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Microsoft is adding two new AI reasoning agents to its Microsoft 365 Copilot suite: Researcher and Analyst. These AI agents are designed to streamline workflows by handling multi-step processes that typically require significant time and expertise. The tech giant introduced these reasoning agents, which Microsoft says are “first-of-their-kind,” as part of its continued push to make AI a core part of productivity tools. Smarter AI for research and data analysis Researcher Researcher is built to handle in-depth, multi-step research projects. It combines OpenAI’s deep research model with Microsoft 365 Copilot’s advanced orchestration and deep search capabilities. It pulls information from a mix of sources, including Microsoft 365 work data (emails, meetings, chats, and files) and external platforms like Salesforce, ServiceNow, and Confluence. Microsoft says Researcher can help users build go-to-market strategies, analyze industry trends, or create in-depth client reports by integrating internal and third-party data. Analyst Analyst focuses on data analysis and operates like a skilled data scientist; it processes raw data, identifies patterns, and generates insights. It’s powered by OpenAI’s o3-mini reasoning model and can perform advanced data analysis, including Python-based calculations and visualizations. Microsoft says users will be able to watch the AI generate Python code in real time, making it easier to understand and verify results. Analyst follows a “chain-of-thought” reasoning process, meaning it works through problems iteratively to refine its conclusions, mimicking human analytical thinking. Early access — but not for everyone These tools will debut in April as part of Microsoft’s “Frontier” program, an early-access initiative for Copilot users. Businesses with a Microsoft 365 Copilot license can try these AI tools, while also acting as testers for features still in development. In addition, Microsoft is rolling out updates to Copilot Studio, its tool for building custom AI agents. It’s offering new “deep reasoning” and automation capabilities that enable companies to create, manage, and deploy agents that handle multi-step tasks. The company says this will allow organizations to develop AI-driven workflows tailored to specific business needs, while also using flows to automate processes quickly and predictably. source

Chi Onwurah, chair of the Science, Innovation and Technology Select Committee. Image: UK Parliament/Flickr/Creative Commons Legislation that mandates safety testing of artificial intelligence technologies is at risk of being pushed aside by the U.K. government, the head of the tech select committee says. Labour’s Chi Onwurah warned that the delay may reflect political efforts to align more closely with the United States, particularly the Trump camp’s outspoken opposition to AI regulation. One key focus of the AI Safety Bill is to legally mandate that companies uphold their voluntary agreements to submit frontier AI models for government safety evaluations before deployment. Nine companies, including OpenAI, Google DeepMind, and Anthropic, made such agreements with a number of international governments in November 2023. SEE: UK Report Shows AI is Advancing at Breakneck Speed In November 2024, technology secretary Peter Kyle said he would implement the legislation in the next year. At the time, Chi Onwurah, the Labour chair of the Science, Innovation and Technology Select Committee which is in charge of examining tech policy, was under the impression it was “coming soon,” she told The Guardian, but now she’s worried about whether that is really the case. More must-read AI coverage Political influences and transatlantic ties “The committee has raised with Patrick Vallance [the science minister] the lack of an AI safety bill, and whether that is in response to the significant criticism of Europe’s approach to AI, which J.D. Vance and Elon Musk have made,” she added. In a speech at February’s Paris AI Action Summit, U.S. Vice President Vance disparaged Europe’s use of “excessive regulation” and said that the international approach should “foster the creation of AI technology rather than strangle it.” Europe has solidified a pro-regulation reputation through the AI Act and numerous ongoing regulatory battles with major tech companies — resulting in hefty fines. It is no secret that Trump is not happy about this, referring to the fines as “a form of taxation” at the World Economic Forum in January. SEE: Meta to Take EU Regulation Concerns Directly to Trump, Says Global Affairs Chief U.K. ministers do not plan to publish the AI Bill before the summer in an attempt to please the Trump administration, anonymous Labour sources told The Guardian last month. But this is not the only recent evidence that the country is trying to keep the States on side. Safety vs. innovation — The UK’s strategic shift Last month, the U.K.’s AI oversight body was renamed from the AI Safety Institute to the AI Security Institute, a rebranding seen by some as a shift away from a risk-averse stance and toward national interest farming. In January, Prime Minister Keir Starmer released the AI Opportunities Action Plan which put innovation front