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Tesla is speeding toward a head-on collision with the realities of the auto industry. Amid protests over CEO Elon Musks involvement with President Donald Trumps administration, not to mention Teslas stagnant model line and obsolete technology, the companys revenue for the first quarter of 2025 slid 9% year over year to $19.34 billion while global deliveries shrank 13%. The second quarter was equally dire: Tesla delivered just 384,122 cars, down 13% year over year, and took in $22.5 billion in revenue, 12% lower than the same period last year. Tesla sales have now been eclipsed by Chinas BYD for three consecutive quarters. But Musk wants Tesla fanboys not to worry. Instead of focusing on the companys declining sales figures, Musk spent most of his opening remarks on his recent earnings call talking about the enormous potential of the companys Robotaxi service and Optimus humanoid robots to make Teslaand its investorsvery, very rich. Those promises are still rather hollow. Teslas Robotaxi service, which arrived in Austin in June, is still an invite-only test limited to a small geofenced area. Competitor Waymo has more than 100 fully autonomous vehicles operating on the Uber platform in that city, covering a 90-square-mile area. Tesla covers a fraction of that in a zone shaped like a penis because Musk is a comedy genius. (“It’s going to get bigger and longer,” he told investors on his recent earnings call.) Its also full of dangerous glitches that reveal the limitations of Musks self-driving solution, which currently relies heavily on tele-operators to avoid fatal accidents. Weeks after the Tesla service launched, the city of Austin says the test remains limited to 10 to 20 Model Y cars, which look nothing like the actual Robotaxi design Musk originally presented to investors. Meanwhile, Google’s Waymo and Baidu’s Apollo Go autonomous cab services continue to expand across the planet, with thousands of cars already on the streets thanks to designs that combine AI brains with multiple optical, radar, and laser sensors. The other promisethe really big oneis Optimus, the humanoid robot that Musk has said could one day transform his company into a $25 trillion market-cap, world-dominating empire. In Musks vision, legions of 5-foot-8 electric androids running Teslas vehicle-grade AI will ferry battery cells, haul parts carts, and stack sheet-metal blanks across the companys gigafactories, taking on the dull, injury-prone chores no human wants. These bots, he has said, will be working on Tesla assembly lines by the end of 2025. Next year, theyll roam third-party warehouses and logistics hubs across North America. Within five years, Musk promises, Tesla will be making 1 million units per year. Within a decade, there could be 100 million of them in the wild as companies worldwide deploy them for stockroom restocking, parcel delivery, elder-care assistance, and other services. Conveniently, their sales would buoy Teslas share price just as its core EV lineup shows its vulnerabilities. Optimus has the potential to be north of $10 trillion in revenue, like its really bananas, Musk told investors in April. “It will be the biggest product ever,” he reiterated on the July 22 earnings call. Except, just like with Robotaxi, it doesnt look like thats working out as promised. At this point, it’s extremely hard to believe that Optimus will materialize in any meaningful way within the timeframe Musk anticipates. Its even harder to believe that the program can get off the ground quickly enough to compete with companies that appear to be further ahead in developing and deploying humanoid robotsespecially in China, where competitors have the advantage of fully dominating the supply chain to manufacture bots at scale. [Image: Tesla] Market analysts predict the entire humanoid robot market could reach $13 billion to $38 billion between 2030 and 2035 (making Musk’s claims of $10 trillion in annual revenue mathematically impossible, at least for the next decade). Meanwhile, the industry is still in its Macintosh era, according to Jeff Cardenas, CEO of Apptronik, which makes the Apollo 1 humanoid robot. This is like the early 1980s for personal computers, Cardenas told me recently. We’re in the early days. That means theres a chance for Tesla to catch up. But it also means theres a Mars-size gap between Musks $25 trillion robot revolution and the hard work of actually engineering it. ROBOT DREAMS MEET HARD REALITY Here is the Optimus reality today: Production reportedly froze in mid-June when the bots overheating joints, limp wrists, and batteries that croaked before lunchtime forced a complete procurement pause. By then, only about 1,000 bots had rolled off the Fremont, California, pilot line, costing around $60,000 apiece to make. According to videos of the bots working, they were moving at less than half the speed of the humans