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At Apples annual WWDC keynote, the highest-level subject is always the future of its software platforms. And the big news in that department usually stares us right in the face. In 2023, for example, it was the debut of Apple Vision Pro, the companys entry into the headset market and its first all-new experience since the Apple Watch. Last year brought Apple Intelligence, its branded take on what AI should look like as a core element of computing experiences. And then there was Monday mornings WWDC 2025 keynote, as streamed online to millions and screened to a select audience of in-person attendees at Apple Park. After Apples embarrassing inability to ship the AI-infused update to Siri it showed off at WWDC 2024, it was hardly surprising that this years event didnt bet everything on whipping up a further AI frenzy. That alone set it apart from last months Google I/O keynote, whose topics consisted of AI, AI, and more AI, with some AI drizzled on top. [Photo: Apple] Apple did introduce some new AI during the keynotequite a bit of it. Overall, though, the event felt like an act of counterprogramming. Instead of positioning itself as a leader in AIor at least quashing fears that its a laggardthe company seemed happy being itself. From the unified new design to old features (phone calls!) turning up in new places (the Mac!), it focused on giving consumers even more reasons to own and use as many of its products as possible. Herewith a few of the impressions I took away from my morning at Apple Park: Liquid Glass is classic Apple, in the Steve Jobs sense. In 2012, one of Tim Cooks first dramatic moves after succeeding Jobs as CEO was to oust software chief Scott Forstall. That led to a reorganization that put Jony Ive in charge of design for software as well as hardware. Ives influence was seen in the iPhones iOS 7 upgrade the company shipped the following year. It ditched the lush skeuomorphism of the iPhones software up until that time for a far flatter look, bringing to mind the understated, Dieter Rams-like feel of an Ive MacBook, manifested in pixels rather than aluminum. Ive left in 2019, but the principles he instilled have informed Apple software ever since. [Photo: Apple] But now theres Liquid Glass, a new aesthetic Apple is rolling out across its portfolio of platforms. Its glossy, dimensional, pseudorealistic, and animateda dramatic departure from iOS 7-era restraint, but reminiscent of both earlier iOS releases and also older Apple software all the way back to the first version of the Macs OS X in 2000. That was the one with buttons that Jobs said people would want to licka memorable design imperative that is suddenly relevant again. As my colleague Mark Wilson writes, Liquid Glass isnt about adding new functionality to Apple devices. It might not even be about making them easier to usein fact, when an interface introduces transparency effects and other visual flourishes, legibility is at risk. It does, however, look cool in a way thats classically Apple, and which the Apple of recent years had deemphasized. The iPad has left limbo . . . for Macland. For years, Apple seemed to have reached a mental standstill with the iPad. The company clearly wanted its tablet to be something distinct from a Mac, but it also appeared to be short on ideas that were different than the Mac, especially when it came to building out iPadOS as a productivity platform. End result: The platform has foundered rather than matured. [Photo: Apple] With iPadOS 26, the iPad will finally see a lot of meaningful change all at once, and most of it is distinctly Maclike. Its getting a menu bar. Windows that float and overlap. A more full-featured Files app and, for the first time, a Preview app. Even the quirky circular cursor gives way to a more conventional pointy one. As an unabashed iPad diehard, I admit to my fair share of trepidation about all this. The iPads abandonment of interface cruft in favor of considered minimalism is a huge reason why Ive been using one as my primary computer since 2011: I dont like to wrangle windows or scour menus for the features I need, hidden among those I dont. Maybe Apple has figured out how to retain whats great about the iPad even as it gives in to the temptation to borrow from the Mac. But Im alarmed by the apparent disappearance of the iPads foundational multitasking features in the first iPadOS 26 beta, and hope theyll return before the software ships this fall. VisionOS is still evolving, and thats good. Its been two years since Apple unveiled the Vision Pro and 17 months since it shipped. Rumors aside, we still arent any closer to clarity on how the $3,500 headset might lead to a product that caters to a larger audience than, well, people who will pay $3,500 for a headset. Even Tim Cook says it isnt a mass-market product. Still, Apples enthusiasm for spatial computing doesnt seem to be flagging. As previewed during the WWDC keynote, VisionOS 26 looks downright meaty, with more realistic-looking avatars for use in video calls, features for watching movies and playing games with Vision Pro-wearing friends, widgets you can stick on a wall or place on a mantel in the real world, AI-powered 3D effects for 2D photos, partnerships with companies such as GoPro and Sony, and more. None of these additions will prompt radically more people to spring for a Vision Pro in its current form. But assuming that the headset doesnt turn out to be a dead end, Apples current investment could help a future, more affordable version offer compelling experiences from day one. Its still unclear whether ChatGPT is a feature or a stopgap. Apples own AI assistant, Siri, was acknowledged only at the start of the keynote, when Craig Federighi, senior VP of software engineering, mentioned last years announcements and the decision to delay the newly AI-savvy version until it meets Apples high-quality bar. Another AI helper did pop up several times during the presentation, though: ChatGPT. For example, it powers a new Visual Intelligence feature that will let users ask questions about the stuff on-screen in any app. The keynotes example: Upon seeing an