and centre and made little mention of AI safety. He also skipped the Paris AI Summit, where the U.K. declined to sign a global pledge for “inclusive and sustainable” AI, as did the U.S. The shift toward innovation-first policymaking comes with economic implicationsLimiting AI innovation in the U.K. could have a significant economic impact, with a Microsoft report finding that adding five years to the time it takes to roll out AI could cost over £150 billion. Stricter regulations could also deter major tech firms like Google and Meta from scaling in the U.K., prompting concern from investors. A spokesperson for the Department for Science, Innovation and Technology told The Guardian: “The government is clear in its ambition to bring forward AI legislation which allows us to safely realise the enormous benefits and opportunities of the technology for years to come.” “We are continuing to refine our proposals which will incentivise innovation and investment to cement our position as one of the world’s three leading AI powers, and will launch a public consultation in due course.” source

According to a peer-reviewed paper published on March 12 in the journal Science, D-Wave claims to have performed a materials simulation that surpasses the capabilities of even the most advanced classical supercomputers. Specifically, D-Wave said its annealing quantum computer solved a difficult materials simulation problem that would take millions of years on the Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory. D-Wave states in its related press release that the achievement is “the world’s first and only demonstration of quantum computational supremacy on a useful problem.” However, some researchers have challenged this assertion, insisting that traditional computing methods may already achieve comparable results. Moreover, some experts take issue with the usage of the term “quantum supremacy,” advocating instead for alternatives like “quantum advantage” or “quantum utility.” Simulation in approximately 20 minutes compared to a million years According to D-Wave’s paper, its annealing quantum computer Advantage2 prototype successfully simulated the properties of complex magnetic materials used in smartphones, medical devices, sensors, and motors. The company reported the simulation was completed in less than 20 minutes. Frontier, the most powerful supercomputer at Oak Ridge National Laboratory, would require close to a million years of nonstop computing to achieve the same results. Some physicists have argued that more optimized classical algorithms may significantly reduce this projected gap. SEE: Gartner named post-quantum cryptography among its top 10 strategic technology trends for 2025 D-Wave’s paper was based on research performed last year and did not take into account contemporary computing, research scientist Miles Stoudenmire told The Wall Street Journal. Researcher Dries Sels at New York University said the same calculations can be performed on conventional computers using a field of mathematics called tensor networks. An issue of quantum semantics The marketing term “quantum supremacy” remains contentious in the scientific community. Many researchers have recently embraced alternative terms such as “quantum utility” or “quantum advantage” to describe breakthroughs with the next-gen technology. D-Wave insists its usage of the term “quantum supremacy” is accurate. “We’re solving an important problem, and it’s in a regime that is totally intractable for leading classical methods. That’s why we call it quantum supremacy,” Andrew King, a senior distinguished scientist with D-Wave, told The Wall Street Journal. More about Innovation Quantum computing’s competitive landscape Numerous companies, including Amazon, are currently developing their own quantum computers and associated chips. In 2024, Google introduced Willow, a quantum chip for use in its Sycamore quantum computer. More recently, the tech giant unveiled its quantum-safe digital signatures for Google Cloud’s Key Management Service. Google first claimed to have quantum supremacy all the way back in 2019. Per Google’s announcement, Sycamore performed a task in 200 seconds that would have taken a supercomputer approximately 10,000 years to complete. Engineers have been working on quantum computing for decades. While much of the early work was strictly theoretical, we’re now starting to see the culmination of their efforts with systems like Advantage, Sycamore, and others. TechnologyAdvice staff writer Megan Crouse contributed to this article. source

