In the coming years, AI systems will have a major impact on the ways people work. For that reason, we’re launching the Anthropic Economic Index, an initiative aimed at understanding AI’s effects on labor markets and the economy over time.
The Index’s initial report provides first-of-its-kind data and analysis based on millions of anonymized conversations on Claude.ai, revealing the clearest picture yet of how AI is being incorporated into real-world tasks across the modern economy.
We’re also open sourcing the datasetused for this analysis, so researchers can build on and extend our findings.
Bellebuono’s story isn’t unique. A recent study from the Federal Reserve Bank of New York reported the widest unemployment gap between new graduates and experienced degree holders since the 1990s.
The struggle to find work
The unemployment gap is partly due to the increase in competition and changing employer expectations, said David Deming, professor of public policy at the Harvard Kennedy School.
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Skill requirements for entry-level roles are higher today than a decade ago, he said. But the change has been gradual from year to year.
DeepSeek R-1 Explained— from aieducation.substack.com by Claire Zau A no-nonsense FAQ (for everyone drowning in DeepSeek headlines)
There is a good chance you’re exhausted by the amount of DeepSeek coverage flooding your inbox. Between the headlines and hot takes on X, it’s hard not to have questions: What is DeepSeek? Why is it special? Why is everyone freaking out? What does this mean for the AI ecosystem? Can you explain the tech? Am I allowed to use it?
Let’s break down why exactly it’s such a big deal with some straightforward FAQs:
Voice is one of the most powerful unlocks for AI application companies. It is the most frequent (and most information-dense) form of human communication, made “programmable” for the first time due to AI.
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For consumers, we believe voice will be the first — and perhaps the primary — way people interact with AI. This interaction could take the form of an always-available companion or coach, or by democratizing services, such as language learning, that were previously inaccessible.
The use of artificial intelligence at work continues to climb. Twice as many LinkedIn members in the U.S. say they are using AI on the job now compared to 2023, according to the latest Workforce Confidence survey. Meanwhile, at least half of workers say AI skills will help them progress in their careers. Product managers are the most likely to agree AI will give them a boost, while those in healthcare services roles are least likely.
An entire HR team was terminated after their manager discovered and confirmed that their system automatically rejected all candidates — including his own application.
The manager wrote in their comment, “Auto rejection systems from HR make me angry.” They explained that while searching for a new employee, their HR department could not find a single qualified candidate in three months. As expected, the suspicious manager decided to investigate.
“I created myself a new email and sent them a modified version of my CV with a fake name to see what was going on with the process,” they wrote. “And guess what, I got auto-rejected. HR didn’t even look at my CV.”
When the manager reported the issue to upper management, “half of the HR department was fired in the following weeks.” A typographical error with significant consequences caused the entire problem.
The manager works in the tech industry and was trying to hire developers. However, HR had set up the system to search for developers with expertise in the wrong development software and one that no longer exists.
From DSC: Back in 2017, I had survived several rounds of layoffs at the then Calvin College (now Calvin University) but I didn’t survive the layoff of 12 people in the spring of 2017. I hadn’t needed to interview for a new job in quite a while. So boy, did I get a wake-up call with discovering that Applicant Tracking Systems existed and could be tough to get past. (Also, the old-school job replacement firm that Calvin hired wasn’t much help in dealing with them either.)
I didn’t like these ATSs then, and I still have my concerns about them now. The above article points out that my concerns were/are at least somewhat founded. And if you take the entire day to research and apply for a position — only to get an instant reply back from the ATS — it’s very frustrating and discouraging.
Plus the ATSs may not pick up on nuances. An experienced human being might be able to see that a candidate’s skills are highly relevant and/or transferable to the position that they’re hiring for.
Networking is key of course. But not everyone has been taught about networking and not everyone gets past the ATS to get their resume viewed by a pair of human eyes. HR, IT, and any other relevant groups here need to be very careful with programming their ATSs.
Professionals are navigating rapid change, and staying ahead of the curve is no easy feat. Recent LinkedIn research shows that 64% of workers feel overwhelmed by the pace of workplace shifts, from navigating AI to managing multi-generational teams. At the same time, U.S. workers’ confidence in their job securityis the lowest it’s been since the start of the pandemic.
But as the workplace continues to evolve, new opportunities arise. That’s exactly what our annual Jobs on the Rise list uncovers — the fastest-growing jobs over the past three years and the trends defining the future of work. From the rise of AI roles to the resurgence in travel and hospitality positions, the 2025 ranking highlights sectors with sustainable growth in today’s changing workforce. (You can read more about our methodology at the bottom of this article.)
