By Julie Henson and Greg Hamman ( March 24, 2025, 2:50 PM EDT) — Data from the last quarter of 2024 shows law firm partner mobility continues to increase, and the buyers’ market that emerged in the third quarter continues to shift in favor of firms looking to hire…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

Adapting to new forms of communication and behavior So the question is not how hiring managers connect with young job candidates who, if they are well-educated, will have many job offers in a tight labor market. Rather, the question is how companies can adapt to new communication and social forms as well as changing value systems — regardless of the generation of applicants and job candidates. The answer lies in a changing system. Although Generation Z is having a catalytic effect on changing values within society, it is not the trigger. When people place more value on work-life balance, it can lead to conflicts in traditional work environments that require overtime or constant availability. For example, we offer our employees the option of working from their home office two days a week. This provides the necessary flexibility and space for balance. And it benefits mental health. A value-oriented corporate culture is a must Due to multiple crises (war, climate and inflation), employees are increasingly looking for a value-oriented corporate culture. Sustainable action and social responsibility are in demand — companies that falter here will find it difficult to attract and retain talent from Generation Z (and others). This in turn involves fine-tuning the company’s processes. source

I’ve had the privilege of taking over digital asset management (DAM) system research from my Forrester colleague Chuck Gahun this year, which means I’ve spent the last 60 days immersed, receiving briefings from several dozen vendors, attending events including the Henry Stewart DAM conference in Los Angeles, and getting the scoop on content supply chain at Adobe Summit. As I finish writing my first DAM report, the upcoming “Strategic Technology Selection Guide For Digital Asset Management Systems,” my take is that the opportunities are vast for both DAM vendors and users as DAMs evolve from their traditional role as “systems of record” for rich media and content assets to AI-powered “systems of action.” Below are six capabilities that are increasing their fidelity in DAMs and will likely have a big impact on the future of digital experiences: AI integration and automation. AI continues to shake things up in the DAM space, saving time and creative resources. More vendors are offering AI to generate asset renditions, take over repetitive tasks, and boost metadata management through automatic tagging. They’re ramping up productivity while keeping content relevant and accessible across different markets, such as through video transcription and localization. Personalization for all. It’s a given that audiences and customers want personalized digital experiences, but so do the marketers who deliver those experiences. In addition to expanding tailored content delivery through rich media transformation, many DAM solutions offer customizable, brand-compliant portals and personalized user interfaces, improving the marketer experience. Enhanced content discovery and management. Vendors are investing in AI-powered natural language search and content discovery tools that make digital assets easily accessible and manageable, boosting efficiency and improving the overall user experience. Support for emerging content types. New content formats like 3D models and AR/VR experiences are on the rise, presenting DAM vendors the opportunity to expand their offerings, including tighter integration with e-commerce platforms that enhance customer engagement. Focus on compliance and security. With more regulatory requirements and an increasing volume of AI-generated content, DAM vendors are prioritizing compliance and security, expanding rights management with features such as forensic watermarking, and automating brand and compliance checks. Sustainability initiatives. As businesses become more environmentally conscious, DAM vendors that support sustainability initiatives will have a competitive edge. Many are committing to reducing digital carbon footprints and optimizing data storage efficiency by continuously optimizing and offloading assets to cold storage so that they can align with their clients’ environmental goals. I have captured this and more in the upcoming “Strategic Technology Selection Guide For Digital Asset Management Systems,” which will help technology and digital business leaders find the right solution to engage better with their target customers. source

