chatbots can “steal” search engine traffic. Think of how many of the queries that you usually direct at Google-from basic stuff like “what’s 200 Farenheit in Celcius?” to more complex matters like “what’s the most recent games console made by Sony?”–could be answered by a chatbot instead. Typing those queries into ChatGPT or a system like Microsoft’s Copilot could mean they aren’t directed through Google’s labyrinthine search engine systems. There’s also a hint that future web surfing won’t be as search-centric as it is now, thanks to the novel Arc app. Arc leverages search engine results as part of its answers to user queries, but the app promises to do the boring bits of web searching for you, neatly curating the answers above more traditional search engine results. AI “agents” are another emergent form of the tech that could impact search-AI systems that’re able to go off and perform a complex sequence of tasks for you, like searching for some data and analyzing it automatically. Google, of course, is savvy regarding these trends, and last year launched its own AI search push, with its Search Generative Experience. This is an effort to add in some of the clever summarizing abilities of generative AI systems to Google’s traditional search system, saving users time they’d otherwise have spent trawling through a handful of the top search results in order to learn the actual answer to the queries they typed in. But as AI use expands, and firms like Microsoft double– and triple-down on their efforts to incorporate AI into everyone’s digital lives, the question of the role of traditional search compared to AI chatbots and similar tech remains an open one. AI will soon impact how you think about marketing your company’s products and Search Engine Optimization to bolster traffic to your website may even stop being such an important factor. So if you’re building a long-term marketing strategy right now it might be worth examining how you can leverage AI products to market your wares alongside more traditional search systems. It’s always smart to skate to where the puck is going to be versus where it currently is. BY KIT EATON @KITEATON

OpenAI Says Using ChatGPT Can Make You Lonelier. Should You Limit AI Use at Work?

The dramatic increase in AI chatbot use created a new way for people and machines to interact, and that may be a problem. Researchers from market leading AI firm OpenAI and MIT’s Media Lab have concluded that using ChatGPT may actually worsen feelings of loneliness for people who use the chatbot all the time. If your company is using AI tools to speed up your worker’s days, this is definitely something to consider! While the results were presented with some nuance and subtlety, they fuel a narrative begun in 2023, when then Surgeon General Dr. Vivek Murthy warned that there was an “epidemic” of “loneliness and isolation” that was harming Americans’ health, and he partly blamed our digital era, noting to NPR that “we are living with technology that has profoundly changed how we interact with each other.” That doesn’t mean AI use should be banned at work, but it’s worth considering how long your employees are spending working with a chatbot. The authors of the joint study noted that their analysis found that while “most participants spent a relatively short amount of time chatting with the chatbot, a smaller number of participants engaged for significantly longer periods.” It’s these “power users” that may be experiencing the biggest impact. The authors noted that people who had “higher daily usage — across all modalities and conversation types — correlated with higher loneliness, dependence, and problematic use, and lower socialization.” Reporting on the study, Business Insider pointed out that in some ways this sort of investigation is always tricky because feelings of loneliness and social isolation often change from moment to moment, influenced by many factors. But to control for this the researchers measured both the survey participants’ feelings of loneliness and their actual level of socialization, to separate out when people really experience isolation from the feelings of loneliness. As with face-to-face interactions, tone was a big influence, the study concluded. When ChatGPT was instructed to react with flatter, more neutral interactions in a “formal, composed, and efficient” manner, the power users felt heightened loneliness. When the chatbot was told to be “delightful, spirited, and captivating” and reflect the user’s emotions, the users didn’t suffer this way. This makes sense: you wouldn’t necessarily feel listened to if, say, your AI conversations were as muted as a short discussion with a clerk at the department of motor vehicles, but you would feel differently if your AI coworker spoke more like the machine in Scarlett Johansson‘s movie Her. If your company has raced to embrace the promise of AI, does this mean you should rethink your AI tool usage, or, at the very least, worry about your staff mental health? The nuanced answer is probably not. Not yet, at least…but it’s definitely something to keep a weather eye on. AI technology is making its presence felt in the workplace, and it’s now capable of remarkably human-like level of interaction. Wired’s recent report about Google’s “scramble” to catch up with OpenAI will unsettle critics. After Google’s Gemini AI was perfected and released, one executive told Wired that “she had switched from calling her sister during her commutes to gabbing out loud with Gemini Live.” That’s a score for Google’s AI chops, but it’s easy to see how the change may impact that executive’s relationship with her family. For now, many AI tools exist more in the background in the workplace, and they’re less like chatting to a digital person than interacting with a smarter version of Microsoft’s old, much-loathed “clippy” digital assistant. For example, taking advantage of Microsoft’s AI Copilot suggestions to speed up writing an email in Outlook is unlikely to harm your workplace friendships in the way that gabbling to ChatGPT for 8 hours while sat at your desk might. At this point, connections are fraying in the increasingly digitized workplace. Workplace friendships are eroding, and the idea of a “workplace spouse” is fading. Tech company executives are pushing AI hard too, with Slack’s leadership imagining a near future when workers spend more time talking to AI agents at work than they do chatting with their colleagues. Last year, drug maker Moderna’s CEO said he was hoping his company’s bottom line would benefit from workers chatting to ChatGPT at least 20 times per day. Increased use of AI in the workplace could easily mean that many more people effectively become AI “power users,” triggering the kind of worry about loneliness that MIT’s researchers spoke of. No matter how much AI may drive up your employees’ efficiency, and boost your bottom line, it’s worth remembering that a ton of science shows that happy workers are better workers. BY KIT EATON @KITEATON