The list is a roadmap that can point you in the right direction at any stage of your career. Under each job title, you can explore the most common skills, top hiring regions, remote and hybrid availability and more. And you can turn those insights into action by exploring open roles, honing your skills through LinkedIn Learning courses (free for all members until Feb. 15) or joining the conversation in the collaborative article for each featured role.
With this mind, Thomson Reuters and Lexpert hosted a panel featuring law firm leaders and industry experts discussing the challenges and trends around the use of generative AI in the legal profession.?Below are insights from an engaging and informative discussion.
Sections included:
Lawyers are excited to implement generative AI solutions
Angelo added, “We really doubled down on AI because it was just so new — not just to the legal industry, but to the world.” Under his leadership, Buchanan’s efforts to embrace AI have garnered significant attention, earning the firm recognition as one of the “Best of the Best for Generative AI” in the 2024 BTI “Leading Edge Law Firms” survey.
This acknowledgment reflects more than ambition; it highlights the firm’s ability to translate innovative ideas into actionable results. By focusing on collaboration and leveraging technology to address client demands, Buchanan has set a benchmark for what is possible in legal technology innovation.
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The collective team followed these essential steps for app development:
The rise of artificial intelligence (AI), particularly generative AI, has introduced transformative potential to legal practice. For in-house counsel, managing legal risk while driving operational efficiency increasingly involves navigating AI’s opportunities and challenges. While AI offers remarkable tools for automation and data-driven decision-making, it is essential to approach these tools as complementary to human judgment, not replacements. Effective AI adoption requires balancing its efficiencies with a commitment to ethical, nuanced legal practice.
In other words, individual learning leaders need to obtain information from surveys and studies that are directly useful in their curriculum planning. This article attempts, in these early days, to provide some specific guidelines for AI curriculum planning in enterprise organizations.
The two reports identified in the first paragraph help to answer an important question. What can enterprise L&D teams do to improve AI fluency in their organizations?
The Importance of Building a ‘Change Muscle’ The ability to test and learn, pivot quickly, and embrace change is an increasingly foundational skill that all employees, no matter the level of experience or seniority, need in 2025 and beyond. Adaptable organizations significantly outperform more change-averse peers on nearly every metric, ranging from revenue growth to employee engagement. In other words, having agility and adaptability embedded in your culture pays dividends. Although these terms are often used interchangeably, they represent distinct yet interconnected aspects of organizational success:
Agility refers to the ability to swiftly and efficiently respond to immediate challenges or opportunities. It’s about being nimble and proactive, making quick decisions, and adjusting to navigate short-term obstacles.
Adaptability is a broader concept that encompasses the capacity to evolve and thrive in the face of long-term shifts in the environment. It’s about being resilient and flexible by modifying strategies and structures to align with fundamental changes in the market or industry.
And a quick comment from DSC:
Agility and adaptability are key skills/orientations/expectations that we need to help our K-16 students build. Changes can happen quickly, as those of us who worked several decades can attest to.
Employees’ skills and abilities must match the skills and abilities required for their jobs; when they do, organizational performance and productivity improve.
Skills gaps occur when there are mismatches between employees’ skills and capabilities and the skills and capabilities needed for their work. As technology and work become more complex, identifying and correcting skills gaps become essential to optimizing employee performance.
This article discusses various methods involving skills inference and predictive analytics in addition to traditional methods to pinpoint and prevent skills gaps.
Another year, another opportunity to bring microlearning into your performance and talent development strategy! This is especially appealing as more and more organizations strive to deliver training in ways that meet the fast-paced needs of their employees.
However, implementing a microlearning strategy that aligns with organizational outcomes and sustains performance is no small feat. Learning and Development (L&D) leaders often grapple with questions like: Where do we start; How do we ensure our efforts are effective; and What factors should we evaluate?
The Microlearning Effectiveness (MLE) Framework offers a practical approach to addressing these challenges. Instead of rigid rules, the framework acts as a guide, encouraging leaders to evaluate their efforts against six key components:
NVIDIA’s Apple moment?! — from theneurondaily.com by Noah Edelman and Grant Harvey PLUS: How to level up your AI workflows for 2025…
NVIDIA wants to put an AI supercomputer on your desk (and it only costs $3,000). … And last night at CES 2025, Jensen Huang announced phase two of this plan: Project DIGITS, a $3K personal AI supercomputer that runs 200B parameter models from your desk. Guess we now know why Apple recently developed an NVIDIA allergy…
… But NVIDIA doesn’t just want its “Apple PC moment”… it also wants its OpenAI moment. NVIDIA also announced Cosmos, a platform for building physical AI (think: robots and self-driving cars)—which Jensen Huang calls “the ChatGPT moment for robotics.”