If you are a business that regularly makes international payments to global suppliers, choosing an international bank that offers free or low-cost worldwide transfer fees, speedy processing, and multiple currencies is vital. The availability of digital banking is also a critical factor in making cross-border payments faster and more affordable. These create a competitive advantage for companies intent on expanding their markets globally. Here, I’ve reviewed the 9 best banks for international business. Best overall bank for international business: Bluevine Provider is a fintech platform, not a bank. It provides FDIC insurance and deposit services through a partnership with Coastal Community Bank. (high APY and reduced fees from higher-tier accounts) Best for low transparent fees and speedy fund access: Novo Provider is a fintech platform, not a bank. It provides FDIC insurance and deposit services through a partnership with Middlesex Federal Savings. Best for free USD international wires: Mercury Mercury is a fintech company, not an FDIC-insured bank. Banking services provided by Choice Financial Group and Evolve Bank & Trust ®️; Members FDIC. Deposit insurance covers the failure of an insured bank. Best for full-suite banking products and premium checking: Chase Member FDIC Best for multi-member teams needing more accounts and debit cards: Relay Provider is a fintech platform, not a bank. It provides FDIC insurance and deposit services through a partnership with Thread Bank. Best for flat fee rate for non-USD transfers: Rho Provider is a fintech platform, not a bank. It provides FDIC insurance and deposit services through a partnership with Webster Bank N.A., member FDIC. International and foreign currency payments services are provided by Wise US Inc. Best overall bank for international business: Bank of America Member FDIC Best for fast transfers and conversion fee savings: Airwallex Provider is a fintech platform, not a bank. It provides FDIC insurance and deposit services through a partnership with Evolve Bank & Trust. Best for multi-currency accounts and plan options: Revolut Provider is a fintech platform, not a bank. It provides FDIC insurance and deposit services through a partnership with Community Federal Savings Bank (CFSB) and Sutton Bank. Best for cost-effective international payments: Wise Provider is a fintech platform, not a bank. It provides FDIC insurance and deposit services through a partnership with Community Federal Savings Bank. Best international banks for business comparison Below is a summary of the top features I considered for the 9 financial providers. Here is our list of the best banks for international business. Our rating (out of 5) Charges monthly fees Offers annual percentage yield (APY) Number of countries & currencies Available payment methods Bluevine Standard 4.23 No Yes Countries: 32Currencies: 15 ACH, wire transfers, international payments, checks, and debit cards Novo Business Checking 4.20 No No Countries: 150-plusCurrencies: 50 Online ACH, digital wallets, international transfers via Wise, and Stripe Mercury Business Checking 4.17 No No Countries: 160-plusCurrencies: 30-plus ACH transfers, wire transfers, digital wallets, checks, and Stripe Chase Business Performance Banking 4.07 Yes No Countries: 140-plusCurrencies: 40-plus Digital wallets, debit and credit cards, wire transfers, ACH transfers, and Zelle Relay Business Checking 4.07 No No Countries: 200-plusCurrencies: 32 ACH transfers, domestic and international wire transfers, and checks Rho Business Checkingt 4.04 No No Countries: 200-plusCurrencies: 32 ACH, domestic and international SWIFT wire transfers, FX transfers, and checks Airwallex Global Account 3.93 No No Countries: 150-plusCurrencies: 23-plus Credit cards, digital wallets, e-wallets, bank transfers, and direct debit Wise Business Account 3.92 No Yes, optional Countries: 150-plusCurrencies: 40-plus Bank transfers, debit and credit cards, ACH, international transfers, and digital wallets Revolut Basic Business Account 3.91 No No Countries: 150-plusCurrencies: 36 in-app Revolut payment gateway, international transfers, and debit and credit cards Bluevine: Best overall bank for international business Our rating: 4.23 out of 5 Image: Bluevine Bluevine is a solid fintech company with three business checking options, a credit card with unlimited cash back, and an outstanding line of credit. On top of that, it offers fast international business payments with a turnaround of 24 hours Payments are received from 8 a.m. to 5 p.m. ET every business day. Timing may vary based on sender bank and country, and whether payment is sent during business hours. . Customers can send payments in 15 currencies to 32 countries, except for businesses based in Nevada or those categorized under finance, insurance, or mining. Bluevine pricing is transparent for overseas payments. Under the standard account, you will be charged $25 for each USD payment, while a fee of $25 plus 1.5% of