Microsoft’s AI Agents Aim to Make Cybersecurity Teams’ Work Easier

If you peek behind the curtain at a network defender’s workflow, you might see hundreds—if not thousands—of emails marked as potential spam or phishing. It can take hours to sift through the messages to detect the most urgent threats. When a data breach occurs, figuring out what vital information was stolen is a critical—but often challenging—step for investigators. Today, Microsoft announced a set of artificial intelligence agents aimed at making cybersecurity teams’ work a little easier. That could be good news for the many businesses large and small that use Microsoft 365 for their email, cloud storage, and other services. Agentic AI is a buzzy new term for AI systems that can take actions on behalf of a human user. One step up from generative AI chatbots, AI agents promise to do actual work, such as executing code or performing web searches. OpenAI recently launched Deep Research mode for ChatGPT, which can conduct multi-step web searches to research complex topics or make shopping recommendations for major purchases. Google has been rolling out its own AI agents built off the latest version of Gemini. A year ago, Microsoft launched Security Copilot, which introduced AI tools to its suite of security products: Purview, Defender, Sentinel, Intune, and Entra. Starting in April, users can opt in to having AI agents do specific tasks for them. Microsoft says the agents can help streamline the work of security and IT teams, which are facing both a labor shortage and an overwhelming volume of threats. Take phishing emails. In 2024, Microsoft says it detected 30 billion phishing emails targeting customers. At a company level, security teams often have to individually evaluate every potential phishing email and block malicious senders. A new phishing triage agent inside Defender scans messages flagged by employees to ensure that the most urgent threats are addressed first. Among the tasks the agent performs are reviewing messages for language that suggests a scam and checking for malicious links. The most dangerous emails go to the top of a user’s queue. Other messages might be deemed false positives, or simple spam. From there, the IT team can review a detailed description of the steps the agent took. The AI agent will suggest next steps—such as blocking all inbound emails from a domain associated with cybercriminals—and the human user can click a button to instruct the agent to perform those tasks. If an email was mistakenly marked as spam, there’s a field for the user to explain in natural language why that email should not have been flagged, helping train the AI to be more accurate going forward. Another AI agent helps prevent data loss—for example, looking for suspicious activity that might indicate an insider threat—and in the event of a data breach, helps investigators understand what information was stolen, whether a trade secret or customer credit card numbers. Other AI agents ensure new users and apps have the right security protocols in place, monitor for vulnerabilities, or analyze the evolving threat landscape a company faces. In each case, a user can look under the hood to see what steps the AI agent took in its investigation. The user can make corrections, or with the click of a button, tell the agent to complete the tasks it suggested, such as turning on multi-factor authentication for certain users, or running a software update. So far, the tools work across Microsoft services, such as Outlook, OneDrive and Teams, though integrations with third-party tools such as Slack or Zoom could be offered down the line. The tools also don’t take remediation steps without human approval. In the future, some of those tasks could also be automated. BY JENNIFER CONRAD @JENNIFERCONRAD

What Are AI Agents? Here’s How They Can Help You Get Stuff Done

OpenAI leader Sam Altman kicked off the year by declaring that 2025 would be when AI agents “join the workforce.” And he predicted that their addition will “materially change the output of companies.” It’s a sentiment shared by many AI industry luminaries, including Nvidia CEO Jensen Huang, who called agents “a multi-trillion-dollar opportunity.” (This type of technology is sometimes referred to as “agentic AI.”) But while the AI industry hypes up its shiny new toys, the rest of us are left with an important question: What the heck is an AI agent? What is an AI agent? OpenAI defines AI agents “as systems that independently accomplish tasks on behalf of users.” Olivier Godement, who heads up OpenAI’s API product team, says that an AI agent has been equipped with a specific purpose, a specific workflow to follow, and specific tools that enable it to take actions. That special purpose could be serving as a customer support specialist, and the actions it could take could be searching through an internal database, googling information, running a piece of code, or controlling a computer or internet browser. Essentially, agents are AI systems that can accomplish computer-based tasks for you. What’s the difference between an AI agent and a chatbot? Godement recommends thinking of agents as being the next evolution of chatbots. Apratim Purakayastha, general manager of Talent Development Solutions at online education platform Skillsoft, says that AI models become AI agents when they’ve been “enriched” with additional data and capabilities. You could direct an AI agent to continuously monitor prices for flights on a given date, or analyze job applications against an internal rubric. By combining the raw intelligence of AI models with data not included in its original training, says Purakayastha, a whole new world of opportunities arise. When they were originally released, chatbots like ChatGPT only existed as a channel for people to converse with AI models, but interactions were limited to the information the model had been trained on. Now, by activating the app’s Deep Research mode, users can instantly transform the chatbot into an AI agent, capable of searching the internet for minutes at a time and developing reports based on its findings. The AI model stays the same, but the added gadgets make it more useful. How have businesses used AI agents? According to Purakayastha, “gadgets” are actually a pretty good way to think about what makes AI agents different from AI models. Think about another notable agent: James Bond. Just like 007 receives a mission and gets equipped with gadgets specifically designed to help him carry out that mission, AI models are given a purpose and then equipped with the tools needed to carry out that purpose. A more mundane comparison is to an old-school travel agent, who books flights or hotel rooms for clients. One of the most successful examples of a company making use of an AI agent comes from software developer platform Replit. In 2024, the startup released an AI agent, built with an Anthropic Claude model, that can program applications from natural language prompts. Since the agent’s release, Replit has seen its revenue grow by over 10x. Other potential use cases for agents include providing customer support services, enabling more efficient data analysis, and, as recently demoed by Meta, empowering digital sales professionals. Can AI agents replace employees? One thing that AI agents aren’t? Virtual employees. Agents are intended to be used for very specific tasks, and shouldn’t be expected to act as a replacement for a human employee. Instead, says Purakayastha, agents should be thought of as a “virtual facet of an employee” or an “automated process.” A single agent should ideally only be responsible for completing a single step in a workflow, like approving or denying refunds by analyzing internal policy documents. You wouldn’t want to give the refund agent access to any unnecessary context or tools, because it would result in the agent becoming less focused on its specific task. Agents can be programmed to hand off control to each other, so you can essentially create a chain of agents that, when linked together, accomplish tasks. This process, which OpenAI’s Godement refers to as “separation of concerns,” also makes it easier to observe and optimize the effectiveness of agents, since they only need to be judged by their ability to complete a single step of a process. Can my business start using AI agents? AI agents are still in their infancy, and Godement cautions that businesses should “start small” when building agentic applications. Godement recommends identifying a workflow that you think could be more efficient, breaking down all the individual steps, and developing separate agents to handle each of those steps. “There will be a time when you can reinvent your whole product and company with agents,” he says, “but start small with one team of early adopters who are super passionate. You need one undeniable success story.” BY BEN SHERRY @BENLUCASSHERRY

