Latest news with #genAI
Yahoo
05-08-2025
- Business
- Yahoo
Blue J secures $122m Series D funding for AI tax platform
Blue J, a generative AI (genAI) tax research platform, has raised $122m (C$168.26m) in a Series D funding round led by Oak HC/FT and Sapphire Ventures. The funding round also included participation from Intrepid Growth Partners and previous investors Ten Coves Capital and It will be used to support Blue J's efforts to expand its team, enhance product development and increase market reach. Blue J's platform uses genAI to provide answers to complex tax questions across US federal, state and local tax, as well as Canadian and UK tax law. Built on a curated database of authoritative tax law, Blue J's system improves by learning from millions of user queries each year. Blue J CEO and co-founder Benjamin Alarie said: 'We are thrilled to partner with Sapphire Ventures, Oak HC/FT, Ten Coves, and Intrepid Growth Partners – firms with exceptional track records of backing market-defining companies. 'Their commitment is a powerful endorsement of our vision to transform tax research. With this capital and industry support, we will accelerate innovation and deliver even greater value to tax professionals. We are building the future of tax. This is just the beginning.' Blue J's interface is designed to allow users to ask tax questions conversationally, without the need for complex syntax. The platform delivers answers with relevant source citations. Oak HC/FT partner Allen Miller said: 'Tax research has long been a cumbersome, time-consuming task. Blue J has solved this challenge with an elegant AI solution that dramatically accelerates research while raising the bar for accuracy. 'We believe Blue J will become the new standard for complex tax questions – and we are proud to support Ben and the team in their next stage of growth.' Blue J said that its revenue and customer base more than doubled in the first half of 2025. The Series D round follows Blue J's December 2024 Series C. Since January 2025, Blue J has grown to over 80 employees and more than doubled its rate of new customer acquisition, the company said. Earlier this year, collaborated with Blue J to provide companies of all sizes with access to an AI-powered tax research solution. "Blue J secures $122m Series D funding for AI tax platform " was originally created and published by International Accounting Bulletin, a GlobalData owned brand. The information on this site has been included in good faith for general informational purposes only. It is not intended to amount to advice on which you should rely, and we give no representation, warranty or guarantee, whether express or implied as to its accuracy or completeness. You must obtain professional or specialist advice before taking, or refraining from, any action on the basis of the content on our site. Error while retrieving data Sign in to access your portfolio Error while retrieving data Error while retrieving data Error while retrieving data Error while retrieving data
Yahoo
01-08-2025
- Business
- Yahoo
Federal Reserve economists aren't sold that AI will actually make workers more productive, saying it could be a one-off invention like the light bulb
A new Federal Reserve Board staff paper concludes that generative artificial intelligence (genAI) holds significant promise for boosting U.S. productivity, but cautions that its widespread economic impact will depend on how quickly and thoroughly firms integrate the technology. Titled 'Generative AI at the Crossroads: Light Bulb, Dynamo, or Microscope?' the paper, authored by Martin Neil Baily, David M. Byrne, Aidan T. Kane, and Paul E. Soto, explores whether genAI represents a fleeting innovation or a groundbreaking force akin to past general-purpose technologies (GPTs) such as electricity and the internet. The Fed economists ultimately conclude their 'modal forecast is for a noteworthy contribution of genAI to the level of labor productivity,' but caution they see a wide range of plausible outcomes, both in terms of its total contribution to making workers more productive and how quickly that could happen. To return to the light-bulb metaphor, they write that 'some inventions, such as the light bulb, temporarily raise productivity growth as adoption spreads, but the effect fades when the market is saturated; that is, the level of output per hour is permanently higher but the growth rate is not.' Here's why they regard it as an open question whether genAI may end up being a fancy tech version of the light bulb. GenAI: a tool and a catalyst According to the authors, genAI combines traits of GPTs—those that trigger cascades of innovation across sectors and continue improving over time—with features of 'inventions of methods of invention' (IMIs), which make research and development (R&D) more efficient. The authors do see potential for