For those that attended VMware Explore in Las Vegas and Barcelona, there was a new self-paced hands-on lab released exclusively for the attendees to experience Google Cloud VMware Engine while at the events. I am happy to announce that this lab has now been made publicly available through the VMware Lab Platform website for anyone to enroll and try. I thought it may be worth taking a moment to briefly discuss the new modules and content as well as provide you a direct link to access it easily. Hands-on lab summary Since last year, there have been many interface changes and product enhancements that have changed the look and feel of Google Cloud VMware Engine. These refreshed modules capture the latest changes and features, and even let you experience some of the adjacent services. The lab modules start with deploying your first private cloud, as well as configuring the initial VMware Engine networking. The follow-on modules walk you through everything from using Terraform, to migrating workloads with HCX, to external storage options, configuring backup, and using other Google Cloud services. Figure 1: The Google Cloud VMware Engine hands-on lab landing page Takeaway All-in-all, there is a lot here to give you a taste of what using Google Cloud VMware Engine has to offer. Best of all, the lab modules are formatted into reasonable time chunks, usually 30 minutes or less, so that they can be done at your convenience. About the author:Darin Schmitz is a Senior Technical Marketing Architect in the VMware Cloud Foundation division at Broadcom focused on Google Cloud VMware Engine. Prior to Broadcom, he worked across multiple disciplines in the information technology industry, most notably within enterprise storage, cloud computing, and even as a systems administrator for some of the nation’s largest private sector and government organizations. source

By Ali Sullivan ( April 10, 2025, 8:55 PM EDT) — Google will temporarily offer its Workspace suite to agencies across the federal government at a 71% discount, the tech giant and the U.S. General Services Administration announced Thursday…. 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

specifically about analytics, right, which was what we’re here to talk about today, as we’ve discussed quite a lot already, the underlying data quality infrastructure issue that’s real. That’s top of mind. I think that exists everywhere. Really interesting hearing Qiraat talk there about, in essence, ROI Right? Return on Investment. I think that’s a real challenge for a lot of organizations around these projects. I love the way keyra framed it. As you know, don’t worry about the FOMO kind of thing, like, like, drill down to the value. At the same time, organizations are worried about being left behind and from an innovation perspective. But I do think that issue of ROI is increasingly becoming a space where some organizations can see AI helping right data preparation, in and of itself, can consume a huge amount of time and resources due to those difficulties in finding, accessing, cleaning, transforming, sharing data efficiently. I think the increasing number and complexity of data sources coupled with the need to access them across distributed ecosystems, again, both the guys spoke about that that demands significant resources and expertise, and I’m starting to hear it buyers think maybe AI can help with some of that complexity, like applying AI to an imperfect system, as I mentioned earlier. Um, other things I think IT teams are often overwhelmed by the rising requests for self serving data access and integration, varying data requirements from different users, complicating the process further. So again, starting to see some opportunities for AI supported data platforms to help like reduce some of the challenges around data preparation and management, incompatible data types, formats, aging data. These things all pose obstacles to effective data access and collection. Skills Gap, which Qiraat hit on, I think the data related skill gaps are further hindering the development of robust data management as well as AI related skills gaps. It’s another area where actually, I think organizations are starting to think about AI supported data platforms, or potentially agentic AI helping to winnow data into insights. Again, there’s a risk involved, because you’re not doing it through human insight, but potentially it could be helpful and work. But with all of these, these pieces, all of these challenges, I think there is one underlying challenge that that we see and pretty much everywhere, which is, you know, you have the question of, can it be done? And after you answer, and this is where Qiraat was coming in, there are the questions of, will it work and should we do it? Because I think. Think the other questions that I’m hearing a lot, the other challenges that I’m hearing a lot are this year as opposed to last year. And Keith, you and I have spoken about this many times. The other challenge with AI applied to analytics is, okay, we can generate insights, but will those insights help us? Can we trust them? And then there’s the big question of, how are we managing the risks? Because some of those risks are unforeseen. So it definitely is all of the above, from what what the guys were saying before, plus some others, Keith Shaw source