they are meant to replace. Optimuss problems have prompted a redesign to improve the robots performance. Tesla, according to reports, is evaluating new providers of all its key failing components, a process that will further delay an already delayed schedule. According to AInvest, two soures in the Optimus supply chain claim that “Tesla had procured enough parts to produce 1,200 Optimus units and had manufactured close to 1,000. Though Musk had claimed the company would produce 5,000 units in 2025, according to these sources, With the suspension of parts procurement, this target is now largely unattainable. (The Information confirmed the report.) On his Q2 earnings call, Musk said that Tesla is now working on an Optimus 3 prototype. We are gonna retool a bunch of things, so its gonna probably be prototypes of Optimus 3 [at the] end of this year and then scale production next year, he said. The rosary of failures may explain why Optimus’s program chief, Milan Kovac, bolted in June. Kovac left Tesla abruptly, citing family reasons (“I want to make it clear that this is the only reason,” he insisted on social media). The project is now in the hands of Tesla’s Autopilot boss, Ashok Elluswamy. Some old-design Optimus robots are currently in Tesla factories doing limited jobs. The company has shown the robots performing specific tasks, like folding a T-shirt and moving batteries at glacial speeds. Musk also recently reposted a video of an Optimus serving popcorn at the new Tesla Diner in Hollywood, though the clip is speeded up, giving the impression that the robot functions at a normal pace. The Jetsons-esque diner, which houses a Supercharger station, is a smokescreen, detonated the day before the company’s Q2 results and meant to distract from yet another empty promise: Musk hasnt yet delivered batteries that load as fast as gas pumps, so hes now inviting drivers to fill up on pancakes and burgers while waiting for their cars to charge. The popcorn-serving Optimus, meanwhile, is a prop used by the company to distract fans and investors. A MAGNET-SIZE PROBLEM Optimuss problems run deep, starting with the rare-earth magnets it needs to power its motors. Without the magnets, theres no way to make robots that can move with the speed and precision of real humans. While Tesla hasnt disclosed the number of magnets the Optimus requires, analyst Luke Lango says it may use up to 8 pounds of magnets. (A typical humanoid robot needs more than 40 servo motors, and each of those requires up to 3.5 ounces of magnets.) Back in March, Musk blamed Optimuss manufacturing problems on the lack of rare-earth magnets. Beijing had canceled exports when Musk’s former best buddy declared a trade war against China. In June, Chinas Ministry of Commerce resumed issuing permits for rare-earth magnet exports, putting them on a short leash while cracking down on smuggling. But this is a problem that is not going to be solved anytime soon, if ever. As long as geopolitical tensions exist, no Western company can fully rely on Chinese magnets. [Image: Tesla] The U.S. government is trying to stop Chinese dominance by investing in MP Materials, an American company that just built a small magnet supply chain thats still in its embryonic state. To make the millions of magnets that Musk needs for Optimus to succeed at scale, Tesla would have to put itself at the front of the line, ahead of everyone from carmakers to gadget peddlers, including Apple (which itself bought into the MP Materials pipe dream this month). Such a supply chain will be very hard to build and could disintegrate at any time. DESIGNED TO FAIL? Even ifand that is a Starship-size ifTesla manages to secure a steady supply chain to scale up production to the levels that Musk needs, Optimus’s design may be doomed from the start. Tesla is chasing the hardest form factor in robotics, humanoids, without lidar, which means its robots will encounter the same issues that plague the company’s Full Self-Driving mode and Robotaxi. While Musk claims that lidar is for losers, the exclusive use of regular cameras has proven insufficient to understand the world around cars, leading to accidents. (From 2019 to 2023, Tesla’s Autopilot was involved in 736 crashes, including 17 fatal ones. And thats without counting the near-misses and car bumper accidents.) It will be the same with robots, which is why many of Tesla’s rivals, including startups like Unitree and AgiBot, are leaning on proven sensor stacks. And even then, the humanoid form factor may not be right in some settings. Chris Walti, Tesla’s first Optimus lead, who left in 2022 to found the non-humanoid robotics startup Mytra, recently argued that human-shaped robots are “the wrong option for factory work” because the human form “evolved to escape wolves and bears, rather than perform repetitive industrial tasks, making it a suboptimal system. A Tesla Optimus robot scoops popcorn and gestures