the payment in USD conversion will be charged for FX transactions. Subscribing to higher plans reduces the payment charges to $20 (Plus) and $12.50 (Premier). Check out why I included Bluevine in our best online business bank accounts. Why we chose it I chose Bluevine as the overall best bank for international businesses because of its competitive interest rates. With an entry-level Bluevine Standard account, you can earn 1.5% AP The APY for Bluevine Standard applies to balances up to $250,000. by either spending a minimum of $500 using your Bluevine debit or credit card or by receiving $2,500 in monthly payments in your checking account. As your balances grow, you can switch to premium accounts with more benefits, including a higher APY and reduced fees for sending international payments. Monthly fees Bluevine Standard: $0 Bluevine Plus: $30; waivable by having: An ADB of $20,000 across your Bluevine checking account, including subaccounts. A spend of $2,000 monthly using your Bluevine debit card or credit card. Bluevine Premier: $95; waivable by meeting: An ADB of $100,000 across your Bluevine checking account, including subaccounts. A spend of $5,000 monthly using your Bluevine debit card or credit card. Features International payments to 32 countries in 15 currencies. Reduced wire transfer fees and same-day ACH fees for higher-tier accounts. FDIC insurance of up to $3 million. Unlimited transactions. QuickBooks, Xero, Expensify, and Wave integrations. Compatible with Wise, Venmo, CashApp, and Square. Lines of credit up to $250,000 at low rates. No annual fee and an unlimited 1.5% cash back

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A new framework called METASCALE enables large language models (LLMs) to dynamically adapt their reasoning mode at inference time. This framework addresses one of LLMs’ shortcomings, which is using the same reasoning strategy for all types of problems. Introduced in a paper by researchers at the University of California, Davis, the University of Southern California and Microsoft Research, METASCALE uses “meta-thoughts”—adaptive thinking strategies tailored to each task—to improve LLM performance and generalization across various tasks.  This approach can offer enterprises a way to enhance the accuracy and efficiency of their LLM applications without changing models or engaging in expensive fine-tuning efforts. The limitations of fixed reasoning Strategies One of the main challenges of LLM applications is their fixed and inflexible reasoning behavior. Unlike humans, who can consciously choose different approaches to solve problems, LLMs often rely on pattern matching from their training data, which may not always align with sound reasoning principles that humans use.  Current methods for adjusting the reasoning process of LLMs, such as chain-of-thought (CoT) prompting, self-verification and reverse thinking, are often designed for specific tasks, limiting their adaptability and effectiveness across diverse scenarios.  The researchers point out that “these approaches impose fixed thinking structures rather than enabling LLMs to adaptively determine the most effective task-specific strategy, potentially limiting their performance.” To address this limitation, the researchers propose the concept of “meta-thinking.” This process allows LLMs to reflect on their approach before generating a response. Meta-thoughts guide the reasoning process through two components inspired by human cognition: Cognitive mindset: The perspective, expertise, or role the model adopts to approach the task. Problem-solving strategy: A structured pattern used to formulate a solution for the task based on the chosen mindset. Instead of directly tackling a problem, the LLM first determines how to think, selecting the most appropriate cognitive strategy. For example, when faced with a complex software problem, the LLM might first think about the kind of professional who would solve it (e.g., a software engineer) and choose a strategy to approach the problem (e.g., using design patterns to break down the problem or using a micro-services approach to simplify the deployment).  “By incorporating this meta-thinking step, LLMs can dynamically adapt their reasoning process to different tasks, rather than relying on rigid, predefined heuristics,” the researchers write. Building upon meta-thoughts, the researchers introduce METASCALE, a test-time framework that can be applied to any model through prompt engineering.  “The goal is to enable LLMs to explore different thinking strategies, and generate the most effective response for a given input,” they state. METASCALE operates in three phases: Initialization: METASCALE generates a diverse pool of reasoning strategies based on the input prompt. It does this by prompting the LLM to self-compose strategies and leveraging instruction-tuning datasets containing reasoning templates for different types of problems. This combination creates a rich initial pool of meta-thoughts. Selection: A Multi-Armed Bandit (MAB) algorithm selects the most promising meta-thought for each iteration. MAB is a problem framework where an agent must repeatedly choose between multiple options, or “arms,” each with unknown reward distributions. The core challenge lies in balancing “exploration” (e.g., trying different reasoning strategies) and “exploitation” (consistently selecting the reasoning strategy that previously provided the best responses). In METASCALE, each meta-thought is treated as an arm, and the goal is to maximize the reward (response quality) based on the selected meta-thought. Evolution: A genetic algorithm refines and expands the pool of cognitive strategies iteratively. METASCALE uses high-performing meta-thoughts as “parents” to produce new “child” meta-thoughts. The LLM is prompted to develop refined meta-thoughts that integrate and improve upon the selected parents. To remain efficient, METASCALE operates within a fixed sampling budget when generating meta-thoughts.  The researchers evaluated METASCALE on mathematical reasoning benchmarks (GSM8K), knowledge and language understanding (MMLU-Pro), and Arena-Hard, comparing it to four baseline inference methods: direct responses (single-pass inference), CoT, Best-of-N (sampling multiple responses and choosing the best one), and Best-of-N with CoT. They used GPT-4o and Llama-3.1-8B-Instruct as the backbone models for their experiments. The results show that METASCALE significantly enhances LLM problem-solving capabilities across diverse tasks, consistently outperforming baseline methods. METASCALE achieved equal or superior performance compared to all baselines, regardless of whether they used CoT prompting. Notably, GPT-4o with METASCALE outperformed o1-mini under style control. “These results demonstrate that integrating meta-thoughts enables LLMs to scale more effectively during test time as the number of samples increases,” the researchers state. As the number of candidate solutions increased, METASCALE showed significantly higher gains than other baselines, indicating that it is a more effective scaling strategy. Implications for the enterprise As a test-time technique, METASCALE can help enterprises improve the quality of LLM reasoning through smart prompt engineering without the need to fine-tune or switch models. It also doesn’t require building complex software scaffolding on top of models, as the logic is completely provided by the LLM itself. By dynamically adjusting the reasoning strategies of LLMs, METASCALE is also practical for real-world applications that handle various reasoning tasks. It is also a black-box method, which can be applied to open-source models running on the enterprise cloud or closed models running behind third-party APIs. It shows promising capabilities of test-time scaling techniques for reasoning tasks. source

  The enterprise world is on the brink of a fundamental transformation, and I believe we’re underestimating just how deep it will go. Over the past month, I’ve had a series of epiphanies about generative AI, knowledge graphs, and AI agents. What I’m now seeing is a reinvention of one of management’s most foundational practices: continuous learning and improvement. The classic continuous improvement models such as Deming and Juran were meant to drive cycles of progress through measurement and feedback and, in the broad history of management, were enormous contributions to progress. But let’s be honest: In too many organizations, they devolved into bureaucratic rituals. Continuous improvement became a department, a toolbox, not a way of working and being. Feedback loops broke. The data was stale. The insights, pro forma and shallow. The excitement, gone. That changes now. Unlocking Your Knowledge Is Finally Possible We are seeing the reemergence of continuous learning and improvement at enterprise scale but, this time, fueled by AI, operationalized through agents, structured in graphs, and enriched with live telemetry. Imagine the modern enterprise as an organism constantly producing digital exhaust: transactions, reports, artifacts, documents, source code, logs, alerts, collaboration threads, service tickets. Far from being waste, this exhaust holds untold potential to fuel innovation, growth, and continuous learning. For decades, though, we lacked the means to turn this torrent of information into coherent, trustworthy, operationalized knowledge. Knowledge management tried to harness it but struggled under the weight of manual curation, siloed formats, and weak engagement. With the convergence of genAI, retrieval-augmented generation (RAG), knowledge graphs, and autonomous agents, we stand at the edge of a new era. Why It Works Now The new feedback loop is radically different. It looks like this: Enterprise operations continue as they always have: massive estates of digital and physical complexity. They generate data and information: records of activity, structured or unstructured. Harvester AI agents (empowered by large language models [LLMs]) observe and interpret the information in real time and structure and curate it into a semantic graph. Connected, unstructured information is translated into embeddings in a vector store.