Publishers Clearing House, which started as a magazine subscription seller known for giant check giveaways, filed for bankruptcy protection Wednesday in New York with plans to focus on its digital advertising operations and sell its assets. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Enterprise AI company Writer unveiled a new platform today that it claims will help businesses finally bridge the gap between AI’s theoretical potential and real-world results. The “AI HQ” product represents a significant shift toward autonomous AI systems that can execute complex workflows across organizations. “This is not another hype train, but a massive change coming to enterprise software,” said May Habib, Writer’s CEO and co-founder, at a press conference announcing the product. “The vast majority of enterprises have not gotten meaningful results from generative AI, and it’s been two years. There has never before been such a gap between what the tech is capable of and what the enterprise results have been.” AI HQ is Writer’s answer to this problem—a platform for building, activating, and supervising AI “agents” that can perform sequences of tasks traditionally requiring human intervention. These agents can make decisions, reason through problems and act across different systems with little human oversight. How Writer’s AI agents move beyond chatbots to deliver real business value The announcement comes as many enterprises reevaluate their AI strategies. According to Habib, most AI implementations have failed to deliver substantial value, with businesses struggling to move beyond basic generative AI use cases. “Process mapping is the new prompt engineering,” Habib said, highlighting how the company’s approach has evolved beyond simply crafting the right text prompts to designing entire workflows for AI systems. AI HQ consists of three main components: a development environment called Agent Builder where IT and business teams collaboratively create agents; Writer Home, which provides access to over 100 pre-built agents for specific industries and functions; and observability tools for monitoring and governing agent behavior at scale. During a product demonstration, Writer executives showed how customers already use these technologies. For example, an investment management firm uses Writer’s agents to automatically generate fund reports and personalized market commentary by pulling data from Snowflake, SEC filings, and real-time web searches. Another demonstration showed a marketing workflow where an agent could analyze a strategy brief, create a project in Adobe Workfront, generate content, find or create supporting images, and prepare the material for legal review. Enterprise AI that actually works: How Writer’s autonomous agents tackle complex business workflows Writer’s pivot to agent-based AI reflects broader market trends. While many companies initially focused on using large language models for text generation and chat functions, businesses are increasingly exploring how AI can automate complex processes. “Ten percent of the headcount is going to be enough,” Habib told Forbes in a recent interview about the potential workforce impact of agent technologies. This dramatic assertion underscores the transformative potential—and potential disruption—these technologies may bring to knowledge work. Anna Griffin, chief marketing officer at cybersecurity firm Commvault and an early adopter of Writer’s agent technology, spoke during the press conference about the value of connecting previously siloed systems. “What if I could connect our Salesforce, Gainsite, Optimizely? What if I could pull together enough of the insights across these systems that we could actually work to create an experience for our customer that is seamless?” Griffin said. Her advice for others: “Think about the hardest, gnarliest problem your industry has, and start thinking about how agentic AI is going to solve that.” The future of AI learning: Writer’s self-evolving models remember mistakes and learn without retraining The event also featured a presentation from Waseem AlShikh, Writer’s co-founder and CTO, who unveiled research into “self-evolving models” — AI systems that can learn from their mistakes over time without additional training. “If we expect AI to behave more like a human, we need it to learn more like a human,” AlShikh explained. He demonstrated how traditional AI models repeatedly make the same errors when faced with a maze challenge, while self-evolving models remember past failures and find better solutions. “This unique architecture means that over time, as the model is used, it gains knowledge — a model that gets smarter the more you engage with it,” AlShikh said. Writer expects to have self-evolving models in the pilot by the end of the year. Inside Writer’s $1.9 billion valuation: How enterprise AI adoption is driving explosive growth Writer’s aggressive expansion comes after raising $200 million in Series C funding last November, which valued the company at $1.9 billion. The funding round was co-led by Premji Invest, Radical Ventures and ICONIQ Growth, with participation from major enterprise players including Salesforce Ventures, Adobe Ventures and IBM Ventures. The company has witnessed impressive growth, with a reported 160% net retention rate. This means customers typically expand their contracts by 60% on average after initial adoption. According to a Forbes report published today, some clients have grown from initial contracts of $200,000-$300,000 to spending approximately $1 million each. Writer’s approach differs from competitors like OpenAI and Anthropic, which have raised billions but