at customers during the opening of the Tesla Diner in Hollywood on July 21, 2025. [Photo: Patrick T. Fallon/AFP/Getty Images] The reality today is that specialized, purpose-built automation consistently outperforms general-purpose humanoid robots in cost, reliability, and efficiency for industrial tasks. That makes Tesla’s approach both an expensive engineering exercise and one that may lack a viable business strategy. Unless Optimus mutates into something tougher, easier to make, and a lot cheaper (Unitrees model has a $16,000 price tag), its destined to remain a showroom tease for a long time. Apptroniks Cardenas is still bullish on humanoids, which he argues can one day be deployed to perform a multitude of tasks. (Most bots today are created for single purposes.) “My view is that the key thing for robotics to scale is versatility, he says, noting his belief that we will someday see humanoids everywhere in the world, both legged and wheeled. Investors seem to agree. Financing for the sector has been growing wildly, especially in China, where the humanoid robot industry is most advanced. There, total funding reached $4.4 billion as of July 2025, doubling the previous years high-water mark, according to data from ITjuzi, which tracks Chinas venture-capital market. On July 21, Chinese e-commerce giant JD.com unveiled investments in three Chinese robotics startups: Engine AI, LimX Dynamics, and Spirit AI. Meanwhile, Hangzhou-based Unitree reached unicorn status in June with a new funding round that valued it at more than $1.3 billion. Investors included Alibaba Group Holding and affiliate Ant Group; Tencent Holdings; China Mobile; carmaker Geely; and Jinqiu Capital, an investment firm founded by former ByteDance employees. Many of these Chinese companies are already lining up customers. Hong Kong-listed UBTech secured a $12.6 million purchase from state-owned car exporter MiEE (Shanghai) Automotive Technology, by far the largest deal in the humanoid industry. Unitree and AgiBot also struck deals with telecoms operator China Mobile, worth $6.4 million and $10.9 million, respectively. Unitree founder and CEO Wang Xingxing said the company’s annual revenue had surpassed $139.4 million. These deals are far from the trillions that Musk covets, but they are a clear signal that his company is behind. Three months ago, Musk promised an army of Optimus robots marching through Tesla factories by the end of the year. Looking at the current state of the project, his 100-million robot party is turning into the Fyre Festival of robotics.
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A leader recently told me about her dilemma: Her top performer of four years was asking about advancement opportunities, but with frozen budgets and no open positions, she felt powerless to help. Sound familiar? This scenario plays out everywhere. High performers hit their stride, ask “What’s next?” and managers default to the same answer: promotion. When that’s not possible, both sides feel stuck. But here’s what most leaders miss: When employees ask about advancement, they’re often asking for something deeperto be seen, valued, and recognized for their contributions. For decades, organizations have made promotion the primary symbol of professional success. It’s become our go-to way of saying “your work matters.” But this creates problems when budgets freeze: managers feel powerless, and employees feel invisible. The solution isn’t finding more money for promotions. It’s separating recognition from title changes. The S Curve of Growth Framework Instead of thinking about career development as a ladder (up or nothing), I encourage leaders to think about it as a learning curvespecifically, what I call the S Curve of Growth. Every skill, project, or responsibility follows this predictable S-shaped pattern: Launch Point: You’re at the base of the S, where learning feels slow but you’re building crucial foundations. Sweet Spot: The steep middle of the S, where you gain confidence and competence. Progress feels exponential. Mastery: The top plateau of the S, where you’ve reached high performance but growth levels off. The S Curve of Growth gives you and your employees a shared language for career conversations. Instead of “I need a promotion,” the conversation becomes “I’m reaching mastery on my project management S Curvewhat new curve should I start climbing?” Making This Work in Practice The most effective leaders using this approach: Make development ongoing, not annual. Replace yearly reviews with regular check-ins. Ask employees where they see themselves on different learning curves and what support they need to progress. Let employees drive their growth. Using the S Curve framework, stop dictating development paths. Ask: “Which of your S Curves do you want to accelerate? What new curve interests you?” Then create opportunities around their answers. Recognize progress publicly. Acknowledge