OpenAI’s New Developer Tools Make Building AI Agents Easy

Earlier this week, OpenAI released two new solutions aimed at helping developers create AI-powered agents capable of going beyond just answering questions and actually taking actions, like approving refunds or buying plane tickets. Executives from OpenAI and cloud storage platform Box say these new development tools will make it much easier for businesses to take advantage of the cutting-edge tech. In a live streamed video on Tuesday, March 11, a group of OpenAI employees introduced the Agents software development kit (SDK) as well as the Responses application programming interface (API). The SDK gives developers a framework that enables applications built with OpenAI’s models to access additional tools and capabilities, like searching across files, parsing the internet, running code, or controlling a computer. The Responses API connects the company’s models to applications that require those new agentic capabilities. In essence, think of the SDK as a spell book and the API as a magic wand. The SDK gives developers the language needed to call upon these new powers, and the API channels those powers from their source (OpenAI) to an application. Developers give each agent a name, a set of instructions to follow (like “you are a customer support specialist … ”), and a defined set of tools that enables them to use specific capabilities or functions. In the live stream, the employees created an AI stylist agent as an example of how the new developer tools can be leveraged to create more useful AI applications. They gave the stylist agent two tools: the ability to search the internet, and access to a private database containing information about the OpenAI employees’ personal style. The agent used the insights from this data to recommend nearby stores with products that could match those preferences. To show how easily developers can upgrade their AI apps with new functionality, the OpenAI employees then created a second agent, assigned it to handle customer support, and gave it the ability to search through a database of previous orders and submit refund requests. In order to swap between the stylist and customer support agents, the team created a third agent, tasked solely with using contextual understanding to “hand off” control from one agent to the other. Olivier Godement, leader of OpenAI’s API business, says that within 24 hours of the SDK and API’s announcement, “several companies” had already pushed new products into production. OpenAI chief commercial officer Giancarlo Lionetti says he’s seen customers develop billing agents to send out invoices, financial analyst agents to compare market information found online with internal databases, and application agents for automating user enrollment of new programs and initiatives. It wasn’t impossible for developers to build agents before, says Godement, but it was a complex process that required multiple APIs. With OpenAI’s simplifying the process and creating a set of built-in tools, he says, it’s easier and faster than ever to equip AI models with agentic capabilities. One of the first new products built using the new API and SDK comes from Box, the cloud-based data storage platform. Box chief technology officer Ben Kus says that within 48 hours of receiving the development tools, his team created an agent that can connect proprietary data stored on the platform with OpenAI’s models, and use that information to accomplish various tasks. Imagine you have an e-commerce business and want to automate a customer service task, such as approving or denying a refund. You could create an agent, give it access to specific data on Box containing your company’s refund policy and customer order history, and then give it the ability to execute code approving or rejecting the claim based on the analyzed data. Box is so sure about agents’ ability to leverage data that the company is redesigning its internal search functions to be more agent-friendly. The data that a human may find useful when searching through their internal files isn’t necessarily as valuable to an AI agent, says Kus, so his team has been tailoring search integrations to ensure agents can obtain as much relevant information as possible. OpenAI’s Godement expects businesses to gradually become more ambitious with their agentic use cases over the next few months. Before long, he says, it could be common for an individual’s personal agent, with access to their identification and credit card info, to make transactions simply by conversing with a merchant’s agent. Basically, instead of scouring the internet yourself to buy a new sweater, your personal agent will handle the searching and shopping for you. A word of caution, though: Don’t overwhelm agents with an excess of information. With too much context, your agent may be a jack of all trades, but a master of none. Instead, Kus suggests thinking through how you’d accomplish a given task with humans, and then creating individual agents for every step of the workflow you’re hoping to automate. “Each agent has a job to be done,” says Lionetti, “and if you want it to do that job really well, it needs to be focused.” BY BEN SHERRY @BENLUCASSHERRY

AI is getting better at thinking like a person. Nvidia says its upgraded platform makes it even better