focus more on developing general-purpose AI models. Instead, Writer has developed its own models—Palmyra—specifically designed for enterprise use cases. “We trained our own models even though everyone advised against it,” AlShikh told Forbes. This strategy has allowed Writer to create AI that’s more secure for enterprise deployment, as client data is retrieved from dedicated servers and isn’t used to train models, mitigating concerns about sensitive information leaks. Navigating the $114 billion enterprise AI market: Opportunities and obstacles ahead Writer’s ambitions face obstacles in a competitive landscape. The enterprise AI software market — projected to grow from $58 billion to $114 billion by 2027 — is attracting intense competition from established tech giants and well-funded startups alike. Paul Dyrwal, VP of generative AI at Marriott who appeared at Writer’s press conference, shared advice for enterprises navigating this rapidly evolving field: “Focus on fewer, higher-value opportunities rather than chasing every possibility.” The announcement also comes amid growing concerns about AI’s impact on jobs. While Habib acknowledged that AI will change work dramatically, she painted an optimistic picture of the transition. “Your people are instrumental to redesigning

Image: garloon/Envato Images Apple’s appeal against the U.K.’s demands to be provided access to any material uploaded to iCloud will not remain confidential. The country’s Investigatory Powers Tribunal dismissed the government’s request to prevent details about the hearing from being published on its website, despite claims of national security concerns. In a judgement published on Monday, Judges Rabinder Singh and Judge Jeremy Johnson wrote: “For the reasons that are set out in our private judgement, we do not accept that the revelation of the bare details of the case would be damaging to the public interest or prejudicial to national security.” In February, it was reported that the U.K.’s Home Secretary had asked Apple for a way to access user information that was covered under Advanced Data Protection, an optional security layer introduced in 2022. Data stored under ADP offers the highest level of protection the company provides, keeping information hidden even from Apple itself. They invoked the Investigatory Powers Act of 2016, which grants law enforcement the authority to compel companies to provide access to data as part of criminal investigations. The law also prevents Apple from publicly disclosing the request or voicing its concerns to the public, effectively placing the company under a gag order. In response, Apple disabled access to the ADP encryption feature for devices registered in the UK. iPhone, iPad, and Mac users in the country can no longer sign up for ADP, and existing users must disable it manually to retain iCloud access. The company then appealed the U.K.’s order at the Investigatory Powers Tribunal, arguing that compliance would jeopardise user privacy and set a dangerous precedent. It is this case that the U.K. wished to keep private. “There is no reason why the U.K. [government] should have the authority to decide for citizens of the world whether they can avail themselves of the proven security benefits that flow from end-to-end encryption,” Apple wrote in a statement to Parliament. Must-read Apple coverage The U.K. says it only wants access to data useful for criminal investigations Senior officials from the U.K. privately met with their U.S. counterparts in March to clarify that their request for access to encrypted data in Apple’s iCloud is not a blanket demand. Instead, they are seeking access solely to data linked to individuals already involved in crimes such as terrorism, according to Bloomberg. British officials emphasised separate warrants would be required for each access request, Bloomberg’s sources said, ensuring they are strictly tied to investigations into serious crime within the U.K. They denied seeking wide-ranging powers to access anyone’s data for any reason, particularly that of U.S. residents, a claim that has fueled controversy. U.S. lawmakers warn of free speech and privacy risks U.S. Director of National Intelligence Tulsi Gabbard warned the U.K.’s demands may violate the CLOUD Act, which limits foreign governments from directly accessing encrypted data stored by U.S. companies. She also raised concerns about the effective gag order the Investigatory Powers Act of 2016 imposes on Apple, which was reiterated by a bipartisan group of U.S. lawmakers. They urged the U.K. to “remove the cloak of secrecy” surrounding the order, claiming that it is “violating the free speech rights of US companies and impairing Congress’ power and duty to conduct oversight on matters of national security.” Under President Donald Trump’s first term as president, the FBI protested Apple’s ADP over similar concerns regarding law enforcement’s inability to access encrypted data — a barrier the U.K. is now attempting to bypass. Meanwhile, tech companies like Apple warn that creating a backdoor would increase the risk of abuse by criminals and authoritarian governments alike. source