NVIDIA is bringing AI from the cloud to personal devices and enterprises, covering all computing needs from developers to ordinary users.
At CES 2025, which opened this morning, NVIDIA founder and CEO Jensen Huang delivered a milestone keynote speech, revealing the future of AI and computing. From the core token concept of generative AI to the launch of the new Blackwell architecture GPU, and the AI-driven digital future, this speech will profoundly impact the entire industry from a cross-disciplinary perspective.
From DSC: I’m posting this next item (involving Samsung) as it relates to how TVs continue to change within our living rooms. AI is finding its way into our TVs…the ramifications of this remain to be seen.
The Rundown: Samsung revealed its new “AI for All” tagline at CES 2025, introducing a comprehensive suite of new AI features and products across its entire ecosystem — including new AI-powered TVs, appliances, PCs, and more.
The details:
Vision AI brings features like real-time translation, the ability to adapt to user preferences, AI upscaling, and instant content summaries to Samsung TVs.
Several of Samsung’s new Smart TVs will also have Microsoft Copilot built in, while also teasing a potential AI partnership with Google.
Samsung also announced the new line of Galaxy Book5 AI PCs, with new capabilities like AI-powered search and photo editing.
AI is also being infused into Samsung’s laundry appliances, art frames, home security equipment, and other devices within its SmartThings ecosystem.
Why it matters: Samsung’s web of products are getting the AI treatment — and we’re about to be surrounded by AI-infused appliances in every aspect of our lives. The edge will be the ability to sync it all together under one central hub, which could position Samsung as the go-to for the inevitable transition from smart to AI-powered homes.
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“Samsung sees TVs not as one-directional devices for passive consumption but as interactive, intelligent partners that adapt to your needs,” said SW Yong, President and Head of Visual Display Business at Samsung Electronics. “With Samsung Vision AI, we’re reimagining what screens can do, connecting entertainment, personalization, and lifestyle solutions into one seamless experience to simplify your life.” — from Samsung
The following framework I offer for defining, understanding, and preparing for agentic AI blends foundational work in computer science with insights from cognitive psychology and speculative philosophy. Each of the seven levels represents a step-change in technology, capability, and autonomy. The framework expresses increasing opportunities to innovate, thrive, and transform in a data-fueled and AI-driven digital economy.
The Rise of AI Agents and Data-Driven Decisions — from devprojournal.com by Mike Monocello Fueled by generative AI and machine learning advancements, we’re witnessing a paradigm shift in how businesses operate and make decisions.
AI Agents Enhance Generative AI’s Impact Burley Kawasaki, Global VP of Product Marketing and Strategy at Creatio, predicts a significant leap forward in generative AI. “In 2025, AI agents will take generative AI to the next level by moving beyond content creation to active participation in daily business operations,” he says. “These agents, capable of partial or full autonomy, will handle tasks like scheduling, lead qualification, and customer follow-ups, seamlessly integrating into workflows. Rather than replacing generative AI, they will enhance its utility by transforming insights into immediate, actionable outcomes.”
Everyone’s talking about the potential of AI agents in 2025 (and don’t get me wrong, it’s really significant), but there’s a crucial detail that keeps getting overlooked: the gap between current capabilities and practical reliability.
Here’s the reality check that most predictions miss: AI agents currently operate at about 80% accuracy (according to Microsoft’s AI CEO). Sounds impressive, right? But here’s the thing – for businesses and users to actually trust these systems with meaningful tasks, we need 99% reliability. That’s not just a 19% gap – it’s the difference between an interesting tech demo and a business-critical tool.
This matters because it completely changes how we should think about AI agents in 2025. While major players like Microsoft, Google, and Amazon are pouring billions into development, they’re all facing the same fundamental challenge – making them work reliably enough that you can actually trust them with your business processes.
Think about it this way: Would you trust an assistant who gets things wrong 20% of the time? Probably not. But would you trust one who makes a mistake only 1% of the time, especially if they could handle repetitive tasks across your entire workflow? That’s a completely different conversation.
In the tech world, we like to label periods as the year of (insert milestone here). This past year (2024) was a year of broader experimentation in AI and, of course, agentic use cases.
As 2025 opens, VentureBeat spoke to industry analysts and IT decision-makers to see what the year might bring. For many, 2025 will be the year of agents, when all the pilot programs, experiments and new AI use cases converge into something resembling a return on investment.