Nvidia on Tuesday revealed more details about its next artificial intelligence chip platform, Blackwell Ultra, which it says will help apps reason and act on a user’s behalf – two capabilities that would take AI beyond chatbots further into real life. Blackwell Ultra, which the company detailed at the its annual GTC conference, builds on Nvidia’s existing sought-after Blackwell chip. The additional computing power in the new Ultra version should make it easier for AI models to break complicated queries down into multiple steps and consider different options – in other words, reason, the company said. Demand for AI chips has surged in the wake of OpenAI’s ChatGPT in 2022, fueling a massive surge in Nvidia share prices. Its chips fuel the data centers that power popular, power-hungry AI and cloud-powered services from companies like Microsoft, Amazon and Google. But the arrival of Chinese tech startup DeepSeek – whose R1 model sent shockwaves through Wall Street for its reasoning capabilities and supposedly low cost – sparked speculation that expensive hardware may not be necessary to run high-performing AI models. Nvidia, however, appears to be skirting such concerns, as evidenced by its January quarter earnings in which it breezed past Wall Street’s expectations. Nvidia wants its chips to be central to the types of reasoning models that the Chinese tech startup helped popularize. It claims a DeepSeek R1 query that would have taken a minute and a half to answer on Nvidia’s previous-generation Hopper chip would only take 10 seconds with Blackwell Ultra. Cisco, Dell, HP, Lenovo and Supermicro are among the companies working on new servers based on Blackwell Ultra. The first products with Blackwell Ultra are expected to arrive in the second half of 2025. Being able to reason, or think through an answer before responding, will allow AI apps and agents to handle more complex and specific types of questions, experts say. Instead of just spitting out an answer, a chatbot with reasoning abilities could dissect a question and provide multiple, specific responses accounting for different scenarios. Nvidia cited an example of using a reasoning model to help create a seating arrangement for a wedding that takes into account preferences such as where to sit parents and in-laws and ensuring the bride is seated on the left. “The models are now starting to mimic a little bit of human-like behavior,” said Arun Chandrasekaran, an analyst covering artificial intelligence for market research firm Gartner. And it’s not just DeepSeek and OpenAI creating models that can reason. Google also updated its Gemini models with more reasoning capabilities late last year, and Anthropic introduced a hybrid reasoning model called Claude 3.7 Sonnet in February. Some experts also believe reasoning models could pave the way for “AI agents,” or AI assistants that can take actions rather than just answering questions. Companies like Google, Amazon and Qualcomm have been vocal about their visions for AI-powered helpers that can do things like book a vacation for you based on your preferences rather than just churning out answers to questions about flights and destinations. “What agentic AI excels at is multitasks,” said Gene Munster, managing partner at Deepwater Asset Management. “And being able to reason in each of those tasks is going to make the agents more capable.” By Lisa Eadicicco

If You Use AI Search at Work, Be Careful: A New Study Finds It Lies

With market leader Google leaning harder into AI-generated search results (after a stuttering start last year) and peer companies like OpenAI also trying out this innovative tech, it really does seem like AI is the future of online search. That will have implications for workers at pretty much any company, no matter the industry, because searching for information is such a fundamental part of the internet experience. But a new study from Columbia University’s Tow Center for Digital Journalism, featured in the Columbia Journalism Review, highlights that your staff needs to be really careful, at least for now, because AI search tools from several major makers have serious accuracy problems. The study concentrated on eight different AI search tools, including ChatGPT, Perplexity, Google’s Gemini, Microsoft’s Copilot, and the industry-upending Chinese tool DeepSeek; it centered around the accuracy of answers when each AI was quizzed about a news story, tech news site Ars Technica reported. The big takeaway from the study is that all the AIs demonstrated stunningly bad accuracy, answering 60 percent of the queries incorrectly. Not all the AIs were as bad as each other. Perplexity was incorrect about 37 percent of the time, while ChatGPT had a 67 percent error rate. Elon Musk’s Grok 3 model scored the worst, being incorrect 94 percent of the time—perhaps to no one’s surprise, given that Musk has touted the model as being limited by fewer safety constraints than rival AIs. (The billionaire also has a somewhat freewheeling attitude to facts and free speech.) Worse still, the researchers noted that premium, paid-for versions of these search tools sometimes fared worse than their free alternatives. It’s worth noting that AI search is slightly different to using an AI chatbot, which is more of a conversation. AI search typically sees the search engine trying to do the search for you after you type in your query, summarizing what it thinks are the important details from what it’s found online, so you don’t have to go and read the original article where the data comes from. But the problem here centers around the fact that, just like that one overconfident colleague who always seems to know the truth no matter what’s being discussed, these AI models just don’t like to admit they don’t know the answer to a query. The study’s authors noted that instead of saying “no” when they weren’t able to find reliable information in answer to a query on a news story, the AI frequently served up made-up, plausible-seeming, but actually incorrect answers. Another wrinkle detected by this study is that even when these AI search tools delivered citations to go alongside their search results (ostensibly so that users can then visit these source sites to double check any details, or to verify if the data is true) these citation links often led to syndicated versions of the content rather than the original publishers’ versions. Sometimes these links just led to web addresses that didn’t exist—Gemini and Grok 3 did this for more than half of their citations. Why should you care about this? The experiment was a bit niche, since it was based on news articles, and the researchers didn’t look deeply into the accuracy of AI search results for other content found online. Instead, they fed excerpts from real news pieces into the AI tools then asked them to summarize information, including the headline and other details. You should care for one simple reason. We know that AI can speed up some humdrum office tasks and boost employee efficiency. And it seems like AI search may become the norm, replacing traditional web searching, which can sometimes be a laborious task. But if your team is, for example, looking for background information to include in a piece of content you’re going to publish, or even looking for resources online before starting a new project, they need to be super careful about trusting the results that AI search tools deliver. Imagine if you published something on your company’s site only to learn that it was actually made up by an AI search tool that wasn’t prepared to say it didn’t know the actual answer. This is another version of the well-known AI hallucination problem, and it’s yet more proof that if you’re using AI tools to boost your company’s efforts, you definitely need savvy humans in the loop to check the AI’s output. BY KIT EATON @KITEATON

