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Theres a scene in Office Space where Peter sits across from two consultants during a company downsizing. They ask him, What would you say you do here? He hesitates, smirks, and admits he only works about 15 minutes a week. The rest of the time, hes pretending. It was comedy in 1999. Its confession now. That question has come back to us. For years, we filled our calendars, stayed visible, and kept the machine moving. Our worth was measured in hours, output, and presence. It had to be. Humans were the system, and the system required us to keep it running. We didnt question it because that was how things got done. AI has changed that. It can now do many of the things we once did to keep things moving: the summaries, the reports, the follow-ups, the updates, the spreadsheets. It can organize, calculate, write, and execute at a pace we cant match. That realization feels strange at first, but its also freeing. Now we get to hand that part over. We can give the robotic work to the robots and return to the human work. The work of thinking, deciding, designing, and connecting. So what does that look like? For one, it means our conversations are changing. When the noise quiets, the meetings sound different. Theres more space to ask better questions. We can finally talk about what matters: What is the business really trying to accomplish? Whats next? What do we need to build the product, craft the strategy, organize the team, and align around purpose? Its fantastic, really. Because when people stop being buried in repetitive work, they start showing up differently. They bring curiosity. They tell the truth. They collaborate in new ways. Im hearing it everywherein companies that are deep into their AI transformation and in those that are just starting. The tone is changing. The conversations are more human. Were still in the waiting room of this transition. Some are pacing the floor, some are seated patiently, some are already being called in. Wherever a company sits on that curve, the shift has begun. Deloittes 2024 Global Human Capital Trends report describes this moment as a readiness gap. Most leaders recognize that AI and technology will transform their organizations in the coming years, yet few say they feel prepared to lead their people through that change. The tools are ready. The humans are still catching up. For leaders, this is the moment to adjust the focus. The work still needs watching, but the focus of that attention is different. Its no longer about overseeing tasks; Its about overseeing direction. How we design. How we execute. How we build and with whom. Leadership now is about being intentional and accountable for how work is created, not just how it is completed. Many leaders are rebuilding, or at least redesigning, how they lead. The language is changing. The tone is shifting. Its not a different language, but it has a new accent. And those who thrive in this era will be the ones who can translate it. Theyll know how to take complexity and turn it into clarity. Theyll bring forward a sharper vision, a stronger purpose, and a deeper ability to communicate the why. Theyll be what I call full-stack leaders: people who can support the front, the back, and the middle layer. They understand product, people, and process, and they move fluidly across them all. AI has taken the repetitive pieces off our plates and has given us back the chance to think, create, and build with intention. It gives us room to lead.
Category:
E-Commerce
When an X user recently pointed out the eye-popping increase in billionaires wealth since 2015, entrepreneur Mark Cuban, a billionaire himself, responded with his opinion on why, but he urged followers to consider a different question: Why are we not giving incentives to companies to require them to give shares in their companies to all employees, at the same percentage of cash earnings as the CEO? Cuban said. It is the right question to be asking. Because while the debate over wealth inequality continues, the solution has been hiding in plain sight for decades. The top 10% of U.S. households now control 67% of all wealth, while the bottom half holds just 2.5%. The typical American worker approaches retirement with about $4,000 in savings, which is less than the cost of one month in an assisted living facility. That imbalance is not sustainable, economically or socially. The fix does not require new legislation or another corporate responsibility pledge. It lies in a proven model that has been quietly transforming companies and communities for 50 years: employee ownership. From Silicon Valley to Main Street Silicon Valley figured this out long ago. Equity compensation has been the foundation of the tech sectors innovation economy since the 1970s. Stock options allowed startups to attract world-class talent without paying top-tier salaries, align employee incentives with company performance, and build wealth for workers who might otherwise never own an asset. Yet outside of tech, broad-based ownership remains rare. Fewer than 7,000 U.S. companiesmostly in traditional sectors like manufacturing, construction, and distributionoperate under an employee stock ownership plan (ESOP). The results, however, mirror the Valleys success. Employee-owned firms grow more than 2% faster per year than their peers and are half as likely to go bankrupt. During the 2008 financial crisis, they laid off workers at only one-third the rate of conventional firms. For employees, the impact is just as powerful. ESOP participants hold 92% higher median household wealth, twice the retirement savings, and 33% higher median income than comparable workers. This is not philanthropy. It is a durable, market-tested strategy that drives growth, resilience, and equity at the same time. The Timing Could Not Be Better Today, several powerful trends make this the perfect moment to bring ownership to scale. A massive generational handoff is underway. Ten thousand baby boomers retire each day, many of them owners of successful small and midsize businesses with no succession plan. Transferring ownership to employees keeps those businesses rooted in their communities, preserves good jobs, and rewards founders with fair market value. The retirement crisis demands new solutions. With average savings at historic lows, workers