Image: stockasso/Envato Elements A growing number of workers are pushing back against corporate AI strategies, with 31% of employees — and 41% of Gen Z — admitting to refusing to use AI tools or outputs, according to a new study. The desire to sabotage their company’s AI strategy stems from widespread fears of job displacement and dissatisfaction with their company-provided AI tools, according to a survey by Writer that polled 1,600 C-suite executives and employees. Frustrations are so high that 35% are footing the bill themselves for the generative AI tools they prefer to use at work. More must-read AI coverage Internal tensions undermine AI adoption The report also highlights power struggles, poor internal alignment, and friction between IT and business leaders over how GenAI should be deployed. About two out of three executives said GenAI adoption has created internal tension and divisiveness, with 42% warning that it is “tearing their company apart.” Despite optimism surrounding GenAI’s potential, 72% of C-suite respondents said their company has faced at least one major hurdle during adoption. Meanwhile, 71% reported that AI applications “are being created in a silos,” disconnected from broader strategy and collaboration. Further, an overwhelming 95% of the C-suite admitted their company needs to improve its approach to AI integration. SEE: Will Power Availability Derail the AI Revolution? (TechRepublic Premium) Leaders and employees see AI progress differently The survey revealed a sharp divide between how executives and employees perceive AI implementation. Only 45% of employees believe their company has been very successful with GenAI in the past year compared to 75% of the executives who believe the rollout has gone well. Still, momentum around GenAI continues to build. The report found 88% of employees and 97% of executives have personally benefitted from using GenAI, and both groups are across a range of use cases. “It’s not enthusiasm that’s stalling adoption,” observed May Habib, CEO and cofounder of Writer. “It’s the lack of a real strategy, the right tools to empower teams, and a partner that can actually make it work at scale.” Employees driving solutions from within Encouragingly, 77% of employees using AI are “AI champions” — individuals helping lead adoption efforts within their organizations. Nearly all (98%) of AI champions have either contributed to developing AI tools at work or expressed a desire to do so. “The future of AI in the enterprise depends on leaders taking a collaborative and inclusive approach,” Writer’s chief strategy officer Kevin Chung told TechRepublic. “By nurturing these champions and fostering a culture of innovation, organizations can navigate the challenges and fully harness the transformative power of generative AI.” source

Generative AI companies Anthropic and Databricks have teamed up to sell AI tools for business, trying to raise $100 million in five years, according to the Wall Street Journal. The partnership is an attempt to alleviate both companies being “under tremendous pressure” to perform relative to their valuations as the AI bubble threatens to burst. What will the Anthropic/Databricks partnership look like for business customers? Anthropic and Databricks sales teams will promote and sell one another’s products, according to The Wall Street Journal. The companies will target large corporate customers who want to build their own AI agents, which are: generative AI tools that can chain together different tasks to, seemingly autonomously, arrive at the result the user expressed in natural language. For example, an AI agent asked to “order a pizza delivered to the office” might require access to the user’s mobile meal delivery app and place the order. “Databricks has built up that trust with 10,000 customers,” Kate Jensen, Anthropic’s head of sales and partnerships, told The Wall Street Journal. “Anthropic is still relatively new, but continuing to grow extremely quickly.” According to Databricks and Anthropic, customers have requested better integration between the two companies’ tools. DOWNLOAD this IT Leader’s Guide to Generative AI from TechRepublic Premium Companies that use Databricks’ cloud data storage platform will be able to access Anthropic’s advanced generative AI, Claude, within it. The two companies already have a relationship in place, with mutual customers like Block (owner of payment platform Square), using both Databricks and Anthropic’s Claude behind the scenes on its own AI agent. Coding is among the tasks Square employees use Claude on Databricks for. More must-read AI coverage Blockers to generative AI adoption Generative AI companies have struggled to generate revenue despite the hot buzz around investing in or using the technology; Anthropic and Databricks are betting on agentic AI being no different. Agentic AI still has a reputation for being inaccurate or inefficient; the Databricks research team is aiming for 95% accuracy among their AI agents, The Wall Street Journal said. Agentic AI is the current buzzword in AI for business, with OpenAI adding speech to AI agents and Microsoft developing agents for specific cybersecurity tasks. Generative AI still has a trustworthiness problem, and prompt writing is an art unto itself that can take time away from core business functions. source

