Today at Forrester’s largest annual customer event in Phoenix, my colleague Barry Vasudevan opened B2B Summit North America with his keynote address, “Introducing Buying Networks: Your Buyers’ New Reality,” which introduced the new concept of buying networks. This wasn’t an easy narrative to deliver, because there are a significant number of challenging and hard-to-stomach realities in B2B today that compel us all to acknowledge that much about how we’ve sold in the past won’t work in the future. This in turn means that revenue enablement teams need to start pivoting — now — or risk irrelevance. Let’s first review some of Barry’s tough-love findings. The Bad News About Buyers Barry told us that “a seemingly never-ending list of people, processes, and technologies involved in making a purchase decision has radically transformed the landscape of business buying.” The hard facts about B2B buyers boil down to the following: Buyers hate buying 81% of buyers are dissatisfied … with the winning provider. Buyers are growing far more complex The average B2B sale now involves 13 internal and 9 external individuals. Buyers are taking longer to buy 86% of purchases experience a significant stall. Buyers are relying on the direct provider less than ever 28% of purchases already include 10+ external influencers. Buyers are using genAI to change everything 89% of buyers are using generative AI agents to support their purchase.   Not very uplifting, is it? But wait, there’s more …  The More Troubling News About Providers Marketing and sales teams within B2B companies remain extraordinarily inward-focused, relying on historically successful or traditional mechanics that fail to address modern realities: Providers focus on revenue growth at the expense of customer goals Only 3% of B2B companies are legitimately customer-obsessed. Providers are losing ground to buyer self-service The self-service technology market size is projected to double by 2032. Providers misalign incentives and behaviors The average conversion ratio from target stage to qualified stage is less than 5%. Providers are not trusted Buyers rank salespeople ninth out of 12 trust options — only ahead of news media, government officials, and social media influencers. Providers rely on archaic processes and metrics B2B CMO dashboards focus on an average of nine organizational value metrics and only two customer value metrics.   All is not lost, however. Barry provided several examples of revenue process transformation success stories, because after all, “big problems require bold solutions.” It starts with graduating the provider organization’s mindset “from checkers to chess.” We must all better respond to the buyer’s needs, their expanding networks, and use of technology with better abilities to collect and interpret signals, maneuver through the buying ecosystem, and acknowledge that outside-in revenue generation approaches override our internal org charts, fiefdoms, and vanity metrics. How Revenue Enablement Can React Today My favorite quote stemming from Barry’s current work is this: “To maximize the lifetime value of the customer, organizations need to maximize lifetime value for the customer,” says Mike Randall, head of global demand generation at Jones Lang LaSalle. Your revenue enablement team can immediately start shifting to a more customer-obsessed mindset by: Cleansing all traditional enablement materials — onboarding curricula, product launch training, methodology reminders — of “What’s in it for me?”-like, “It’s all about us and our products” content. Replace all the self-congratulatory and product-centric enablement references with buyers, personas, markets, business savvy, and whatever else it takes to fulfill Randall’s vision. Reviewing the plans for all upcoming spiffs, SKOs, QBRs, blitz days, and contests to identify recurring mistakes. Are you rewarding seller activity instead of genuine buyer interest? Are you working harder to acquire new logos instead of working smarter to secure renewals? Refining all enablement materials about buyer personas and trends to reflect the realities of their generative AI usage. Sellers can’t and shouldn’t compete with machines but need to be experts on how their buyers are leveraging AI to bypass human interactions … for when they do get in front of their prospect. What Revenue Enablement Must Prepare For Tomorrow Forrester also quotes Ali Rastiello, VP of revenue operations at Health Catalyst: “When my company evaluated offerings from two leading vendors, we chose the provider that demonstrated time after time that they knew who we were and what we wanted to achieve.” This informs my sole, focused recommendation for enablement leaders hoping to support the rise of buying networks: Double down on evolving your seller competencies to adapt to changing buyer needs. Pushing an RDR to make 100 dials per day should give way to hiring, onboarding, and everboarding reps with higher emotional inteligence, a stronger ability to identify and navigate buyer networks, and, above all, an understanding of how to earn customer trust. source