genAI to be a GPT like the electric dynamo, which continually sparked new business models and efficiencies, or an IMI like the compound microscope, which revolutionized scientific discovery. The Fed economists did cautioning that it is early in the technology's development, writing 'the case that generative AI is a general-purpose technology is compelling, supported by the impressive record of knock-on innovation and ongoing core innovation.' Since OpenAI launched ChatGPT in late 2022, the authors said genAI has demonstrated remarkable capabilities, from matching human performance on complex tasks to transforming frontline work in writing, coding, and customer service. That said, the authors said they're finding scant evidence about how many companies are actually using the technology. Limited but growing adoption Despite such promise, the paper stresses that most gains are so far concentrated in large corporations and digital-native industries. Surveys indicate high genAI adoption among big firms and technology-centric sectors, while small businesses and other functions lag behind. Data from job postings shows only modest growth in demand for explicit AI skills since 2017. 'The main hurdle is diffusion,' the authors write, referring to the process by which a new technology is integrated into widespread use. They note that typical productivity booms from GPTs like computers and electricity took decades to unfold as businesses restructured, invested, and developed complementary innovations. 'The share of jobs requiring AI skills is low and has moved up only modestly, suggesting that firms are taking a cautious approach,' they write. 'The ultimate test of whether genAI is a GPT will be theprofitability of genAI use at scale in a business environment and such stories are hard to come by at present.' They know that many individuals are using the technology, 'perhaps unbeknownst to their employers,' and they speculate that future use of the technology may become so routine and 'unremarkable' that companies and workers no longer know how much it's being used. Knock-on and complementary technologies The report details how genAI is already driving a wave of product and process innovation. In healthcare, AI-powered tools draft medical notes and assist with radiology. Finance firms use genAI for compliance, underwriting, and portfolio management. The energy sector uses it to optimize grid operations, and information technology is seeing multiples uses, with programmers using GitHub Copilot completing tasks 56% faster. Call center operators using conversational AI saw a 14% productivity boost as well. Meanwhile, ongoing advances in hardware, notably rapid improvements in the chips known as graphics processing units, or GPUs, suggest genAI's underlying engine is still accelerating. Patent filings related to AI technologies have surged since 2018, coinciding with the rise of the Transformer architecture—a backbone of today's large language models. 'Green shoots' in research and development The paper also finds genAI increasingly acting as an IMI, enhancing observation, analysis, communication, and organization in scientific research. Scientists now use genAI to analyze data, draft research papers, and even automate parts of the discovery process, though questions remain about the quality and originality of AI-generated output. The authors highlight growing references to AI in R&D initiatives, both in patent data and corporate earnings calls, as further evidence that genAI is gaining a foothold in the innovation ecosystem. Cautious optimism—and open questions While the prospects for a genAI-driven productivity surge are promising, the authors warn against expecting overnight transformation. The process will require significant complementary investments, organizational change, and reliable access to computational and electric power infrastructure. They also emphasize the risks of investing blindly in speculative trends—a lesson from past tech booms. 'GenAI's contribution to productivity growth will depend on the speed with which that level is attained, and historically, the process for integrating revolutionary technologies into the economy is a protracted one,' the report concludes. Despite these uncertainties, the authors believe genAI's dual role—as a transformative platform and as a method for accelerating invention—bodes well for long-term economic growth if barriers to widespread adoption can be overcome. Still, what if it's just another light bulb? For this story, Fortune used generative AI to help with an initial draft. An editor verified the accuracy of the information before publishing. This story was originally featured on Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Harvard Business Review
25-07-2025
- Business
- Harvard Business Review
Will Your Gen AI Strategy Shape Your Future or Derail It?