In February, Microsoft claimed it had created a new form of matter and used it to develop a quantum computer architecture that could potentially be put to work solving complex industrial problems within years. Since the announcement, some researchers and scientists have disputed these claims, saying Microsoft hasn’t actually achieved what it’s suggesting. The promise of topological qubits Microsoft stated its in-house experts had created “the world’s first topoconductor, a breakthrough type of material which can observe and control Majorana particles to produce more reliable and scalable qubits, which are the building blocks for quantum computers.” Majorana particles are fermions, a subatomic particle. What makes these particular topological qubits potentially promising is their supposed natural ability to reduce errors, which is one of the biggest challenges facing all current quantum computers. The topoconductor is one component of a new chip called Majorana 1, which Microsoft said could unlock industrial-scale uses for quantum computing within years. The company claimed the chip is an important roadmap to fitting one million qubits on a single chip. Moreover, Microsoft said the topoconductor can create an entirely new state of matter that enables Majorana particles to be arranged in a neat grid of H-shaped units. “It’s complex in that we had to show a new state of matter to get there, but after that, it’s fairly simple. It tiles out. You have this much simpler architecture that promises a much faster path to scale,” said Krysta Svore, Microsoft technical fellow. The research is part of DARPA’s Underexplored Systems for Utility-Scale Quantum Computing (US2QC) competition to create a quantum computer whose computational value outweighs its costs. Skepticism from the scientific community There are many reasons Microsoft’s announcement was a shock to the community, but the biggest one is because of the elusiveness of these Majorana particles. The particles were first proposed in 1937, but actually finding them has been challenging; yet, Microsoft declared it had not only detected these elusive particles but had managed to harness them in a working machine containing eight topological qubits. Objections to Microsoft’s methodology have arisen since then, including the editor of Nature pointing out that the paper Microsoft published does not prove there are Majorana particles in any specific devices. What’s more, experiments of the type Microsoft performed tend to create false signals that can look like the presence of Majoranas, according to interviews conducted by NewScientist. In addition, researchers argue that Microsoft simply hasn’t shared enough proof to back up its claims. Henry Legg, a lecturer in theoretical physics at the University of St Andrews in the U.K., recently published a pre-print critique that states Microsoft’s work “is not reliable and must be revisited.” Legg says the company’s work does not have a “consistent definition,” and that the findings “vary significantly, even for measurements of the same device.” Microsoft’s quantum VP, Zulfi Alam, fired back, calling Legg a “pontificator” who didn’t “bother to read the papers or even try to understand the data.” SEE: Amazon says its Ocelot chip reduces errors that can plague quantum computing.   “The announcement from Microsoft on their topological qubit – a qubit harnessing matter which can be reformed to perform the low-error operations crucial to quantum computing’s success – has been a core strategy for Microsoft for over a decade,” said Gerald Mullally, interim CEO of Oxford Quantum Circuits. “Their announcement indicates that qubits could be formed from a single ‘physical qubit’ using smart (but incredibly difficult) material and fabrication techniques just microns in size.” Mullally goes on to say, “While this is a significant moment for the maturity and fast march of the industry, further research on measured coherence and gate fidelity characterisation – key metrics to understand the platform’s viability – is required to really understand its impact. Research such as this from a major technology company underpins the importance and prospects of commercial quantum computing.” Time will tell whether Microsoft’s announcement represents a genuine quantum revolution. TechnologyAdvice staff writer Megan Crouse contributed to this article. source

It can be difficult to determine how generative AI arrives at its output. On March 27, Anthropic published a blog post introducing a tool for looking inside a large language model to follow its behavior, seeking to answer questions such as what language its model Claude “thinks” in, whether the model plans ahead or predicts one word at a time, and whether the AI’s own explanations of its reasoning actually reflect what’s happening under the hood. In many cases, the explanation does not match the actual processing. Claude generates its own explanations for its reasoning, so those explanations can feature hallucinations, too. A ‘microscope’ for ‘AI biology’ Anthropic published a paper on “mapping” Claude’s internal structures in May 2024, and its new paper on describing the “features” a model uses to link concepts together follows that work. Anthropic calls its research part of the development of a “microscope” into “AI biology.” In the first paper, Anthropic researchers identified “features” connected by “circuits,” which are paths from Claude’s input to output. The second paper focused on Claude 3.5 Haiku, examining 10 behaviors to diagram how the AI arrives at its result. Anthropic found: Claude definitely plans ahead, particularly on tasks such as writing rhyming poetry. Within the model, there is “a conceptual space that is shared between languages.” Claude can “make up fake reasoning” when presenting its thought process to the user. The researchers discovered how Claude translates concepts