This Motorola Moto G Power 5G shows the midnight blue color option. Image: Amazon New Android malware is using Microsoft’s .NET MAUI to fly under the radar in a new cybersecurity dust-up this week. Disguised as actual services such as banking and social media apps targeting Indian and Chinese-speaking users, the malware is designed to gain access to sensitive information. Cybersecurity experts with McAfee’s Mobile Research Team say that, while the threat is currently aimed at China and India, other cybercriminal groups could easily adopt the same method to target a broader audience. .NET MAUI’s hidden danger: Bypassing security Microsoft launched .NET MAUI in 2022, a framework that lets developers build apps for both desktops and phones using C#, replacing the now retired Xamarin tool. The intent of .NET MAUI was to make it easier to create apps that work across different platforms. Typically, Android apps are built with Java or Kotlin, and their code is stored in a format called DEX (Dalvik Executable); Android security systems are designed to scan these DEX files for anything weird-looking. However, .NET MAUI allows developers to build Android apps with C#, and in this case, the app’s code ends up in binary “blob” files. Malware’s evolving tactics: The blob advantage These Binary Large Object or “blob” files are essentially raw chunks of data that do not necessarily follow any standard file structure. The issue here is that many current Android security tools — built to analyze DEX files — do not inspect the inner contents of these blob files; this creates a significant security blind spot, as malware can be quietly embedded inside these blobs. For cybercriminals, embedding malicious code from the outset is far more effective than waiting to deploy it through an update. The ‘blob’ format enables this kind of stealthy, immediate attack. “With these evasion techniques, the threats can remain hidden for long periods, making analysis and detection significantly more challenging,” warns McAfee in its blog post on the subject. “Furthermore, the discovery of multiple variants using the same core techniques suggests that this type of malware is becoming increasingly common.” SEE: Scam Alert: FBI ‘Increasingly Seeing’ Malware Distributed In Document Converters Mobility must-reads Protecting your device: Security researchers’ advice It’s always important to be careful where you get your apps from, especially if you’re not using the official app stores. McAfee researchers have found that “…these platforms are often exploited by attackers to distribute malware. This is especially concerning in countries like China, where access to official app stores is restricted, making users more vulnerable to such threats.” To deal with how quickly cybercriminals come up with new tricks, McAfee strongly suggests that users “install security software on their devices and keep it up to date at all times.” Basically, staying alert and having good security in place are the baseline measures to stay safe from new threats. source

The Netherlands has ranked 10th in a global index of tech competitiveness, ahead of the entire G7 group of the world’s largest so-called “advanced” economies. The country was praised for its thriving digital economy, mature biotech and semiconductor industries, and strong digital skills underpinned by “engineering excellence.” London-based Centre for Economics and Business Research (CEBR) and consultancy SThree produced the index, which ranks 35 countries based on economic indicators such as level of high-tech exports, number of software developers, and patent filings related to AI.  Several European countries joined the Netherlands near the top of the rankings. Ireland placed second globally and first in Europe, while Finland (fourth), Norway (sixth), Denmark (seventh), Estonia (eighth), and Sweden (ninth) also featured in the top 10. Singapore claimed the number one position overall, earning praise for its “world-class” digital infrastructure, advanced STEM education, and innovation-driven economy. All the metrics are adjusted for population size.   The UK and US lagged behind at 13th and 15th, respectively, underscoring the shifting dynamics of global tech competitiveness. Notably, G7 economies failed to secure a single position in the top 10. The study excluded India, China, and every African nation due to insufficient data.   The 20 leading nations for tech competitiveness. Credit: SThree/CEBR Robert Doornbos (FR driver), Pernilla Sjöholm (Tinder Swindler survivor) & more Check out every speaker at TNW Conference including Hugging Face, ASML, OpenAI & Datasnipper CEBR and SThree published the rankings as part of a wider study of STEM competitiveness, which evaluates nations on their ability to foster scientific and technological innovation, high-quality education, and employment in STEM-related fields. Switzerland led this index, followed by Sweden, while the Netherlands secured eighth place. The full rankings for STEM competitiveness. Credit: SThree/CEBR Positive signs for tech in the Netherlands The report highlighted the Netherlands’ strength in life sciences, where it ranked seventh, supported by a thriving ecosystem of biotech startups and a strong network of research institutions. Engineering emerged as the country’s weakest STEM sector, ranking 21st globally. The findings suggest there are grounds for optimism about the Dutch tech sector, despite recent heavy criticism. A recent report discovered a “worrying” decline in startups from the country, while founders have warned that burdensome regulation and insufficient government support are stunting the sector’s progress. The report also illustrates the outsized role played by Europe’s smaller countries in nurturing science and technology.  