While she wasn’t sure how it would land, it grabbed the attention of the CIO, who had never seen this approach before, and opened the dialogue for Schulze to be a candidate. She decided to push past any insecurities or fears, and go for a position she didn’t necessarily feel totally qualified for, but ended up landing the job. Schulze knows not everyone feels comfortable stepping out of their comfort zone, but as a leader, she wants to set that example for her employees. She identifies opportunities for growth and advancement, regardless of background or experience, and helps them tap into their potential. She understands it’s difficult for women to break through the boys club mentality that can exist in tech, and the challenge to fight stereotypes around women in IT and STEM careers. In her own career, Schulze had to apply herself extra hard to prove her worth and value, even when she had the same answers as her male counterparts. But she never got discouraged or deterred from tech, focusing instead on positive role models and mentors to help guide her. source

By Lauraann Wood ( April 8, 2025, 11:14 PM EDT) — Outcome Health’s former CEO and co-founder are challenging their convictions for lying about the company’s capabilities and value in a $1 billion fraud, arguing a legally deficient fraud theory, unfair narrative evidence and the government’s admitted pre-trial asset over-restraint warrant unwinding the jury’s verdict…. 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

Measuring customer experiences has long been a cornerstone of customer experience (CX) programs, yet traditional survey-based feedback methods are increasingly under pressure to evolve. As businesses strive to capture customer perceptions more accurately, AI-driven strategies are emerging as powerful supplements to legacy measurement techniques. Advanced technologies and analytic methods redefine how organizations measure experiences and extract insights. CX leaders have an opportunity — and a responsibility — to spearhead this transformation. To remain relevant, they must challenge outdated methodologies, embrace innovation, and modernize measurement strategies. CX teams can unlock deeper, more actionable insights beyond conventional surveys and static metrics. These advanced capabilities elevate CX and drive measurable improvements in business performance, strengthening the connection between CX initiatives and financial success. Modernizing CX Measurement: The Opportunity Ahead As organizations mature their CX measurement, the insights they gain empower executive decision-makers to understand the financial benefits of enhancing CX quality and prioritize improvement opportunities to maximize their impact. Legacy strategies often fail to inspire action or prove the financial value of CX improvement. Surveys typically lack actionable root-cause analysis and fail to establish a concrete link between customer feedback and business outcomes. By adopting modern measurement capabilities, CX programs provide leaders with insights directly connected to financial performance, transforming how organizations approach customer experience initiatives. Key Opportunities Driving CX Measurement Maturity Organizations must address several critical areas to realize the potential of a more mature CX measurement function. Here are four of the top opportunities we have identified to advance CX measurement capabilities and practical steps to get started: 1. Measure Beyond Surveys Techniques such as conversational intelligence and social media listening offer real-time insights into customer perceptions. By enriching this data with operational and financial metrics, organizations can perform advanced analytics to uncover actionable root causes and establish a financial link to CX value. 2. Benchmark Experience Effectively Benchmarking experience performance is useful, but it must be done thoughtfully. Many organizations fall into the trap of comparing unblinded internal survey scores to external benchmarks — an inappropriate approach. Instead, as a best practice, use blinded research that includes the organization’s brand and leverage these comparisons strategically to drive meaningful decisions rather than superficial vanity metrics. 3. Leverage AI In CX Measurement AI is impacting CX measurement in three primary ways: Generating signals: AI can generate signals from unstructured and unsolicited feedback. For example, digital intelligence can infer customer perceptions through non-survey channels such as online interactions. Generating insights: AI analytics, such as machine learning models, can generate insights by predicting customer behavior based on experience quality. Enhancing interactions: Generative AI models can support automated interactions, including personalized responses to customer complaints. 4. Prove The Value Of CX And ROI CX leaders consistently tell us that they struggle to show the business value of their efforts. To overcome this, organizations must articulate the financial impact of experience improvement using empirical measurement or statistical modeling methods. Organizations can employ these techniques to demonstrate ROI as CX measurement matures. Embrace The Future Of CX Measurement Now is the time for CX leaders to drive their organizations toward a more modern, sophisticated approach to experience measurement. By identifying opportunities, addressing challenges, and creating a roadmap for advancement, they can avoid stagnation and unlock the full potential of CX insights. When executed successfully, maturing CX measurement strategies transition organizations from reporting traditional metrics to delivering actionable insights that enhance customer experiences and drive financial success. To learn more about how to future-proof CX measurement strategies, join us at Forrester’s CX Summit North America in June. We will be hosting a Q&A session titled “Boost Your Experience Measurement Mastery,” one of several sessions designed to equip CX leaders and teams with measurement best practices and actionable strategies. Explore the full agenda here. source