between languages by examining the overlap in how the AI processes questions in multiple languages. For example, the prompt “the opposite of small is” in different languages gets routed through the same features for “the concepts of smallness and oppositeness.” This latter point dovetails with Apollo Research’s studies into Claude Sonnet 3.7’s ability to detect an ethics test. When asked to explain its reasoning, Claude “will give a plausible-sounding argument designed to agree with the user rather than to follow logical steps,” Anthropic found. SEE: Microsoft’s AI cybersecurity offering will debut two personas, Researcher and Analyst, in early access in April. Generative AI isn’t magic; it’s sophisticated computing, and it follows rules; however, its black-box nature means it can be difficult to determine what those rules are and under what conditions they arise. For example, Claude showed a general hesitation to provide speculative answers but might process its end goal faster than it provides output: “In a response to an example jailbreak, we found that the model recognized it had been asked for dangerous information well before it was able to gracefully bring the conversation back around,” the researchers found. How does an AI trained on words solve math problems? I mostly use ChatGPT for math problems, and the model tends to come up with the right answer despite some hallucinations in the middle of the reasoning. So, I’ve wondered about one of Anthropic’s points: Does the model think of numbers as a sort of letter? Anthropic might have pinpointed exactly why models behave like this: Claude follows multiple computational paths at the same time to solve math problems. “One path computes a rough approximation of the answer and the other focuses on precisely determining the last digit of the sum,” Anthropic wrote. So, it makes sense if the output is right but the step-by-step explanation isn’t. More must-read AI coverage Claude’s first step is to “parse out the structure of the numbers,” finding patterns similarly to how it would find patterns in letters and words. Claude can’t externally explain this process, just as a human can’t tell which of their neurons are firing; instead, Claude will produce an explanation of the way a human would solve the problem. The Anthropic researchers speculated this is because the AI is trained on explanations of math written by humans. What’s next for Anthropic’s LLM research? Interpreting the “circuits” can be very difficult because of the density of the generative AI’s performance. It took a human a few hours to interpret circuits produced by prompts with “tens of words,” Anthropic said. They speculate it might take AI assistance to interpret how generative AI works. Anthropic said its LLM research is intended to be sure AI aligns with human ethics; as such, the company is looking into real-time monitoring, model character improvements, and model alignment. source

Apple Watch Series 10. Credit: Apple Apple’s future smartwatches may include cameras to enable AI features like translating signs between languages. Bloomberg’s Mark Gurman reported on the possibility on March 23, saying a camera would be added to the Apple Watch to enable features comparable to those debuted on the iPhone 16. Meanwhile, consumers filed a class-action lawsuit in mid-March alleging many Apple Intelligence features supposed to be enabled by AI in the digital assistant Siri were never delivered. Must-read Apple coverage Camera on Apple Watch would add AI-enabled ways to interact with the real world According to Bloomberg, Apple may add the camera and AI features to their line of smartwatches by 2027. The cameras would be inside the area of the display on the standard watch and next to the digital crown and button on the side of the Apple Watch Ultra. If the AI features on the watch are intended to be similar to the Apple Intelligence features enabled by visual intelligence on the iPhone 16, they could: Summarize and copy text from images captured by the camera, including translating between languages. Automatically open a prompt to add email addresses or phone numbers to contacts if you see them in the real world. Search Google for where to buy an item directly from a photo of that item. Ask ChatGPT to explain unfamiliar diagrams or notes. Gurman also predicted that Apple is exploring the idea of adding a camera to AirPods. SEE: AI literacy, conflict mitigation, and adaptability are skills on the rise in today’s workplace, according to LinkedIn. Apple’s AI division shaken up Apple has historically taken a cautious approach to AI adoption. We had predicted this measured approach would allow the company to introduce generative AI in a way that differentiates its ecosystem. However, the rollout has been gradual, largely consisting of incorporating widely established generative AI tools into its devices. An upgraded version of Siri — expected to understand natural language more intuitively — has reportedly been delayed until 2026. Behind the scenes, Apple removed John Giannandrea as head of the AI division and appointed Vision Pro executive Mike Rockwell to lead the team. 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

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