Timo Lehne, the chief executive of SThree, said the rankings also stand as a clear warning sign for the G7 nations — Canada, France, Germany, Italy, Japan, the UK, and the US. “Once the global epicentre for innovation, these countries are now facing stiff competition from emerging tech hubs,” he said. “Without a renewed focus on cultivating groundbreaking companies and embracing future-facing industries, their leadership in the tech race is no longer guaranteed.” The future of Dutch tech will be a hot topic at TNW Conference, which takes place on June 19-20 in Amsterdam. Check out out our initial list of speakers and our early agenda for a taste of what’s to come. Tickets for the event are now on sale. Use the code TNWXMEDIA2025 at the check-out to get 30% off the price tag. source

A single unmonitored exposed IT asset is all it takes to compromise an entire organization. Hence IT asset monitoring is one of the key strategies that keeps proactive cybersecurity efforts up and running across businesses. However, with the growing reliance on cloud platforms, third-party vendors, and remote operations, the number of IT assets to be monitored, both internal and external has widened. And the wider it gets, the greater the attack surface that could be exploited. Across France, enterprises are grappling with an expanding attack surface as digital transformation accelerates. Recent data from Statista shows that 74% of organizations in France encountered ransomware attacks in 2024. The story was similar to the year before when it was about 64%. But what vulnerabilities are attracting cybercriminals to French businesses? The answer and more could be found in Outpost24’s 2024 French EASM benchmark. Understanding the Risks in France’s Digital Landscape Most CISOs would agree that a complete inventory of their external attack surface is paramount, as internet-exposed assets face relentless automated attacks. Without this knowledge, effective defense becomes a fairy tale. To understand the extent to which public-facing assets of France-based businesses are exposed to cyber-attacks, Outpost24, last year, analyzed over 19,000 assets across various sectors using its External Attack Surface Management (EASM) solution. The results of that study show that while France’s push into digital transformation is creating new technological frontiers, it’s also birthing new vulnerabilities. Let’s take the pharmaceutical sector for example. Findings reveal that it was the most vulnerable with 25.4% of vulnerabilities rated critical, very high, or high. The transport sector had the highest proportion of critical or very high Known Exploitable Vulnerabilities (KEVs) at 49.5%, compared to Finance’s 22%. The analyses also highlighted 252 cookie violations and credentials stolen by malware in the healthcare sector. This is not a surprise as public healthcare systems are often tied to aging legacy infrastructure which bears their fair share of exploitable vulnerabilities. Outpost24 further undertook to analyze the online infrastructure of the Paris 2024 Olympic games to understand what the attack surface risks looked like. The study found two exposed remote access ports, 31 domains (5.8%) with invalid SSL certificates, 86 domains (16%) lacking SSL, and 257 out of 294 websites with security header issues. While the overall cybersecurity posture of the Olympics was deemed good, the deep attack surface analysis was crucial as it made it easier to uncover hidden risks and offered actionable insights. What’s hot at TechRepublic The Cost of Neglecting IT Asset Management The pace at which we are experiencing digital expansion does not give room for neglecting IT asset security. Any nonchalance towards having digital resources often leads to devastating consequences for organizations. IBM’s 2024 Cost of a Data Breach Report pegs the global average cost of a breach at $4.88 million, up 10% from 2023. It also found that breaches involving unmonitored or poorly managed assets (e.g., shadow data or devices) accounted for 35% of incidents and were 16% more expensive than average. But beyond monetary losses, companies that fail to manage their IT assets effectively are bound to face complex compliance issues. As reported by Proximity, nearly half of all asset managers surveyed in 2023 saw compliance as a leading concern, a burden compounded by the ever-evolving regulatory landscape. To this end, organizations must prioritize this crucial aspect of cybersecurity