need wealth-building tools that go beyond 401(k) plans. Ownership creates an asset base that compounds over time, restoring what traditional pensions once offered. Labor shortages are reshaping industries. As skilled workers grow scarce, companies that offer ownership will win the competition for talent, not only by paying well but by giving people a reason to stay. Economic volatility favors resilience. Employee-owned companies outperform during downturns because people at every level have a stake in the outcome. Ownership builds both financial and cultural strength. Beyond Good Intentions America has no shortage of programs designed to help workers. What it lacks is awareness and adoption of the ownership mechanisms that allow employees to share in the value they create. As long as labor and ownership remain separated, inequality will continue to deepen. When employees have an equity stake, their focus shifts from completing tasks to building lasting value. They think like owners because they are owners, and that mindset fuels innovation, strengthens loyalty, and creates a powerful cycle of trust and accountability. The impact case is clear, and the business case is even stronger. Broad-based ownership builds companies that last. It keeps wealth circulating within communities instead of extracting it, and it turns employees into long-term investors in the enterprise they help build. The Moment to Act We are standing on the edge of a once-in-a-generation opportunity to reimagine capitalism for shared prosperity. Employee ownership will not fix every inequity in our economy, but it addresses one of the most fundamental: who benefits from the value a company creates. Cubans challenge should not disappear into the social media ether. It should become a call to action for policymakers, investors, and business leaders to make employee ownership the standard, not the exception. America does not need another wealth redistribution debate. It needs a wealth participation strategy. Employee ownership represents capitalism at its best: fair, inclusive, and fiercely competitive. It aligns profit with purpose and ensures that the people who build our companies share in their success. If we scale it now, we can turn todays inequality into tomorrows shared prosperity.
Category:
E-Commerce
You’ve heard the gospel: AI is going to change everything. Good, great, grand. But when youre staring down a deadline and 80 unread emails, you don’t need philosophy, you need a cheat sheet. The fastest way to master AI isn’t by watching lectures, it’s by finding a way to replace an hour of your grind with a 10-second prompt. Here are five specific, repeatable ways to automate your most time-consuming professional tasks. Grab your chatbot of choice (Gemini, ChatGPT, Claude, Copilotwhatever floats your boat) and let’s get to work. Writing Staring at a blank page. Tedious, formulaic first drafts. Enough. You are a professional. You shouldn’t be spending an hour drafting a boilerplate email to a client or writing the first three paragraphs of a report. Thats grunt work. Instead, master constraint-based prompting. This is where you tell the AI exactly what to write and how to write it, forcing it to follow your specific, professional rules. Heres a prompt example: “You are a [job title]. Draft a [document type (memo, email, etc.)] to [target audience]. The tone must be [tone]. The three key takeaways are [list three specific bullet points]. The final memo should be around [length in words] and include a subject line. Post-meeting action items Sifting through long transcripts and meeting notes for action items? You’re doing it wrong. Let the AI do the heavy lifting of synthesis. Its time to leverage deliverable-based prompting. Instead of asking for a summary, ask the AI to produce specific, structured outputs from a large body of text, such as a meeting transcript or a dense PDF. For example: “Analyze the following [meeting transcript/document]. Do not summarize the entire text. Instead, produce three distinct outputs: 1) A table listing all action items, the person responsible, and the deadline mentioned. 2) A list of three open questions that were not resolved. 3) A short, two-sentence email subject line for the follow-up.” In less than a minute, you can transform raw data into a clean, actionable task list. Research To turn generative AI into a true, trusted research assistant that can search and cross-reference information scattered across multiple work files requires using tools that let you upload your own content, such as Googles NotebookLM or similar features in other platforms. This is called contextual grounding, and it involves uploading a handful of annual reports, project documents, or extensive research files. Check with your organization first to see if there are any rules against this. Heres a prompt you can use: “Based only on the uploaded documents, what is the biggest discrepancy between the Q4 2024 revenue projection [from Document A] and the actual Q1 2025 marketing spend [from Document C]? Explain the gap in three bullet points, referencing the specific document where the information was found.” This lets you stop relying on the AIs general knowledge and start using it as a hyperefficient analyst for your own private data, generating insights that would take hours to gin up on your own. Brainstorming Thanks to AI, hitting a creative wall or falling victim to groupthink during brainstorming is nothing like it used to be. While your brain thinks linearly, AI can think exponentiallybut you have to force it to show its work. Employ critical reasoning prompting, also called “chain-of-thought.” This forces the AI to debate, critique, and explore alternatives before settling on an answer. A sample prompt formula: “I have an idea for a new product feature: [describe the feature]. Before you propose a name for it, I need you to first: 1) Act as a skeptical customer and list three reasons why this feature is useless. 2) Act as a competitor and list three ways they could easily copy and neutralize the feature. 3) Only after those two steps, propose three distinct, benefit-driven names for the feature.” This forces the AI to act as a constructive adversary, getting you to a better, more robust idea much faster.
Category:
E-Commerce
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