when someone moves from struggling with a new system to training others on it. Call out when they take on a challenging project. Make their growth visible. The Bottom Line Growth doesn’t require promotions. A software developer can master new programming languages, mentor junior colleagues, or lead cross-functional projectsall without a title change. A marketing manager can expand into data analytics, build vendor relationships, or develop content strategy expertise. When you help employees map their growth across multiple S Curves, you solve two problems: they feel recognized and engaged, and you build a more versatile, capable team. Everyone wins, even when the org chart stays frozen. The question isn’t whether you can afford to promote everyone. It’s whether you can afford to not help them grow.
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When Lisa opened the resignation email from one of her top performers, she froze. As a regional sales VP at a fast-growing tech company, she prided herself on building a loyal, high-performing team. Shed recently adopted AI to streamline workflows and free up time for more strategic work. But in the exit interview, the employee shared something she hadnt expected: he felt unseen, disconnected, and undervalued. Some of her managers went even furtherusing AI-generated scripts for everything from difficult feedback to performance check-ins, and even praise. The messages felt impersonal, disconnected, and inauthentic. Employees took note. Even if productivity increased, effectiveness took a dive. One top performer began to disengage and soon gave notice. For busy leaders, automating conversations with team members can bring a sense of relief. Plug in a prompt. Let the machine guide the 1:1. However, when we offload the emotional labor of leadership, we risk eroding trust and connection, the very foundations that make teams thrive. AI can be a game changer for managers, but only when its used to amplify the human side of leadership. Too often, tools designed to save time end up weakening connection and culture. The opportunity isnt just to use AI. Its to use it well. Leading Effectively with AI With the proper guardrails, AI can expand a managers capacity, freeing them up to lead with more empathy, presence, and purpose. Think of AI as your backstage partner, not your stand-in. This risk is especially real for Gen Z professionals, many of whom launched their careers remotely and hadnt, for a time, seen relational leadership modeled in person. Todays managers play a critical role in helping them build the emotional fluency and resilience theyll need to lead. If we let AI handle the hard parts for them, like navigating conflict, building trust, or making tough calls, we miss the chance to develop the very capabilities theyll need when AI inevitably falls short or fails in a crisis. Through our work advising dozens of companies facing these dynamics, Kathryn, as an executive coach and keynote speaker, and Jenny, as an executive adviser and learning & development expert, have identified four strategies to help managers embrace AI in ways to make them more strategic, effective, and human-centered. 1. Know What to Automateand What Needs You As generative AI becomes more embedded in day-to-day workflows, leaders must guide their managers in determining which tasks should be automated and which demand human judgment and emotional intelligence. AI is well-suited for structured, repeatable tasks: generating first drafts of reports, summarizing meeting notes, preparing talking points, or reviewing written communication for tone and clarity. These applications reduce cognitive load and free up time for more meaningful work. But AI falls short in moments that require discernment, empathy, or trust-building. It cannot read between the lines of disengagement, coach a direct report whos questioning their fit on the team, or navigate a high-stakes conversation that touches on identity, like feeling excluded, overlooked, or underestimated. Delegating these responsibilities to a tool, even one that appears well-crafted, risks eroding a teams psychological safety and your leadership credibility. Use AI to clear space, not to take your place. We helped Lisas team draft a simple guide to distinguish what to automate and what to lead directly. What to Automate vs. Where to Show Up Use AI forShow up as a leader when..Summarizing reports or meeting notesDelivering difficult feedback or navigating emotionally charged conversationsReviewing written communication or organizing check-in agendasCoaching someone through a new role, challenge, or career inflection pointPreparing performance review draftsCelebrating wins or recognizing great workAnalyzing team feedback or surfacing key themes from engagement dataDiscussing concerns openly and cocreating solutions with the team Pro tip: Ask yourself: Am I using AI to enhance my leadership, or to avoid the parts that feel uncomfortable? 