to protect their digital assets and maintain their competitive edge. Must-read security coverage How EASM Strengthens Digital Resilience Managing an ever-expanding attack surface can feel overwhelming, but solutions like External Attack Surface Management (EASM)-Tools simplify the process. Outpost24’s EASM solution uses passive detection, elaborate discovery methods and AI to continuously scan, track, and asses external IT assets and thus help organizations stay ahead of cyber threats. With the recent addition of a Dark Web module feature, Outpost24 is taking attack surface management and security even further. The module monitors underground forums, chats and datadumps for mentions of company data, and by doing so, detects potential sales or attack plans before they escalate. For French businesses, this level of monitoring is critical. In critical industries, EASM could help eliminate shadow IT, detect compromised credentials and their source, highlight non-criminal-cyber risks and flag neglected servers that could be exploited. In addition to all of these, Outpost24’s risk-ranking system allows security teams to focus on the most pressing threats thereby cutting through the noise. More cloud security coverage Conclusion Cutting down external attack surfaces starts with knowing what IT assets to protect, where they are, and the level of risk they pose. French businesses can significantly lower their vulnerabilities if they incorporate quality external attack surface management solutions. If you’re curious about how your organization’s attack surface score measures up, book a free attack surface analysis today with Outpost24 to spot your cybersecurity weak spots. source

By Christopher Cole ( March 28, 2025, 8:12 PM EDT) — Congress will be prepared to reform the country’s telecom subsidy programs for low-income and rural consumers if the U.S. Supreme Court decides they must be overhauled, according to a key House Republican…. 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

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The release of Gemini 2.5 Pro on Tuesday didn’t exactly dominate the news cycle. It landed the same week OpenAI’s image-generation update lit up social media with Studio Ghibli-inspired avatars and jaw-dropping instant renders. However, while the buzz went to OpenAI, Google may have quietly dropped the most enterprise-ready reasoning model to date. Gemini 2.5 Pro marks a significant leap forward for Google in the foundational model race—not just in benchmarks but also in usability. Based on early experiments, benchmark data and hands-on developer reactions, it’s a model worth serious attention from enterprise technical decision-makers, particularly those who’ve historically defaulted to OpenAI or Claude for production-grade reasoning. Here are four major takeaways for enterprise teams evaluating Gemini 2.5 Pro. 1. Transparent, structured reasoning – a new bar for chain-of-thought clarity What sets Gemini 2.5 Pro apart isn’t just its intelligence – it’s how clearly that intelligence shows its work. Google’s step-by-step training approach results in a structured chain of thought (CoT) that doesn’t feel like rambling or guesswork, like what we’ve seen from models like DeepSeek. These CoTs aren’t truncated into shallow summaries like OpenAI’s models. The new Gemini model presents ideas in numbered steps, with sub-bullets and internal logic that’s remarkably coherent and transparent. In practical terms, this is a breakthrough for trust and steerability. Enterprise users evaluating output for critical tasks – like reviewing policy implications, coding logic, or summarizing complex research – can now see how the model arrived at an answer. That means they can validate, correct, or redirect it more confidently. It’s a major evolution from the “black box” feel that still plagues many large language models (LLMs) outputs. For a deeper walkthrough of how this works in action, check out the video breakdown where we test Gemini 2.5 Pro live. One example we discuss: When asked about the limitations of large language models, Gemini 2.5 Pro showed remarkable awareness. It recited common weaknesses, and categorized them into areas like “physical intuition,” “novel concept synthesis,” “long-range planning” and “ethical nuances,” providing a framework that helps users understand what the model knows and how it’s approaching the problem. Enterprise technical teams can leverage this capability to: Debug complex reasoning chains in critical applications Better understand model limitations in specific domains Provide more transparent AI-assisted decision-making to stakeholders Improve their own critical thinking by studying the model’s approach One limitation worth noting is that while this structured reasoning is available in the Gemini app and Google AI Studio, it’s not yet accessible via the API—a shortcoming for developers looking to integrate this capability into enterprise applications. 