Summary. By studying 100 brand implementations of gen AI, researchers have discovered four archetypes for how companies are using the technology strategically. Bold innovators seek to reshape their markets with gen AI. Disciplined integratorsfocus on trust,...more
Forbes
02-07-2025
- Business
- Forbes
The Future Of Search: Content Strategies For Changing User Behaviors
The Future of Search: Content Strategies for Changing User Behaviors B2B marketing leaders face a harsh reality: Buyers aren't searching for information the way they used to, but most marketing teams are optimizing as if they are. Even as organic traffic declines, many teams continue to rely on outdated digital marketing playbooks to plan, publish, and measure content. These habits are hard to break. They're reinforced by legacy KPIs, familiar workflows, and pressure to show immediate results. Marketers still chase keyword rankings, obsess about page views, and anchor reporting in click-based behaviors, even as genAI redefines how search works and how buyers discover and trust information. Your Buyers' Search Behavior Has Changed Search used to be straightforward: A buyer typed in a query, scanned a results page, and clicked through to vendor content. But that linear search-to-click path is done. Today, buyers ask questions in natural language and get instant, AI-curated answers. According to Forrester's Buyers' Journey Survey, 2024, 89% of B2B buyers say they're using genAI tools at every stage of the purchase process. They consult genAI tools such as Perplexity, ChatGPT, Claude, or Gemini, often on mobile devices or embedded in enterprise software, to accelerate how they learn and evaluate solutions. They gather insights from multiple self-guided sources, including genAI tools, vendor websites, social media platforms, user review websites, industry events, and industry or business association websites. The Risks Of Sticking With An Outdated Content Strategy Holding on to yesterday's content strategy doesn't just slow you down. It actively undermines your visibility, credibility, and influence with modern B2B buyers because even high-quality content is getting filtered, summarized, or skipped entirely. Here's what's at stake: Content Visibility Has New Rules And Higher Stakes Today's buyers are gathering insights in more places before they reach your site. To stay visible and credible, your content must meet them where they are, earn their trust quickly, and reflect the depth of expertise that they expect. This means moving beyond keywords and building content around buyer intent, clear answers, and proof of authority. Every asset should reinforce your relevance and readiness — because if your content isn't built to be recognized by AI and respected by buyers, it won't show up where decisions are made. This post was written by Principal Analyst Lisa Gately and it originally appeared here.
Axios
02-07-2025
- Science
- Axios
AI's great brain-rot experiment
Generative AI critics and advocates are both racing to gather evidence that the new technology stunts (or boosts) human thinking powers — but the data simply isn't there yet. Why it matters: For every utopian who predicts a golden era of AI-powered learning, there's a skeptic who's convinced AI will usher in a new dark age. Driving the news: A study titled "Your Brain on ChatGPT" out of MIT last month raised hopes that we might be able to stop guessing which side of this debate is right. The study aimed to measure the "cognitive cost" of using genAI by looking at three groups tasked with writing brief essays — either on their own, using Google search or using ChatGPT. It found, very roughly speaking, that the more help subjects had with their writing, the less brain activity, or "neural connectivity," they experienced as they worked. Yes, but: This is a preprint study, meaning it hasn't been peer-reviewed. It has faced criticism for its design, small size, and its reliance on electroencephalogram (EEG) analysis. And its conclusions are laced with cautions and caveats. On their own website, the MIT authors beg journalists not to say that their study demonstrates AI is "making us dumber": "Please do not use words like 'stupid', 'dumb', 'brain rot', 'harm', 'damage'.... It does a huge disservice to this work, as we did not use this vocabulary in the paper." Between the lines: Students who learn to write well typically also learn to think more sharply. So it seems like common sense to assume that letting students outsource their writing to a chatbot will dull their minds. Sometimes good research will confirm this sort of assumption! But sometimes we get surprised. Other recent studies have taken narrow or inconclusive stabs at teasing out other dimensions of the "AI rots our brains" thesis — like whether using AI leads to cultural homogeneity, or how AI-assisted learning compares with human teaching. Earlier this year, a University of Pennsylvania/Wharton School study found that people researching a topic by asking an AI chatbot "tend to develop shallower knowledge than when they learn through standard web search." The big picture: As AI is rushed into service across society, the world is hungry for scientists to explain how a tool that transforms learning and creation will affect the human brain. High-speed change makes us crave high-speed answers. But good research takes time — and costs money. Generative AI is simply too new for us to have any sort of useful or trustworthy scientific data on its impact on cognition, learning, memory, problem-solving or creativity. (Forget "intelligence," which lacks any scientific clarity.) Society is nevertheless charging ahead with a vast uncontrolled experiment on human subjects — as we have almost always done with previous new waves of technology, from railroads and automobiles to the internet and social media. Our thought bubble: As tantalizing but risky new tools have come into view, our species has always chosen the "f--k around and find out" door. Since even fears that AI might destroy humanity haven't been enough to slow down its research and deployment, it seems absurd to think we would tap the brakes just to curtail cognitive debt. Flashback: Readers with still-functional memories may recall the furor around an Atlantic cover story by Nicholas Carr from 2008 titled "Is Google Making Us Stupid?" Back then, the fear was that over-reliance on screens and search engines to provide us with quick answers might stunt our ability to acquire and retain knowledge. But now, in the ChatGPT era, reliance on Google search is being framed by studies like MIT's and Wharton's as a superior alternative to AI's convenient — and sometimes made-up — answers.