Sam Altman’s 8-Word Response to Meta’s Rumored ChatGPT Clone Is a Master Class

According to CNBC, Meta plans to launch a standalone app for AI during the second quarter of this year. There are few details available about what that might mean, except that it seems likely Meta will charge a monthly subscription, in line with existing players like ChatGPT, Anthropic’s Claude, and Google’s Gemini. If you’re the CEO of one of those companies, you’re probably thinking about how that might affect your business. After all, Meta is one of the largest companies in the world, with more than three billion users. But OpenAI CEO Sam Altman doesn’t seem all that worried. In a response posted on X, Altman suggested that his company will just “Uno reverse them,” and “do a social app” of its own. Look, I don’t think that OpenAI is launching some kind “ChatGPT With Friends” social app any time soon, but those eight words—”ok fine maybe we’ll do a social app”—are actually an interesting lesson. First of all, it should have been obvious to anyone paying attention that Meta would do this. Meta has never seen a good idea it wasn’t happy to steal from a competitor. In fact, almost every widely used feature in any of Meta’s apps started elsewhere. It’s kind of Mark Zuckerberg’s thing to see what the competition is doing and try to cut it off by just co-opting whatever feature people seem to love. You might argue it’s a gift, really. It has certainly been a successful model. Also, if Meta is serious about its AI chat ambitions, a standalone app seems like the only way to get there. I’m sure there are people who use Meta AI within the company’s various apps, but I’ve never talked to anyone who opens Instagram to chat with AI. They go to see what their friends are up to or get inspired by photos of other people’s lives, or to share funny videos. Still, this would represent an interesting change to Meta’s business model, which typically involves free apps and services that mostly serve as a way to target users with personalized ads. It makes sense that Meta would have to charge—AI inference is far more expensive than serving posts and showing ads—but this is a big shift. Meta is very much a consumer brand, which could expose generative AI tools to a much wider audience. I think a standalone Meta AI app could pose a real threat to ChatGPT in ways that other competitors have not. ChatGPT’s biggest advantage has been that it was first and its name is synonymous with AI for a lot of people. At the same time, it seems as though most of the people paying for ChatGPT or other similar AI tools are doing so for work or business reasons. I’m not sure how many of them will pay for another one. The most important thing here, however, is that Altman’s response is kind of perfect. No, not the part about OpenAI introducing a social app. I doubt that will actually happen—though I agree it would be funny, even if just on principle. Altman’s response does two things that serve as a master class to handling this kind of situation. First, and most important, it’s funny. Altman has mastered the art of reading the room and knowing his audience. On social media, Altman comes across as laid back and unaffected by the challenge to his business. I have no idea what he’s like in person, but this is the exact right way to respond in this environment. Second, Altman manages to highlight the biggest criticism you can make about Meta, which is the part where all of its best features are just copies of other people’s ideas. There’s not a lot you can do about that, except stay focused on what you’re doing instead of getting distracted by the threat of Meta coming for your business. If you look how quickly Meta was able to spin up Threads just by leveraging its existing social graph, there is no doubt in my mind that it could easily launch an app and have a few hundred million users in a short amount of time. If you’re Sam Altman, there is almost nothing you can do about that except continue making your product better. Oh, and have a sense of humor about the whole thing. EXPERT OPINION BY JASON ATEN, TECH COLUMNIST @JASONATEN

Google Says Its New AI Mode Will Help You Find Better, Deeper Information

Google has announced plans to expand generative AI’s presence in its search services with the launch of an experimental new chatbot, designed to help users “access more breadth and depth of information than a traditional search on Google,” according to a blog post announcing the new product. The company also announced updates to its controversial AI overviews, which provide a brief snapshot of key information related to a given Google search. The company has launched ‘AI Mode,’ an alternative to its traditional search interface. Unlike the default version of Google, AI Mode functions like a chatbot. Users can ask the chatbot a question, and the chatbot will use Google to search the web for information in order to quickly deliver an answer, complete with cited sources and links. In addition to conducting Google searches, AI Mode will integrate the company’s information systems, such as its stock market and weather trackers or shopping data. Google anticipates that one major use of AI Mode will be helping consumers find the right product for their specific needs and understand the differences between similar products. Google said in its blog post that it was expanding its AI search ambitions because “we’ve heard from power users that they want AI responses for even more of their search.” The company first attempted AI-augmented search with AI overviews, a feature in which an AI-generated answer to a Google search is posted at the top of the search results. Overviews debuted in May of 2024 to decidedly mixed reactions, but Google says it is one of the company’s “most popular services,” with over one billion global users. Notably, Google neglected to mention that overviews were automatically added to most users’ search experience, provided they were logged in to a Google account. AI Mode’s introduction signals that Google has a vision for the future of search that fully eliminates the need for users to choose from a set of websites, and instead acts more like a conversational assistant that can trawl the internet for you and only surface the best content. The move is a clear shot at OpenAI, which recently debuted a new feature that enables ChatGPT to search the internet, and Perplexity, an AI-powered search engine that is directly competing with Google. Google also announced that the overviews have been upgraded with Gemini 2.0, the latest version of the company’s series of AI models. Google says the new model will enable AI overviews to assist with a larger variety of questions and challenges, including “coding, advanced math, and multimodal queries.” The company added that teenagers can now use AI overviews, which going forward will appear even for users without Google accounts. Google analyzes search history data to estimate users’ ages. “As with any early-stage AI product,” Google said, “we won’t always get it right,” warning that AI Mode chatbot could appear biased on certain subjects. Currently, AI Mode is only available to paid Google One AI Premium subscribers. BY BEN SHERRY @BENLUCASSHERRY