* They monitor for quality, semantic drift, alignment gaps, emergent patterns, and unknown unknowns, feeding raw data into LLMs for synthesis and analysis. Operational agents continuously analyze the graph and vectors, comparing new information with previous, making the knowledge alive and actionable — and feeding it back to step one. And unlike human analysts, agents don’t get tired. You can have dozens running, constantly surfacing insights, looking for contradictions, comparing past patterns with current anomalies, and suggesting actions. They aren’t replacing judgment — they’re finally making relevant, continuous feedback real. The control and improvement of these agents will be a significant task; humans will work with TuringBots (LLM-based coding engines) to evolve them continuously. This Isn’t Just About IT To be clear, this applies well beyond IT. The IT industry — where Forrester has documented the rise of a new control plane architecture — and its telemetry is already rich and digitized, therefore well suited to reap these new benefits. Vendors such as ServiceNow, Atlassian, and Wiz are already implementing large-scale graphs. But every function in the enterprise can start moving toward graph-driven, agent-enabled learning: sales, marketing, R&D, HR, finance, risk, supply chain, customer service, etc. Any domain that produces traceable work can benefit. Why Graphs Are Essential It’s tempting to think that LLMs alone can solve this. But we’re finding that, without structure, genAI alone drifts. The graph is essential. It is the skeleton to the LLM’s flesh. Graphs allow agents to: Track dependencies across domains. Represent evolving relationships (versioned capabilities, changing ownership, dynamic markets). Identify semantic similarity and drift. Enable reasoning over time. We can stop treating knowledge management as a static repository and instead see it as a living, navigable, self-healing system. Systems thinkers know that there is nothing more powerful than a true reinforcing (“positive”) feedback loop. I believe this is now forming, and major new feedback loops in the economy don’t appear all that often — the “network effect” observed in the early internet days is the most obvious comparison. Yes, there will be balancing dynamics: security, privacy — but most of what I am talking about here can take place within the boundaries of an enterprise, assuming that it can afford to run its own large-scale LLMs. There will be many experiments. Are the agents acting as advisors? Regulators? Traffic cops? Auditors? Judge and jury … ? People are going to try all of these. (We’ll need responsibility assignment tools for agents … agentic decision rights, to coin a new term, will be a new business analysis challenge.) Implications For The Enterprise Enterprise architects and CIOs must rethink knowledge systems not as forms-based or document-centric but as graph-centric, with unstructured information a first-class operational citizen, all with continuous agent interaction. Vendors must offer agent-integrated platforms that allow customers to define, extend, and control their semantic models. Venture capitalists, acquirers, and enterprise customers should look for graph-native architectures and agent ecosystems in their due diligence, as well as LLMs and RAG. Knowledge governance must evolve to accommodate autonomous curation, semantic versioning, and feedback validation. Every operating model needs a feedback loop that includes telemetry capture, AI interpretation, graph enrichment, and agent-led action. The Historical Parallel You have to go back to the early 20th century — to the creation of the modern corporate operating model at General Motors and DuPont — to find a change this significant. Back then, accounting and management science reshaped industrial capitalism. I believe that genAI, agents, and graphs will have comparable impact on digital capitalism. It’s time to move beyond the brittle forms of continuous improvement we inherited from midcentury management. Let’s reclaim its spirit and deliver on its promise, with tools that can finally make it real. The new feedback loop is not a theory. It’s starting to happen. Will your organization lead or follow?   *And the graph itself can have vector embeddings, but I’ll save that rabbit hole for the footnote.