In addition, the experts VentureBeat spoke to see 2025 as the year AI orchestration will play a bigger role in the enterprise. Organizations plan to make management of AI applications and agents much more straightforward.
Here are some themes we expect to see more in 2025.
AI agents take charge
Jérémy Grandillon, CEO of TC9 – AI Allbound Agency, said “Today, AI can do a lot, but we don’t trust it to take actions on our behalf. This will change in 2025. Be ready to ask your AI assistant to book a Uber ride for you.” Start small with one agent handling one task. Build up to an army.
“If 2024 was agents everywhere, then 2025 will be about bringing those agents together in networks and systems,” said Nicholas Holland, vice president of AI at Hubspot. “Micro agents working together to accomplish larger bodies of work, and marketplaces where humans can ‘hire’ agents to work alongside them in hybrid teams. Before long, we’ll be saying, ‘there’s an agent for that.'”
… Voice becomes default
Stop typing and start talking. Adam Biddlecombe, head of brand at Mindstream, predicts a shift in how we interact with AI. “2025 will be the year that people start talking with AI,” he said. “The majority of people interact with ChatGPT and other tools in the text format, and a lot of emphasis is put on prompting skills.
Biddlecombe believes, “With Apple’s ChatGPT integration for Siri, millions of people will start talking to ChatGPT. This will make AI so much more accessible and people will start to use it for very simple queries.”
Get ready for the next wave of advancements in AI. AGI arrives early, AI agents take charge, and voice becomes the norm. Video creation gets easy, AI embeds everywhere, and one-person billion-dollar companies emerge.
To better understand the types of roles that AI is impacting, ZoomInfo’s research team looked to its proprietary database of professional contacts for answers. The platform, which detects more than 1.5 million personnel changes per day, revealed a dramatic increase in AI-related job titles since 2022. With a 200% increase in two years, the data paints a vivid picture of how AI technology is reshaping the workforce.
Why does this shift in AI titles matter for every industry?
Per The Rundown: OpenAI just launched a surprising new way to access ChatGPT — through an old-school 1-800 number & also rolled out a new WhatsApp integration for global users during Day 10 of the company’s livestream event.
Agentic AI represents a significant evolution in artificial intelligence, offering enhanced autonomy and decision-making capabilities beyond traditional AI systems. Unlike conventional AI, which requires human instructions, agentic AI can independently perform complex tasks, adapt to changing environments, and pursue goals with minimal human intervention.
This makes it a powerful tool across various industries, especially in the customer service function. To understand it better, let’s compare AI Agents with non-AI agents.
… Characteristics of Agentic AI
Autonomy: Achieves complex objectives without requiring human collaboration.
Language Comprehension: Understands nuanced human speech and text effectively.
Rationality: Makes informed, contextual decisions using advanced reasoning engines.
Adaptation: Adjusts plans and goals in dynamic situations.
Workflow Optimization: Streamlines and organizes business workflows with minimal oversight.
How, then, can we research and observe how our systems are used while rigorously maintaining user privacy?
Claude insights and observations, or “Clio,” is our attempt to answer this question. Clio is an automated analysis tool that enables privacy-preserving analysis of real-world language model use. It gives us insights into the day-to-day uses of claude.ai in a way that’s analogous to tools like Google Trends. It’s also already helping us improve our safety measures. In this post—which accompanies a full research paper—we describe Clio and some of its initial results.
Evolving tools redefine AI video — from heatherbcooper.substack.com by Heather Cooper Google’s Veo 2, Kling 1.6, Pika 2.0 & more
AI video continues to surpass expectations
The AI video generation space has evolved dramatically in recent weeks, with several major players introducing groundbreaking tools.
Here’s a comprehensive look at the current landscape:
Veo 2…
Pika 2.0…
Runway’s Gen-3…
Luma AI Dream Machine…
Hailuo’s MiniMax…
OpenAI’s Sora…
Hunyuan Video by Tencent…
There are several other video models and platforms, including …
Best of 2024 — from wondertools.substack.com by Jeremy Caplan 12 of my favorites this year
I tested hundreds of new tools this year. Many were duplicative. A few stuck with me because they’re so useful. The dozen noted below are helping me mine insights from notes, summarize meetings, design visuals— even code a little, without being a developer. You can start using any of these in minutes — no big budget or prompt engineering PhD required.
And you thought return to office policy was settled! For a while, it looked like 2-3 days per week in the office would be the future of work in America.