Data governance is mission-critical for modern enterprises using analytics and AI to make decisions. Yet we hear from many clients that they are on their second, third, or even fourth attempt at establishing enterprise data governance. Why? Most governance programs focus on formalization of governance controls without embedding governance into the organization’s culture. They add governance councils and roles such as data owners, data custodians, and data stewards but ignore the human-centered roles that transform processes into working, adopted practices for data- and AI-driven decision-making within an organization. Roles To Embed Governance In Your Culture To move beyond compliance-driven governance and into a cultural model of data- and AI-driven decision-making, organizations need specialized roles focused on behavior change through communication, literacy, adoption, and engagement. When drafting your data governance policy documents, include roles such as: Data literacy lead. This role establishes and drives organizational data fluency by equipping employees with knowledge of how to recognize, evaluate, work with, communicate, and apply data in the context of business priorities and outcomes. Governance can’t succeed if employees don’t understand data in the first place. This leader will ensure that governance isn’t just about policies — it’s about enabling informed decision-making at every level. Without this leader, your enterprise will have rules without insights. Change management lead. Governance and analytics initiatives need to be embraced rather than resisted. The change management lead role focuses on overcoming corporate culture barriers, addressing resistance, and embedding governance as part of an organization’s natural workflow. Without this function, even the best governance frameworks will face pushback and slow adoption. Enablement champions. An enablement champion accelerates data, AI, and analytics adoption. While governance sets the rules and stewards focus on data quality and access, enablement ensures that teams can actually apply data, AI, and analytics in their daily work by providing training, support, and resources, as well as ensuring that data-driven thinking becomes a part of everyday work. Without enablement champions, you risk a lot of shadow analytics and AI popping up as people struggle to use what’s available to them. Data translator. Data translators convert raw data into meaningful business context. Governance programs fail because they assume that users can make sense of structured datasets without guidance. The data translator acts as a bridge between technical teams and business units, ensuring that governance efforts translate into data that can be used to form actionable insights. Without data translators, you may fail to connect data governance to tangible business results, risk mitigation, outcomes, and value. Data storyteller. Data storytellers communicate data- and AI-based insights through compelling narratives. Governance isn’t just about managing data; it’s about unlocking its value. The data storyteller helps business leaders understand the impact of governance by framing data-driven insights in a way that is engaging, persuasive, and aligned with strategic business objectives. Storytellers help others understand why governance matters and who it impacts. Without these roles, governance remains a theoretical construct rather than an operational reality. Employees see governance as an obstacle, rather than a framework that empowers them to work smarter. Show The “Why” And “How” For Governance Beyond missing key roles, most governance programs fail to explain the why and how of data evolution. They document policies and procedures but ignore a fundamental query: How does data get leveraged to turn into enterprise knowledge and wisdom? To be effective, governance must illustrate: How raw data becomes structured information (e.g., through validation, integration, and categorization). How information turns into knowledge (e.g., by adding business context, analysis, and interpretation). How knowledge evolves into wisdom (e.g., through experience, strategic decision-making, and action). When governance programs fail to communicate this flow, they reduce governance to a set of rules rather than a system that empowers better decision-making. Employees disengage because they don’t see governance as relevant to their daily work or the broader business strategy. Now What? How To Fix These Governance Gaps By addressing the early-stage gaps, enterprises can transform from static policy documents into dynamic drivers of business intelligence. This can help to make sure that governance is not just adopted but actively leveraged to create lasting business value. Schedule an inquiry with me to discuss:   Other colleagues I recommend Relating to this topic, don’t miss out on connecting with: Jayesh Chaurasia (data governance 101–301) Raluca Alexandru (data governance to support data collaboration efforts) Katy Tynan (advanced change management and change leadership) Cheryl McKinnon (internal communications tools) Zeid Khater (artificial intelligence 101, third-party data integration, and customer data segmentations) source