Microsoft Project and Smartsheet are two popular project management software platforms that offer a more traditional user interface design. They may seem similar at first glance, but once I started reviewing both solutions, the differences became apparent. Microsoft Project is a better choice for power users who are comfortable with highly advanced features. It mostly integrates with other Microsoft products and relies on some of them for key functionality, so it’s best used by teams that are already committed to the Microsoft ecosystem. Smartsheet is a good option for teams that are managing their projects in spreadsheets and need an upgrade to dedicated project management software. It also offers more than 100 integrations with third-party software, making it a better choice for teams with a more diverse software stack. Though existing Microsoft customers may feel at home with Microsoft Project, the best choice in terms of pure project management software capabilities is Smartsheet. 1 monday.com Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Agile Development, Analytics / Reports, API, and more 2 Wrike Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Medium, Large, Enterprise Features Agile Development, Analytics / Reports, API, and more 3 Smartsheet Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Agile Development, Analytics / Reports, API, and more Microsoft Project vs. Smartsheet: Comparison table After hands-on reviews of the best project management software, we’ve created a scoring rubric to use when comparing solutions like Microsoft Project and Smartsheet. While close, Smartsheet edges out Microsoft Project for best overall pick in our eyes. Microsoft Project Smartsheet Winner Features 3.9 4.6 Smartsheet Pricing 2.8 2.3 Smartsheet Ease of use 1.8 3.5 Smartsheet Service & support 4.2 3.8 Microsoft Projec Overall 3.4 3.8 Smartsheet Microsoft Project vs. Smartsheet: Which is better? Microsoft Project: Better for Microsoft-aligned teams Use Microsoft Projects if you need highly advanced project management software, your team comprises power users who aren’t intimidated by the higher learning curve, your company is already committed to the Microsoft ecosystem, you don’t need integrations with third-party software, or you want or need an on-premises deployment option. Microsoft Project pros and cons Pros Cons Very detailed project planning tools Integrates well with other Microsoft products Has many built-in resource management tools Very long learning curve due to all the complex features Lacks integrations for non-Microsoft tool Lacks native communication tools Smartsheet: Better for teams with diverse software stacks Use Smartsheet if you want a more cost-effective software platform, you are looking for an upgrade from spreadsheets and want a familiar-looking interface, you want a lower learning curve than Microsoft Project, you need integrations with third-party software, or you don’t need on-premises deployment. Smartsheet pros and cons Pros Cons Familiar user interface due to the spreadsheet base Allows high level of customization Offers a lot of documentation and training resources Not as user-friendly and intuitive as other project management apps Lacks auto-save feature and real-time project update Requires upgrading to Business plan for time tracking and research management Microsoft Project vs. Smartsheet pricing Microsoft offers more plans and on-premises options to choose from than Smartsheet. However, Smartsheet is more affordable than Microsoft Project overall. Both vendor solutions offer a 30-day free trial for certain plans. Microsoft Project pricing Cloud-based subscriptions: Microsoft Planner: Part of Microsoft 365, which starts at $8.00 per user per month Planner Plan 1: $10.00 per user per month, billed annually Planner and Project Plan 3: $30.00 per user per month, billed annually Planner and Project Plan 5: $55.00 per user per month, billed annually Microsoft Project is only available as annual subscriptions, and the vendor breaks down plans by per-user-per-month price. See the table below for the monthly snapshot and the annual price you can expect to pay for each subscription. Plan Monthly Price* Annual Price Planner $8.00 $96.00 Planner Plan 1 $10.00 $120.00 Planner and Project Plan 3 $30.00 $360.00 Planner and Project Plan 4 $55.00 $660.00 *While Microsoft lists plans with monthly prices, all plans are billed annually. On-premises solutions: Project Standard 2024: $719.99 for a license for one PC Project Professional 2024: $1,409.99 for a license for one PC Project Server Plan: Contact for custom pricing quote For more information, read our full Microsoft Project review and view our list of Microsoft