2. A real contender for state-of-the-art – not just on paper The model is currently sitting at the top of the Chatbot Arena leaderboard by a notable margin – 35 Elo points ahead of the next-best model, which notably is the OpenAI 4o update that dropped the day after Gemini 2.5 Pro dropped. And while benchmark supremacy is often a fleeting crown (as new models drop weekly), Gemini 2.5 Pro feels genuinely different. Top of the LM Arena Leaderboard, as of publishing. It excels in tasks that reward deep reasoning: coding, nuanced problem-solving, synthesis across documents and even abstract planning. In internal testing, it’s performed especially well on previously hard-to-crack benchmarks like the “Humanity’s Last Exam,” a favorite for exposing LLM weaknesses in abstract and nuanced domains. (You can see Google’s announcement here, along with all of the benchmark information.) Enterprise teams might not care which model wins which academic leaderboard. But they’ll care that this one can think – and show you how it’s thinking. The vibe test matters, and for once, it’s Google’s turn to feel like they’ve passed it. As respected AI engineer Nathan Lambert noted, “Google has the best models again, as they should have started this whole AI bloom. The strategic error has been righted.” Enterprise users should view this not just as Google catching up to competitors, but potentially leapfrogging them in capabilities that matter for business applications. 3. Finally, Google’s coding game is strong Historically, Google has lagged behind OpenAI and Anthropic in developer-focused coding assistance. Gemini 2.5 Pro changes that—in a big way. In hands-on tests, it’s shown strong one-shot capability on coding challenges, including building a working Tetris game that ran on the first try when exported to Replit—no debugging needed. Even more notable, it reasoned through the code structure with clarity, labeling variables and steps thoughtfully and laying out its approach before writing a single line of code. The model rivals Anthropic’s Claude 3.7 Sonnet, which has been considered the leader in code generation, and a major reason for Anthropic’s success in the enterprise. But Gemini 2.5 offers a critical advantage: a massive 1-million token context window. Claude 3.7 Sonnet is only now getting around to offering 500,000 tokens. This massive context window opens new possibilities for reasoning across entire codebases, reading documentation inlines and working across multiple interdependent files. Software engineer Simon Willison’s experience illustrates this advantage. When using Gemini 2.5 Pro to implement a new feature across his codebase, the model identified necessary changes across 18 different files and completed the entire project in approximately 45 minutes, averaging less than three minutes per modified file. This is a serious tool for enterprises experimenting with agent frameworks or AI-assisted development environments. 4. Multimodal integration with agent-like behavior While some models like OpenAI’s latest 4o may show more dazzle with flashy image generation, Gemini 2.5 Pro feels like it is quietly redefining what grounded, multimodal reasoning looks like. In one example, Ben Dickson’s hands-on testing for VentureBeat demonstrated the model’s ability to extract key information from a technical article about search algorithms and create a corresponding SVG flowchart – then later improve that flowchart when shown a rendered version with visual errors. This level of multimodal reasoning enables new workflows that weren’t previously possible with text-only models. In another example, developer

Data governance tools help organizations manage governance programs. Specifically, they help with data administration, monitoring, control, reporting, lifecycle management, control, security, and compliance. By leveraging the power of data governance software, organizations can ensure that their data is reliable, consistent, and secure, thus using it for better decision-making. In this article, we’ll discuss the top data governance tools of 2024 and help you determine which one is the best fit for your business. Top data governance software comparison The comparison table below highlights important features, such as the ability to catalog data, track data from origin to destination, improve quality, policy management, and more, allowing you to evaluate and compare your options quickly. Ataccama ONE: Best unified AI-powered data governance platform across hybrid and cloud environments Image: Ataccama Ataccama ONE distinguishes itself as a robust, unified AI-powered data governance tool, ideal for managing governance across both hybrid and cloud environments. This platform excels in automatically calculating data quality and classifying data within a catalog, making it easy for data stewards to prioritize their governance efforts systematically. Why I choose Ataccama ONE I chose Ataccama ONE as the best unified AI-powered data governance platform because it stands out for its comprehensive approach to managing data governance across various environments. Its automation capabilities significantly reduce the manual effort required in data management, ensuring higher accuracy and efficiency. Pricing 14-day free