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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.
Category:
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.
Category:
E-Commerce
When I first encountered AI, it wasnt anything like the sophisticated tools we have today. In the 1990s, my introduction came in the form of a helpful, but mostly frustrating, digital paperclip. Clippy, Microsofts infamous assistant, was designed to help, but it often got in the way, popping up at the worst moments with advice no one asked for. AI has evolved since then. Major companies like Apple are investing billions, and tools like OpenAIs ChatGPT and DALL-E have reshaped how we interact with technology. Yet, one challenge from Clippys era lingersunderstanding and adapting to user intent. The original promise of AI was to create experiences that felt seamless, intuitive, and personal. AI was supposed to anticipate our needs and provide support that felt natural. So, why do so many systems today still feel mechanical and rigidmore Clippy than collaborator? When AI assistance is a burden When first introduced, Clippy was a bold attempt at computer-guided assistance. Its purpose was groundbreaking at the time, but it quickly became known more for interruptions than useful assistance. Youd pause when typing, and Clippy would leap into action with a pop-up: It looks like youre writing a letter! Its biggest flaw wasnt just being annoying: It lacked contextual awareness. Unlike modern AI tools, Clippys interactions were static and deterministic, triggered by fixed inputs. There was no learning from previous interactions and no understanding of the users preferences or current tasks. Whether you were drafting a report or working on a spreadsheet, Clippy offered the same generic adviceignoring the evolving context and failing to provide truly helpful, personalized assistance. Is AI destined to be like Clippy? Even with todays advancements, many AI assistants still feel underwhelming. Siri is a prime example. Though capable of setting reminders or answering questions, it often requires users to speak in very specific ways. Deviate from the expected phrasing, and it defaults to, I didnt understand that. This is more than a UX flawit reveals a deeper issue. Too many AI systems still operate under a one-size-fits-all mentality, failing to accommodate the needs of individual users. With Siri, for instance, youre often required to speak in a specific, rigid format for it to process your request effectively. This creates an experience that feels less like assistance and more like a chore. Building a smarter assistant isnt just about better models. Its about retaining context, respecting privacy, and delivering personalized, meaningful experiences. Thats not just technically difficultits essential. Helpful AI requires personalization Personalization is what will finally break us out of the Clippy cycle. When AI tools remember your preferences, learn from your behavior, and adapt accordingly, they shift from being tools to trusted partners. The key to this will be communication. Most AI today speaks in a one-dimensional tone, no matter who you are or what your emotional state is. The next leap in AI wont just be about intelligence, itll be about emotional intelligence. But intelligence isnt only about remembering facts. Its also about how an assistant communicates. For AI to truly feel useful, it needs more than functionality. It needs personality. That doesnt mean we need overly chatty bots. It means assistants that adjust tone, remember personal context, and build continuity. Thats what earns trust and keeps users engaged. While not every user may want an assistant with a personality or emotions, everyone can benefit from systems that adapt to our unique needs. The outdated one-size-fits-all approach is still common in many AI tools today and risks alienating users, much like Clippys impersonal method back in the early days. For AI to thrive in the long term it must be designed with real humans in mind. Building Clippy 2.0 Now imagine a Clippy 2.0an assistant that doesnt interrupt but understands when to offer help. One that remembers your work habits, predicts what you need, and responds in a way that feels natural and tailored to you. It could help you schedule meetings, provide intelligent suggestions, and adapt its tone to fit the moment. Whether it has a personality or not, what matters is that it adapts toand respects the uniqueness of every user. It might even respond with different tones or emotions depending on your reactions, creating an immersive experience. This kind of intelligent assistant would blend seamlessly into your routine, saving you time and reducing friction. Clippy may have been a trailblazer, but it lacked the technological foundation to live up to its potential. With the advances weve made today, we now have the tools to build a “Clippy 2.0an AI assistant capable of transforming the way we interact with technology. Although maybe this time, it doesnt need to come in the form of a paperclip with a goofy smile. Oleksandr Kosovan is the CEO and founder of MacPaw.
Category:
E-Commerce
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