image of a mandolin in a social post, you can ask, Which rock songs is this instrument featured in? Given that the new Siri features Apple revealed a year ago remain unfinished, adding a dash of ChatGPT here and there is an expedient way to maintain some AI momentum. But does the company see integrating the worlds highest-profile LLM-based assistant as an attractive user benefit in itselfor just a placeholder until it can offer similar technology thats entirely under its own control? Im still not sure. At WWDC 2024, Federighi also talked about incorporating other AI models, such as Googles Gemini, but no news has emerged on that front since. Even during a pivotal, unpredictable time for the tech industry, one of the WWDC keynotes purposes remains straightforward. Apple needs to get consumers excited for the software it will ship in the fall, which isnt necessarily synonymous with blowing them away through sheer force of AI breakthroughs. In a Bluesky conversation, one commenter suggested to me that people arent actually clamoring for AI at alla take that has a whiff of truth to it even if it isnt the whole story. Ultimately, users want pleasant products that help them get stuff done, whether in a personal context, a work environment, or somewhere in between. After last years WWDC, assuming Apple will ship everything it brags aboutat least in a timely fashionis dangerous. But its easier to envision the confident vibe of this years keynote paying off, because so much of it involved the company playing in its comfort zone.
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E-Commerce
As the pace and complexity of business accelerate, enterprise leaders are under pressure to deliver more, faster: more growth, innovation, and resilience. And yet, despite bold visions and thoughtful strategies, many organizations still struggle to execute effectively. Its not because leaders fail to plan; they lack real-time visibility and alignment. In my role working closely with product and technology leaders across industries, a consistent pattern emerges: Strategy is often clear at the top, but somewhere between the boardroom and the frontlines, execution becomes fragmented. Priorities get lost in translation. Resources are misaligned, and risks are spotted too late. What started as a solid strategic plan ends up slipping out of reach. This disconnect between strategy and execution isnt a minor inefficiency; it poses a systemic risk. When leaders lack real-time visibility into how work is progressing across their organization, even the best-laid plans can derail. The impact is both tangible and costly: Missed revenue from delayed go-to-market initiatives Rising costs from duplicated work or misaligned efforts Operational risk from bottlenecks or blockers no one saw coming Erosion of culture over time, weakening alignment, and organizational health A lack of connected insight Enterprise leaders dont suffer from a lack of data; they suffer from a lack of connected insight. Dashboards and status updates are often backward-looking, fragmented across systems, and disconnected from the actual work. This creates a lag between whats happening and what leaders think is happening, making it challenging to anticipate risks or adjust course in time. But with AI, we now have access to radical, objective visibilityinsights grounded in real-time data rather than subjective reporting. More importantly, AI empowers them to lead proactive change across large, complex organizations by predicting challenges early and helping navigate transformation with speed and precision. This shift marks a new era in leadership, one where execution is no longer just about tracking work but about driving continuous change and adaptability at scale. Modern platforms can help Modern work management platforms are evolving to meet this challenge by providing leaders with real-time visibility and control while preserving the autonomy and agility of their teams. These solutions connect strategy to execution, enabling organizations to deliver impact with greater speed, consistency, and confidence. Effective execution tools combine control and agility without forcing trade-offs, enabling leaders to maintain oversight while empowering teams to stay productive. They leverage explainable AI to flag emerging risks, clarify their root causes, and prioritize urgency, supporting more informed, proactive decision making. These tools also embed visibility directly into the workflows where teams operate, driving consistent data usage and ensuring strong adoption across the organization. Bridge strategy and execution To lead effectively in todays landscape, enterprise organizations must rethink how to bridge the gap between strategy and execution. This means evolving beyond static planning cycles and siloed reporting, enabling real-time coordination across teams, projects, and priorities. Specifically, leaders need: Live portfolio visibility to monitor execution in real time and surface emerging risks Standardized frameworks that align teams without creating bottlenecks or rigidity Workforce intelligence tools that ensure the right people are working on the right priorities AI-powered insights that not only flag risks early but also help explain and prioritize them These capabilities are not just nice-to-haves; they reflect the most common and urgent needs we hear from enterprise leaders. Delivering them requires once-unimaginable AI tools designed to enable leaders to act swiftly, navigate confidently, and adapt at scale. The future of enterprise success wont be defined by the boldest ideas alone but by the ability to consistently turn those ideas into outcomes. Achieving this starts with asking the right questions: Can you see how your top priorities progress in real time? Are your teams clearly aligned with your strategic goals? And are you leading proactively, or simply reacting after the fact? Execution is no longer a downstream function. Its a leadership imperative. In the age of AI, the systems we rely on to manage work must enable agility, speed, and transformation like never before. Daniel Lereya is chief product and technology officer at Monday.