trial. Pricing starts at $90,000 for 12 months. Key features Data discovery and classification: Automatically calculates and classifies data. Automated data profiling: Provides in-depth analysis of data sets to detect duplicates, anomalies, and patterns. Automated data quality: Monitors and cleanses data across systems, detects anomalies, and conducts structure checks. Centralized reference data management: Establishes a governed process for authoring and distributing reference data organization-wide. AI-augmented master data management: Offers a multi-domain MDM solution with AI-powered matching rules and model configurations for faster deployment. Ataccama ONE takes a comprehensive approach to managing data governance. Image: Ataccama ONE Ataccama One pros and cons Pros Cons Hybrid and cloud-ready. Slow support response. Advanced automation features. Complex for newcomers. Award-winning platform. Cumbersome setup. Flexible industry support. Collibra Data Governance: Best for its system of engagement for data and AI Governance Image: Collibra Collibra Data Governance excels as a data governance tool for engaging with data and AI governance, providing a unified location to discover, understand, and define data. The software allows businesses to operationalize data governance workflows and processes, ensuring trusted data delivery across various domains. Why I choose Collibra Data Governance I recognize Collibra Data Governance as the best platform for systems of engagement in data and AI governance due to its comprehensive and adaptive approach. It supports organizations in establishing a robust governance framework that scales effectively with their growth. Pricing 12-month subscription to Collibra Data Intelligence Cloud: $170,000. 24-month subscription to Collibra Data Intelligence Cloud: $340,000. 36-month subscription to Collibra Data Intelligence Cloud: $510,000. Key features Adaptive data governance: Scales with your organization to streamline governance processes. Comprehensive business glossary: Establishes a common terminology to ensure uniform understanding across the company. Stewardship management: Facilitates data stewardship by assigning clear roles and responsibilities for data protection and improvement. Centralized policy management: Aids in creating, reviewing, and updating data policies to maintain compliance and adoption. AI governance: Enhances AI model effectiveness and reduces data risks through robust cataloging and validation processes. Collibra establishes a robust governance framework that scales effectively. Image: Collibra Collibra pros and cons Pros Cons Scalable AI governance. Weak search functionality. Detailed business glossary. Slow product updates. Enhanced compliance management. Outdated user interface. Google Vertex AI integration. Challenging for non-tech users. Broad partner ecosystem. Google Cloud award winner. IBM Cloud PAK for Data: Best for providing a unified, trusted view of business data Image: IBM IBM Cloud Pak for Data stands out for organizations looking to achieve a unified and trusted view of their business data. This data governance platform was recognized as a leader in the 2024 Gartner Magic Quadrant for Augmented Data Quality Solutions, highlighting its excellence in data management and governance. IBM recently acquired Manta Software Inc., a data lineage platform, enhancing its data lineage and AI governance capabilities Why I choose IBM Cloud Pak for Data I chose IBM Cloud Pak for Data as the best platform for providing a unified and trusted view of business data due to its comprehensive integration of data management tools and cutting-edge AI capabilities. Its strengths in enhancing data quality, ensuring privacy and compliance, and simplifying complex data landscapes make it an invaluable resource for enterprises seeking to optimize their data governance practices. For more information, read the in-depth IBM Data Governance tools review. Pricing Pricing for the IBM data governance solution isn’t listed on IBM’s website. Publicly available data on AWS Marketplace shows the pricing of IBM Cloud Pak for Data, which is the parent product for the data governance solution: Cloud Pak for Data Standard Option: 48 VPCs cost $18,720 per month and $224,640 for 12 months. Cloud Pak for Data Enterprise Option: 72 VPCs cost $56,016 per month and $672,192 for 12 months. Key features Data quality management: Analyze and enhance data quality using AI-driven rules and visual analytics. Data privacy and compliance: Dynamically identify sensitive data and enforce protection rules to mitigate regulatory risks. Data catalog: Simplify data management with extensive metadata management capabilities and lifecycle management of data products. Policy and rules management: Streamline policy management with integrated workflows. Advanced data discovery: Leverage IBM Watson to intelligently recommend relevant data assets. IBM enhances data quality, ensures privacy and compliance, and simplifies complex data landscapes, making it an invaluable enterprise resource. Image: IBM IBM pros and cons Pros Cons Unified governance platform. Inadequate documentation. Focus on data quality. Lacking deployment details. Advanced AI capabilities. Needs better usability. Comprehensive governance tools. Slow customer support. Gartner-recognized leadership. erwin by Quest: Best for an automated, holistic approach to data management and governance Image: erwin erwin by Quest provides comprehensive solutions for enterprise modeling, data intelligence, and data governance. It equips