Yet this quarter has brought significant changes to the landscape. Major companies like Amazon, Dell, and The Washington Post announced their plans for a full return to office. Then came a shift in the political atmosphere, with Trump’s victory and potential incoming changes requiring full-time office work for government employees.
These developments raise important questions about where workplace flexibility is headed. Are we witnessing the beginning of a broader shift back to Full Time In Office? Is the era of fully flexible work coming to an end? Or is this simply another evolution in how companies structure their workplace policies?
In this report, we dig into US-wide trends to see if the high-profile shifts toward Full Time In Office reflect broader market movement or just isolated cases. We examine how different industries are approaching flexibility, from Technology’s continued embrace to the challenges faced by sectors dependent on physical presence. Plus, we explore the divide in how companies of different sizes approach workplace flexibility. Are we truly heading back to the office full time, or is the future of work more nuanced than the headlines suggest?
Today we’re excited to launch our next era of models built for this new agentic era: introducing Gemini 2.0, our most capable model yet. With new advances in multimodality — like native image and audio output — and native tool use, it will enable us to build new AI agents that bring us closer to our vision of a universal assistant.
We’re getting 2.0 into the hands of developers and trusted testers today. And we’re working quickly to get it into our products, leading with Gemini and Search. Starting today our Gemini 2.0 Flash experimental model will be available to all Gemini users. We’re also launching a new feature called Deep Research, which uses advanced reasoning and long context capabilities to act as a research assistant, exploring complex topics and compiling reports on your behalf. It’s available in Gemini Advanced today.
Over the last year, we have been investing in developing more agentic models, meaning they can understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision.
Today, we’re sharing the latest updates to Gemini, your AI assistant, including Deep Research — our new agentic feature in Gemini Advanced — and access to try Gemini 2.0 Flash, our latest experimental model.
Deep Research uses AI to explore complex topics on your behalf and provide you with findings in a comprehensive, easy-to-read report, and is a first look at how Gemini is getting even better at tackling complex tasks to save you time.1
Google Unveils A.I. Agent That Can Use Websites on Its Own — from nytimes.com by Cade Metz and Nico Grant (NOTE: This is a GIFTED article for/to you.)
The experimental tool can browse spreadsheets, shopping sites and other services, before taking action on behalf of the computer user.
Google on Wednesday unveiled a prototype of this technology, which artificial intelligence researchers call an A.I. agent.
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Google’s new prototype, called Mariner, is based on Gemini 2.0, which the company also unveiled on Wednesday. Gemini is the core technology that underpins many of the company’s A.I. products and research experiments. Versions of the system will power the company’s chatbot of the same name and A.I. Overviews, a Google search tool that directly answers user questions.
Google Gemini 2.0 — a major upgrade to the core workings of Google’s AI that the company launched Wednesday — is designed to help generative AI move from answering users’ questions to taking action on its own…
… The big picture: Hassabis said building AI systems that can take action on their own has been DeepMind’s focus since its early days teaching computers to play games such as chess and Go.
“We were always working towards agent-based systems,” Hassabis said. “From the beginning, they were able to plan and then carry out actions and achieve objectives.”
Hassabis said AI systems that can act as semi-autonomous agents also represent an important intermediate step on the path toward artificial general intelligence (AGI) — AI that can match or surpass human capabilities.
“If we think about the path to AGI, then obviously you need a system that can reason, break down problems and carry out actions in the world,” he said.
The same paradigm applies to AI systems. AI assistants function as reactive tools, completing tasks like answering queries or managing workflows upon request. Think of chatbots or scheduling tools. AI agents, however, work autonomously to achieve set objectives, making decisions and executing tasks dynamically, adapting as new information becomes available.
Together, AI assistants and agents can enhance productivity and innovation in business environments. While assistants handle routine tasks, agents can drive strategic initiatives and problem-solving. This powerful combination has the potential to elevate organizations, making processes more efficient and professionals more effective.
Meet NVIDIA – The Engine of AI. From gaming to data science, self-driving cars to climate change, we’re tackling the world’s greatest challenges and transforming everyday life. The Microsoft and NVIDIA partnership enables Startups, ISVs, and Partners global access to the latest NVIDIA GPUs on-demand and comprehensive developer solutions to build, deploy and scale AI-enabled products and services.
The swift progress of artificial intelligence (AI) has simplified the creation and deployment of AI agents with the help of new tools and platforms. However, deploying these systems beneath the surface comes with hidden challenges, particularly concerning ethics, fairness and the potential for bias.
The history of AI agents highlights the growing need for expertise to fully realize their benefits while effectively minimizing risks.