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E-Commerce
Theres a growing concern that artificial intelligence is leading us to a place where we think less and rely on it more. Headlines warn that AI is eroding our critical thinking skills, creating a world of work where human ingenuity might take a backseat to automated convenience. After all, when generative AI can draft a report, summarize a dense article, or generate a marketing plan in seconds, wheres the incentive for leaders and employees to sharpen the skills we relied on before? These concerns arent baseless. Automation has always sparked questions about how reliance on technology impacts our brains and behaviors. Examples like GPS leading us to abandon our navigation skills or calculators replacing mental math, provide a glimpse into the broader challenge AI presents. Research confirms that AI may be changing the way we think today: Constant exposure to AI tools can reduce our ability to think critically. Should workplaces abandon AI and turn the clock back? Of course not. Thats neither practical nor productive. AI isnt a fleeting trend. Its a transformational shift thats here to stay. The genie is out of the bottle, and its applications in nearly every area of life and work are deepening by the day. But this raises an important question: If AI is inevitable, how can we ensure it doesnt simply make us passive users, but instead inspires us to grow and evolve in new ways? The answer lies in how we redefine the skills we value and develop in ourselves and future generations. Instead of seeing AI as a competitor to human intelligence, we must think of it as an enabler that challenges us to excel in areas where AI cant. We must consider how to develop AI fluency. Our human advantage To thrive in an AI-dominated world, enterprises need to invest in the abilities that AI can amplify but not replicate. Part of developing a fluency in AI is recognizing where it excels and where we as humans can outperform it. Here are three areas where humans excel over technology. 1. Critical thinking and judgement Generative-AI tools can surface answers faster than ever, but humans must decide which answers are valid, relevant, and ethical. In an era of AI-generated content, our ability to ask the right questions, evaluate information critically, and spot biases will be more essential than ever. 2. Creativity and problem solving AI can assist in generating ideas, but the ability to connect seemingly unrelated concepts or imagine entirely new possibilitiesknown as taking a creative leapremains inherently human. As automation tackles more routine work, businesses will increasingly seek individuals who can navigate ambiguity and generate innovative solutions. 3. Emotional intelligence and leadership Machines lack the empathy, communication skills, and interpersonal insights required to foster collaboration, inspire teams, and guide organizations through change. Our human edge lies in understanding other humans, which AI cannot replicate. Adaptability is an essential skill As AI becomes embedded in nearly every aspect of work and life, our approach to growth and development needs to evolve alongside it. Today, upskilling is less about acquiring static knowledge and more about developing the agility to apply new skills in dynamic, ever-changing contexts. Being adaptable is a skill unto itself. As AI introduces new opportunities and challenges, our success will hinge on our ability to constantly upskill and adjust to whats next. Organizations and individuals alike must embrace this new reality. For businesses, that means prioritizing upskilling programs that focus on the human-AI partnership. That could mean, for instance, teaching employees how to leverage AI effectively while continuing to contribute their unique human value. For individuals, it requires shifting from passive consumption of AI outputs to active engagement and integration. Instead of simply asking AI to provide answers, we need to think critically about the prompts we design, the follow-up questions we pose, and the frameworks we use to evaluate and synthesize its outputs. AI is a catalyst for human growth The narrative that AI is making us stupid misses the bigger picture. Like every major technological leap in history, AI is changing the nature of how we work, think, and create. But its not a replacement for human intelligence. Its an accelerator. The responsibility is ours to wield it wisely, using it to complement and expand our capabilities rather than diminish them. The future of work wont belong to those who resist AI or passively lean on it. It will belong to those who use it as a catalyst for growth, wielding this revolutionary technology to push the boundaries of what humans can achieve. The question isnt whether well need skills in an AI-driven world. Its what kinds of skills will define human success. And the answer, as it turns out, is a sharper, more agile, and more curious version of ourselves. Hugo Sarrazin is CEO of Udemy.
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E-Commerce
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