As the world becomes increasingly globalized, businesses need to adapt – which is why language translation has never been more important. Whether translating content to reach global audiences, adapting product manuals for user safety and compliance, or facilitating seamless communication through real-time speech translation in customer support or business meetings, the ability to translate with accuracy, context, and speed is vital. But the question becomes, which translation tools do you need? While free translation tools may suffice for consumers, when it comes to business, “good enough” isn’t enough and only precise, nuanced, context-rich and secure solutions will do. Those results are achievable with DeepL’s Language AI platform, says Sebastian Enderlein, CTO at DeepL. “There has been commoditization of regular day-to-day translations. But we offer high quality, secure language and communication tools that over 200,000 businesses around the world trust to remove language barriers, whether internally between colleagues, or externally with clients,” says Enderlein. “Our platform, which offers written and spoken translation tools, as well as advanced writing functionality, going beyond word-to-word translation to offer contextualization and personalization with specialized AI.” The CTO offers this example: A Korean car manufacturer and a Japanese parts supplier need precise communication about components in an upcoming shipment. Accurate translation requires contextualizing automotive industry terminology, as even small errors could result in incompatible parts and disrupt production. This is where DeepL’s Language AI excels, capable of translating highly complex, custom terminology directly between two languages, ensuring full industry context. To achieve that level of precision, DeepL’s platform is powered by specialized LLMs trained on high-quality linguistic data and the expertise of thousands of language experts. “Human model tutoring is critical to the quality and accuracy we’re known for,” says Enderlein. The quality DeepL achieves drives significant efficiencies, saving customers time and money and enabling businesses to scale faster, producing fast, fully accurate translations that require less re-work. “Blind tests have shown that translations powered by our next-gen LLM require two to three times fewer edits than our competitors,” he says. The DeepL API As part of its platform, DeepL offers an API solution that enables customers to integrate DeepL’s Language AI technology into their own systems. Earlier this year, DeepL expanded its API capabilities to include more advanced translation capabilities powered by its next-generation language models, as well as the DeepL API for Write, which provides access to its advanced writing tools, providing AI-powered suggestions on word choice, phrasing, style, tone and more. Common use cases for the DeepL API include website translation and multilingual company communications via integrations with collaboration tools, CRMs and helpdesk platforms. Additionally, many leading CAT tool providers have integrated DeepL’s technology, allowing translators to leverage DeepL’s high-quality neural translations directly within their preferred software. Businesses are catching on. DeepL’s fast-growing customer network includes industry leaders like Softbank, Mazda, Harvard Business Publishing, The Ifo Institute, and Panasonic Connect. As companies expand and deepen their global initiatives, language and translation are critical to ensuring effective communication across international markets. Learn more about DeepL, including its powerful API solution, here. source

Gone are the days when a bean bag and free kombucha made your office cool. Today’s top tech talent wants something far more valuable: their health. That’s the view of Lucien Engelen, a renowned healthcare innovation expert, who believes workplace wellbeing is about to spark a seismic shift. This transition will not only transform employment perks, but also create a new tech market. Engelen’s vision draws on deep experience. Across three decades in healthcare, his work has spanned acute care, ambulance services, and dispatch centres. As the founding director of the REshape Center of the Radboud University Medical Center, he spent eight years developing and implementing healthcare technologies, grabbing headlines for efforts to integrate patients in their own care and improve service provision with social media. Today, he focuses on running Transform.Health, which assists organisations such as Vodafone, Erasmus University Medical Center, Deloitte, and Sanofi in their healthcare strategies. He also delivers 100 