Project alternatives. Smartsheet pricing Pro: $9.00 per user per month billed annually, or $12.00 per user per month billed monthly Business: $19.00 per user per month billed annually, or $24.00 per user per month billed monthly Enterprise: Contact for custom pricing quote Advanced Work Management: Contact for custom pricing quote Smartsheet plans include monthly and annual options for users looking to avoid vendor lock-in with a monthly plan or want to save more with a yearly subscription. See the table below for a look at the monthly plan rates and the savings included in selecting an annual plan. Plan Monthly Plan Annual Plan Per Month Annual Plan Total Pro $12.00 $9.00 $108.00 Business $24.00 $19.00 $228.00 Enterprise & Advanced Work Management Quote Quote Quote For more information, read our full Smartsheet review and view our list of Smartsheet alternatives. Microsoft Project vs. Smartsheet: Feature comparison Project management Winner: Smartsheet Microsoft Project got a 3.9/5 for features overall on our scoring rubric. It offers three main project views: grid, board, and timeline (Gantt) view. The design is similar to other Microsoft products, but I didn’t find the interface particularly intuitive to use, and the sheer number of features can be overwhelming and makes it difficult to find what you need. But what’s impressive about Microsoft Project is that it gives you the option to get very detailed with resource management, such as tracking costs of materials over the course of a project or seeing how much time an individual has spent on

AI can also be used to enable a much more decentralized data infrastructure by having a centralized intelligence that employs agentic AI to manage the decentralized infrastructure. Hundreds of thousands of agents can enforce standards and ensure data consistency, which, according to Sáiz, is one of the biggest challenges companies face in regard to data infrastructure. For example, AI can help ensure the systems of records of a particular client are consistent in all systems including CRM, contact center software, and financial applications. “To maintain consistency, whenever there’s a customer interaction with a contact center or with the web, all systems get the change in near real time,” says Sáiz. “Where you used to have more latency and lots of manual checks before, now it’s all driven by AI, which constantly checks on the state and the master data set to determine, based on intelligence, whether a record needs to be updated in the whole system.” Beatriz Sanz Sáiz, global AI sector leader, EY EY According to Sáiz, knowledge is becoming more important than data because it helps interpret the data. A knowledge layer can be built on top of the data infrastructure to provide context and minimize hallucinations. “If somebody in telco runs a forecasting model, the variables, inputs, and results will be different than running the same model for financial forecasting,” she says. “The more you focus on knowledge, the more accurate your AI.” source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has finally added a long-requested feature for ChatGPT users: the ability to reference internal knowledge sources.  ChatGPT Team users, one of the company’s paid tiers, can connect internal knowledge databases directly to the platform during this beta period, bringing company-specific information. A feature many enterprises say would give better responses to questions. This lets users perform semantic searches of their data, link directly to internal sources in responses, get the most relevant and up-to-date context, and ensure that ChatGPT understands internal company lingo.  Right now, ChatGPT Team admins can connect Google Drive to ChatGPT. However, Nate Gonzales, a product manager at OpenAI, said in a LinkedIn post that the team “is already working on the next wave of connectors, aiming to support all the key internal knowledge sources your team relies on today.” These could include data analytics platforms and CRMs. “One of my favorite parts: over time, the model learns your org’s unique language—project names and acronyms, and team-specific terms—while respecting your user permissions so responses are grounded in the right context. (We love our codenames at OpenAI ?),” Gonzales said.  Internal documents lead to better institutional knowledge By connecting internal knowledge bases, ChatGPT Team could become more invaluable to users who already ask the platform strategy questions or for analysis. Querying company and domain-specific data gives users more context for their conversations and makes AI chatbots more useful.  