Meet the Company Talking Big About Using AI to Render Private Wealth Managers Obsolete

Like many of AI’s biggest evangelists, Fahad Hassan believes the technology will transform entire industries, albeit with one distinction: Whereas other CEOs hope for a wave of so-called AI agents to reinvent areas like sales, Hassan is confident that bots will descend on the private wealth management space and irrevocably change the industry’s makeup. With that bullishness comes a grim prediction about the future employment of Certified Private Wealth Managers. “I tell them their job will not exist in the next five to ten years,” Hassan says with a smile. After co-founding the Mclean, Virginia-based Range in 2021, Hassan has helped build an investment management company that seeks to automate an industry that grew for decades on a bedrock of human relationships. He and his co-founder David Cusatis have strong votes of confidence from investors, including Google’s AI-focused fund Gradient Ventures, which contributed $12 million in Range’s Series A round in 2023, and also participated in its $28 million Series B last November. Hassan says more fundraising is coming: “We’re getting inbounds every 24 hours from AI-based VCs and other investors. We’re probably going to do a megaround this fall or this winter to accelerate our growth.” VCs are banking on their shared vision, one which is pretty rampant across Silicon Valley: The technological tide is turning and AI is making the upending of old norms inevitable. For Range’s purposes, this means that people don’t need to be on a first-name basis with a wealth advisor to make money. Trips to the golf course to build relationships and talk about ETFs are fast becoming a relic, thanks to AI agents, which work around the clock. “Stock brokers are a really good example where people had traded millions of dollars on the phone and knew a person. And today, you don’t do that. You don’t even think about it,” Hassan argues. Stock brokers’ demise has been noted before, although they still exist, often just under different titles like wealth managers, or financial advisers. The biggest question hanging over Range’s gambit is whether a platform that seeks to grow people’s money through new technology can earn enough public trust to unseat major financial institutions. How will it be regulated? Perhaps lightly, if Big Tech’s incursion into the federal government provides a clue: Many of President Donald Trump’s prominent backers hail from the tech industry, including the venture capitalists Ben Horowitz and Marc Andressen, whose firm, Andreessen Horowitz, has been praising AI-driven investment strategies since 2023. Hassan says it’s “the Wild West.” For now, Range isn’t even offering AI tools for its clients, making Hassan’s promises of sweeping automation sound perhaps a little blustery. “We’re still in the very, very early days of what a good AI user experience looks like,” says Cusatis, a software engineer who holds the title of chief architect at Range. For now, Range provides three pricing tiers that start at $2,655 annually. Unlike other private investment managers, Range doesn’t bill based on a percentage of a client’s assets. So far, the company’s custom-built AI tools, which both founders say are built on existing major Large Language Models, are used by Range’s team of wealth advisors to help tailor strategies for clients’ needs. Range is targeting a mid-year release of its first client-facing AI programs, and plans to keep its human team of advisors intact. The company’s ambition to automate jobs out of existence doesn’t apply to its own teams: “Range will have wealth managers, and it will always be a service they provide, if people want it,” a spokesperson tells Inc. The cautionary period makes sense. Some of the splashier rollouts in commercial AI have had major hiccups. Google’s AI overhaul of search famously recommended glue on pizza, and had a rocky start in general. Self-driving vehicles have also crashed, prompting scrutiny from regulators. So the question remains: Why should people trust a similar technology with their most important financial decisions? Alejandro Lopez-Lira, a professor of finance at the University of Florida, has been experimenting with how Large Language Models can be put to this test. There are some advantages, he says, in that an application like ChatGPT can absorb and synthesize far more information than any human can. But when it comes to financial planning over a long period, can an AI account for all the unforeseen variables that might arise and affect your portfolio? “It’s extremely hard to test the performance of any of these AI [investment] strategies, because they have basically memorized the whole internet up until very, very recently,” Lopez-Lira says. ChatGPT, for instance, can synthesize immense data, but only to a point: “For the latest ChatGPT models, the cutoff date is 2024. So if you want to use that model, you only have less than one year to simulate the performance of the strategy,” he explains. There is also the question of regulating autonomous investments. Algorithmic trading, or buying and selling securities on an automated basis, is something hedge funds have done for years, regulated by the Securities and Exchange commission and the Financial Industry Regulatory Authority, a non-profit that issues certifications. But agentic AI in private wealth management is a new area that isn’t regulated yet. “It’s a little bit of a gray area, for sure,” Lopez-Lira says. Hassan claims that’s to Range’s advantage. “Our vision is to keep doing what we’re doing growing as fast as we’re growing, and candidly, lobby for the set of laws that will come around AIs giving you advice and what that looks like.” he says. BY SAM BLUM, @SAMMBLUM