2. Show Your Team What Good AI Use Looks Like If you want AI to be used well, your team has to see what well looks like. That starts at the top. Managers take their cues from what leaders say and what they do. When Lisa began introducing AI into her teams workflows, she focused on implementation, but hadnt yet modeled how to use it thoughtfully. Her managers saw the tools being used for speed and scale, but not as an enabler for coaching, collaboration, or deeper thinking. In a recent coaching session, Lisa reflected that she had unintentionally created a culture of quiet experimentationwithout guidance, feedback, or clarity about what effective AI use looked like. We encouraged her to share her learning process with her direct reports: where she was experimenting, where shed made mistakes, and where she saw potential. She began demoing use cases with her team, inviting feedback, and normalizing discomfort. That shift, from quiet adoption to visible shared learning, sparked more thoughtful, responsible AI use across her team. Here are three ways you can do the same with your team: Share your learning journey. Be open about where youre experimenting and what youre still figuring out. Frame AI as an enabler. Position it as a way to work smarter and lead with greater focus and presence. Create psychological safety. Encourage your team to try, fail, and learn without fear of judgment. Even with great modeling, boundaries matter. Without clear guardrails, AI can quietly start doing the parts of leadership that should never be outsourced. 3. Draw the Line Between Support and Substitution When expectations are vague, AI can slowly shift from a helpful assistant to a leadership shortcut. Weve seen managers start by using it to draft talking points, only to lean on it later for delivering feedback or handling conflict. The tone may be polished, but the message often lacks the personalization and presence. People notice, and over time, trust erodes. Leaders must help their teams set clear boundaries. AI can help structure a message, but it shouldnt deliver it for you, especially when the moment calls for empathy, vulnerability, or moral courage. Research from MIT Sloan reinforces this distinction: while AI excels at structured, transactional tasks, its significantly less effective in emotionally nuanced situations, such as coaching, conflict resolution, or performance feedback. This is especially important for middle managers, who play a critical role in developing Gen Z professionals. Many early-career employees are still building confidence through live, relational interactions and will take their cues from what is modeled. When managers default to AI prompts, they not only weaken their own impact, but also risk sending the message that presence is optional. A useful rule of thumb: If a conversation could shape how someone feels about their value, performance, or belonging; it needs to be human-led. As AI tools become more capable, drawing the line between support and substitution will become one of the defining responsibilities of modern leadership. 4. Help Managers Use Saved Time Strategically One of AIs biggest benefits is time. But without a clear plan, that reclaimed time is often consumed by low-value meetings, inbox clutter, or busywork. The risk isnt just wasted hours. Its wasted opportunity. Help managers use their freed-up capacity with intention. Encourage them to reinvest it in what matters most: mentoring team members, building culture, thinking strategically, or developing their own leadership skills. These are the high-leverage activities that often fall by the wayside, but make the biggest difference over time. Ask yourself: Where is your time most valuable, and how are you protecting it? What high-impact conversations are you putting off, and why? In what ways could you invest this time to grow your team, or yourself? Pro tip: Use time by design, not by default. When time is freed, leaders have a choice: fill it by default, or use it by design. A Better Way to Lead with AI Lisa began modeling her own learning, setting clearer boundaries, and making space for reflection. She stopped simply asking what her managers were automating, and started asking why. That shift helped her to rebuild trust, reconnect with her team, and lead with focus. Ultimately, the most significant impact of AI wasnt speed. It was presence. AI will continue to shape how we lead, communicate, and make decisions. But leadership has never been just about efficiency. Its about discernment, trust, and showing up fully for the moments that matter. The best leaders wont only ask, How can I use AI? Theyll ask, How is my use of AI impacting the people I lead? The future of leadership isnt a choice between human or machine. Its humanyou bringing yourself to the job, with AI as your copilot.
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