Unsurprisingly, many companies with AI platforms, chatbots, agents, or applications tout their proprietary internal knowledge graphs as a differentiator. This is also why enterprise search is a rising area of enterprise AI.  Companies like Glean offer a way to use AI to find information throughout companies. ServiceNow acquired MoveWorks in a bid to boost its enterprise search capabilities.  OpenAI already lets people upload documents directly from Google Drive or Microsoft’s OneDrive. Google brought the power of Gemini to its Workspace product, meaning users could ask the model questions about their work while in a file. Perplexity added the capability to use internal documents as data sources.  Control and customization  OpenAI said controls around the data sources will look different for some users.  While only admins can add data connectors, users from smaller teams can configure when ChatGPT will tap into internal knowledge bases and which drives. However, larger teams require the administrator to decide which shared Google Drives can be accessed. OpenAI said that ChatGPT knows when to access connected data sources for many common prompts. Users can still select “Internal Knowledge” in the message composer.  The company said ChatGPT “fully respects existing organization settings and permissions,” so users who do not have access to specific drives or documents cannot force ChatGPT to read those. source

As early flowers start to bloom, Amazon holds another sale — its Big Spring Sale discounts are available to customers with or without a Prime membership. We selected some of Amazon’s best deals on tech products, focusing on tools you can use for work; where possible, we focused on deals that approach or reach 50% off. Amazon technically takes up to 40% during this specific sale, but we expanded our search to include deeper current deals. Amazon’s Big Spring Sale runs until March 31. Beats Studio Pro Headphones: Amazon Ring Stick Up Cam Pro Home Security Camera: Amazon DREAME X40 Ultra Robotic Vacuum: Amazon Lenovo Tab M9 Tablet: Amazon Motorola Moto G Power 5G: Amazon Note: The pricing and product availability information was accurate at the time of publication. Beats Studio Pro Headphones The sale applies to most color variants of the Beats Studio Pro headphones. Image: Amazon For Amazon’s Big Spring Sale, these wireless, noise-cancelling headphones are 49% off, dropping from $349.99 to $179.95. The headphones interface with either Apple or Android phones. Switch between listening to music and taking work calls – or between a transparent mode and an immersive noise-calling mode – depending on your location and whether you’re wearing them for work or pleasure. Reviewers praise the solid build quality and the comfort of the soft ear cups. Ring Stick Up Cam Pro Home Security Camera This home security camera offers two-way talk plus package and movement alerts. Image: Amazon Have a home office and want to keep an eye on package deliveries, or you’re just looking for peace of mind? The Stick Up Cam Pro from Ring is a battery-powered outdoor security camera with 1080p HDR vision, color vision even at night, and a two-way talking function. Perhaps most importantly for us, it’s exactly 50% off now, with the price dropping from $179.99 to $89.99. DREAME X40 Ultra Robotic Vacuum The DREAME X40 robotic vacuum is housed in a relatively large charging station. Image: Amazon While not directly work-related, this robot vacuum can keep your home office tidy and save time on those pesky chores you would otherwise have to do after work. The X40 Ultra from DREAME cleans carpets, wood floors, tile, marble, and other hard surfaces. It includes a mop for solid surfaces, and you can set it to avoid mopping carpeted areas. For the Big Spring Sale, Amazon offers the DREAME X40 robotic vacuum for $899.99, 44% of its list price of $1,599.99. What’s hot at TechRepublic Lenovo Tab M9 Tablet The Tab M9 is a 9-inch tablet released in 2023. Image: Amazon Amazon took 47% off the $149.99 2023 Lenovo Tab 9 tablet for a sale price of $79.99. This tablet has a 9-inch HD screen, 13 hours of battery life, 32 GB of storage, and Google Lens’ translation and identification software. It unlocks using a face scan. The Lenovo Tab M9 is a reliable tablet for work or gaming. Motorola Moto G Power 5G This Motorola Moto G Power 5G shows the midnight blue color option. Image: Amazon This unlocked 2024 Motorola phone brings 128 GB of base storage, a 50 MP camera, a 120 Hz display, and 8 GB of RAM. Amazon is offering it on sale for $179.99, 40% off $299.99. The Moto G doesn’t offer as many perks or polish as a contemporary Apple or Samsung phone, but it has Android 14 just like the competitor and does most of the same things at a much more reasonable price. source