Anthropic’s Newest AI Wants to Be a Pokémon Master. Here’s Why That’s a Big Deal

On Monday, Anthropic released Claude 3.7 Sonnet, the company’s most capable AI model yet. It also revealed a new capability with implications for the business world: Claude can now play Pokémon, and it’s pretty good at it, at least for an AI. In a blog post detailing the new Claude model, Anthropic wrote that a small internal team had created an interface that enabled Claude to play Pokémon Red, the original Pokémon game released on the Nintendo Game Boy way back in 1996. So, why teach an AI model to play Pokémon? David Hershey, a member of Anthropic’s technical team, tells Inc. that staffers were inspired by a YouTube video in which an original reinforcement learning model was trained to play Pokémon, so they created a virtual environment in which Claude could attempt to play the game. Eventually, around June 2024, Hershey (a self-proclaimed Pokémon fan) took up the idea as a side project, first using it to test the capabilities of Claude 3.5 Sonnet, the new model at the time. He found that while earlier versions of Claude would immediately get stuck, Claude 3.5 could progress further, successfully catching a Pokémon and leaving the starting area of Pallet Town. For the uninitiated, the goal of Pokémon Red is to catch adorable creatures, train them by battling against non-playable characters, and win badges from powerful enemies called Gym Leaders. Pokemon is, of course, wildly popular, and is considered the highest-grossing media franchise of all time. To keep his coworkers, many of whom are also Pokémon fans, up-to-date on his efforts, Hershey started a dedicated Slack channel in which Anthropic employees could monitor Claude’s Pokémon journey. Every time Claude successfully caught a Pokémon or won a battle, more and more people would join the Slack channel, says Anthropic product research lead Diane Penn. The project developed a cult following within the company. Video games have long been used as a method for gauging an AI model’s ability. In the early days of OpenAI, staffers spent years training models to play online multiplayer game DOTA 2. “Defining success is hard,” says Hershey, “But video games happen to be structured in a way where progress is often measurable and linear.” Other games have been important over the decades as AI, or just thinking machines in general, developed. In 2016, Google DeepMind’s AlphaGo beat one of the world’s highest-ranked players of the ancient game Go, and in 2011, IBM’s Watson system beat Jeopardy champions Ken Jennings and Brad Rutter at their own game. And in 1997, IBM’s Deep Blue beat Garry Kasparov at chess. When Anthropic released an updated version of Claude 3.5 Sonnet in September, the model saw slight improvement, but the real breakthrough came in the form of Claude 3.7 Sonnet, the new model released this week. While the previous model got stuck in Viridian Forest, an early area in the game, 3.7 Sonnet was able to go further, collecting three badges from Pokémon gym leaders. So how is Claude able to improve itself? Hershey says that Claude’s new Pokémon skills are the direct result of a new feature called “extended thinking,” which enables the model to take additional time to “think” through how to solve a problem, instead of immediately generating a response. Hershey says a common complaint he’s heard from Anthopic’s customers is that earlier versions of Claude would make a false assumption and then struggle to reverse course. But because of its improved thought process, the new Claude is able to more effectively pivot and try new strategies, meaning it doesn’t get stuck nearly as often as earlier versions. According to Penn, Anthropic decided to include Hershey’s Pokémon benchmark in Claude 3.7 Sonnet’s announcement because the company is slowly moving away from traditional benchmarks in favor of more “accessible” tests that can be understood by a larger group of people. “We’re at a point where evaluations don’t tell the full story of how much more capable each version of these models are,” Penn says. Penn says the benchmark demonstrates Claude’s ability to intelligently make a plan and adapt with new strategies when it runs into a problem. For companies looking to use AI on complex tasks like conducting high quality research or complex financial analysis, the benchmark is proof that models can improve their performance by using reasoning capabilities. By using Pokémon progression as a benchmark, Anthropic is able to educate an entirely new audience about Claude’s capabilities. After learning that the benchmark would be included in the announcement, Hershey and a small team hustled to quickly create an ongoing livestream on Twitch, in which anyone can watch Claude attempt to catch ‘em all. Some users have even said in the livestream’s chat that they were inspired to subscribe to Anthropic’s $18 per month Claude Pro service. Even with its enhanced capabilities, the model is still far from becoming a Pokémon Master, say Penn and Hershey. As of Thursday afternoon, the model had been stuck in Mt. Moon, an early game area that’s notoriously tricky for kids, for over 27 hours. Viewers of “Claude Plays Pokémon” were especially delighted when Claude named its rival character Waclaud, a reference to Super Mario Bros villains Wario and Waluigi, but that actually wasn’t a decision made by the model. “It was in the system prompt,” admits Hershey. Before the livestream was launched, he says, “we ran an internal poll on what we should name the rival, so Waclaud is just a small easter egg from our internal culture at Anthropic.” Could the project’s popularity result in Pokémon becoming a new standardized benchmark for AI? Hershey isn’t quite sure, but based on the response his project has received online, he wouldn’t be surprised to see other AI labs use video games as benchmarks more often. “It’s just a great way to see progress over a long period of time,” he says, “and we’re definitely not the only people who think that’s important.” BY BEN SHERRY @BENLUCASSHERRY

Can AI Startups Dethrone Google Chrome in the Web Browser Wars?