keynotes a year across the globe about the subject. These roles revealed a fundamental flaw in conventional treatment. “We’ve built a sick care system, not a healthcare system,” he says. Hugging Face, ASML, OpenAI, Monzo & Datasnipper Check out the NEW speakers for TNW Conference 2025 on June 19 & 20. Engelen compares the problem to bad plumbing. “We wait until water gushes out of the wall before fixing the leak, instead of turning off the tap.” For Engelen, the fix is obvious. We need to shift the focus from treating illnesses to preventing them. And employers have a crucial role to play. At TNW Conference on June 19, Engelen will share his vision in full during a talk titled “CODE RED: Why the Future of Work is the Future of Health.” Ahead of the event, he shared a glimpse of what to expect. Employers as catalysts for wellbeing The business case for staff wellbeing is obvious: healthier employees deliver higher performance. Illness, stress, and long waits for medical care drain their productivity and availability. “If it takes eight weeks to get a consultation, that’s eight weeks of lower productivity,” Engelen notes. “And if they leave due to poor health, replacing them can cost about €40,000 in rehiring and training someone to reach the same level.” To stay ahead, forward-thinking employers are getting proactive. Instead of waiting for health problems to arise, they’re offering services that can prevent them.  Technology is rapidly expanding the possibilities. From digital wellbeing apps and fitness trackers to online therapy, these perks are becoming a competitive advantage in attracting elite workers.  As Engelen says, “We’re all fishing in the same bucket of talent.” To attract that talent, he urges employers to apply a broader concept of wellbeing. “It’s not only about your physical health. There’s also your mental health, and even your social health and financial health.” Gradually, this holistic model is shaping modern workplaces. The next generation For employers, mental health services have become a growing focus — and with good reason. Deloitte research found that UK organisations investing in mental health support see an average return of five to one. The benefits could be especially impactful for younger workers. A recent study by PwC found that almost four in 10 Gen Z employees in the UK have seriously considered leaving their jobs in the last year, with mental health “a major driver.”  Digital services offer promising solutions. Yet they also introduce new challenges. “The same Gen Z that is willing to step down due to mental health concerns also thinks privacy is very important — for the right reasons,” Engelen says. “The challenge now for companies is offering solutions without sacrificing their privacy.” Engelen sees employers addressing this by offering third-party services that staff can use confidentially, away from the prying eyes of bosses or colleagues. For instance, they’re providing anonymised access to online mental health services and fitness apps connected to gyms outside the company — with no data flowing back to the business. This growing focus on employee wellbeing also has powerful potential for tech firms. Engelen envisions a new market emerging for them. “We’ll see an increase in Big Tech closing big contracts with big corporates,” he says.  “We will also see Big Tech acquiring more startups in this sector than ever before, because they can not only get this technology scaled, but also access a market that is willing to pay for it. Now that employers see the real financial benefit of this, it is going to create a new revenue stream.” For tech companies, this is a lucrative opportunity. The same is true for employers.  The future of wellbeing in the workplace The benefits of healthy workplaces are well-established. Researchers have found that the ROI on employee wellness programs can be six to one.  “Employers are realising that investing in prevention is far cheaper than paying for treatment or replacing talent — and can also attract talent,” Engelen explains. Accessibility to digital wellbeing is also set to increase. Integration layers are connecting more and more healthcare apps, creating new approaches to medical care. The EU, meanwhile, recently ratified the European Health Data Space regulation, which will enforce mandatory access to medical records on users’ smartphones. As the technology progresses and enters the workplace, the ripple effects could improve lives and productivity, while alleviating pressure on overburdened health systems. By embracing wellbeing tech, Engelen believes employers can accelerate a shift from reactive healthcare to proactive prevention. “The technology is already there,” he says. “What’s changing is how we’re using it. Employers have realised that investing in health and wellbeing is not just good for their people — it’s good for business.”  Lucien Engelen will be among the standout speakers at TNW Conference, which takes place on June 19-20 in Amsterdam. Tickets for the event are now on sale. Use the code TNWXMEDIA2025 at the check-out to get 30% off the price tag. source