A new report from the research firm Gartner, has some unsettling news for search engine giants like Google and Microsoft’s Bing. It predicts that as everyday net users become more comfortable with AI tech and incorporate it into their general net habits, chatbots and other agents will lead to a drop of 25 percent in “traditional search engine volume.” The search giants will then simply be “losing market share to AI chatbots and other virtual agents.” One reason to care about this news is to remember that the search engine giants are really marketing giants. Search engines are useful, but Google makes money by selling ads that leverage data from its search engine. These ads are designed to convert to profits for the companies whose wares are being promoted. Plus placing Google ads on a website is a revenue source that many other companies rely on–perhaps best known for being used by media firms. If AI upends search, then by definition this means it will similarly upend current marketing practices. And disrupted marketing norms mean that how you think about using online systems to market your company’s products will have to change too. AI already plays a role in marketing. Chatbots are touted as having copy generating skills that can boost small companies’ public relations efforts, but the tech is also having an effect inside the marketing process itself. An example of this is Shopify’s recent AI-powered Semantic Search system, which uses AI to sniff through the text and image data of a manufacturer’s products and then dream up better search-matching terms so that they don’t miss out on matching to customers searching for a particular phrase. But this is simply using AI to improve current search-based marketing systems. AI–smart enough to steal traffic More important is the notion that AI chatbots can “steal” search engine traffic. Think of how many of the queries that you usually direct at Google-from basic stuff like “what’s 200 Farenheit in Celcius?” to more complex matters like “what’s the most recent games console made by Sony?”–could be answered by a chatbot instead. Typing those queries into ChatGPT or a system like Microsoft’s Copilot could mean they aren’t directed through Google’s labyrinthine search engine systems. There’s also a hint that future web surfing won’t be as search-centric as it is now, thanks to the novel Arc app. Arc leverages search engine results as part of its answers to user queries, but the app promises to do the boring bits of web searching for you, neatly curating the answers above more traditional search engine results. AI “agents” are another emergent form of the tech that could impact search-AI systems that’re able to go off and perform a complex sequence of tasks for you, like searching for some data and analyzing it automatically. Google, of course, is savvy regarding these trends, and last year launched its own AI search push, with its Search Generative Experience. This is an effort to add in some of the clever summarizing abilities of generative AI systems to Google’s traditional search system, saving users time they’d otherwise have spent trawling through a handful of the top search results in order to learn the actual answer to the queries they typed in. But as AI use expands, and firms like Microsoft double– and triple-down on their efforts to incorporate AI into everyone’s digital lives, the question of the role of traditional search compared to AI chatbots and similar tech remains an open one. AI will soon impact how you think about marketing your company’s products and Search Engine Optimization to bolster traffic to your website may even stop being such an important factor. So if you’re building a long-term marketing strategy right now it might be worth examining how you can leverage AI products to market your wares alongside more traditional search systems. It’s always smart to skate to where the puck is going to be versus where it currently is. BY KIT EATON @KITEATON

Slack Imagines a Future Workplace Where You Chat More With AIs Than With Your Colleagues

The folks behind the messaging app Slack know a thing or two about how workers communicate with one another and their bosses. At least 750,0000 organizations around the world rely on it for their workplace communications. So when the company’s chief marketing officer makes a prediction about the future of workplace comms, it’s worth paying attention — and, boy, does Ryan Gavin have a doozy of an idea. In conversation with news outlet Axios, Gavin predicted that the rise of AI agents will transform workplaces, and that staff may soon talk to AIs more than to their human co-workers. AI agents have been hailed by many experts as the first truly useful tools that AI may provide, and possibly the next big thing in this technology revolution. Even OpenAI’s CEO Sam Altman is on board with this notion, and his company’s upcoming agent Operator may even prove to be the first AI gizmo that transforms the average workplace. Agents are more powerful than the ask-then-answer AI model chatbots use because they can actually perform actions in a digital environment, like filling in forms on a website automatically, or even taking control of your computer’s mouse and using apps on the desktop. Axios reminds us that Salesforce, which owns Slack, has been promoting its own AI agent systems, which are apparently already capable of acting like sales reps. But instead of being innovations looming in a far-off future, Gavin said he anticipates these agent systems achieving everyday use in many workplaces sooner rather than later. “I think that right now people are underestimating just how much the world of work is about to change,” he told Axios, putting a timeline on the transformation brought by AI agents as just “three or four or five years.” By then he said he imagined he could be talking to agents “as much, if not more than I’m talking to my human colleagues today.” This projection may unsettle AI critics who worry the tech will seriously disturb the way that humans interact with each other in the office, possibly contributing to worker burnout or the erosion of human relations, and even displace people from their jobs. But Gavin’s prediction aligns with numerous other expert views that suggest that AI’s will augment workers’ office skills, rather than replace them outright. Picture the scene if “every single employee had a human resources agent that sat right alongside them in Slack” Gavin said. As Axios noted, AI co-workers like this have the added benefit that they are easier to train than people, they may be cheaper to “employ,” they don’t ask for raises, and they won’t strike or quit. Gavin’s words brush over the obvious issue that workers often have an existential dislike of office human resources departments. Couple that with the notion that a computer-based company representative is digitally watching over your shoulder as you work, and the idea may worry people who already think that workplace surveillance solutions and worker time and task tracking are already far too Orwellian. That said, it’s easy to imagine an AI agent co-worker that would be very useful — it could serve up people’s contact info automatically when you’re planning a task, andf it could even fill in timesheets for you or look up specific company information, like financial data, when you’re putting together a presentation. How this will actually play out in the typical workplace of tomorrow is anyone’s guess, of course. Gavin’s point of view is merely one of many diverse perspectives, and seems centered more around digital messaging chats than actually talking to co-workers in person — no one is suggesting that office water cooler gossip will go away. But Gavin’s prediction of ubiquitous AI co-workers even aligns with recent data showing that employees now shun deep and lasting friendships with co-workers, since it suggests a digital colleague may take up some of this void. Supporters of AI use will also point out that some research suggests letting staff use AI in the workplace can actually boost their happiness. BY KIT EATON @KITEATON