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AI is no longer a fringe technology sitting on the sidelines of innovation. Its already influencing who gets hired, how diagnoses are made, what products we prioritize, and even which creative ideas rise to the top. But the most urgent leadership question isnt how fast we adopt AI. Its how deeply we integrate our humanity alongside it. As a leadership adviser, I have worked with executives navigating complex, high-stakes transformations. The leaders who thrive in this new landscape arent the ones chasing every shiny new tool, nor are they the ones retreating into nostalgic resistance. They are the ones who have learned to bring more of themselves into the room: their discernment, their emotional intelligence, and their narrative insight. Because when machines get smarter, humans must become better stewards of meaning. Beyond the Binary: A New Leadership Mandate We live in a world addicted to binaries: human or machine, analog or digital, automate or resist. The future wont be built in absolutes, according to a joint study by MIT Sloan Management Review and the Boston Consulting Group. Some 85% of companies who have implemented AI tools in their work report that it has brought them tangible business value. Yet fewer than 20% have redefined the roles and capabilities of their workforce alongside those tools. Technology is accelerating rapidly, while human systems are lagging behind. To close that gap, we need a new leadership lensone that doesnt just examine what AI can do but also asks what kind of world were creating with it. Introducing the HIT Framework for Human-Integrated Thinking AI doesnt need to replace human thinking; it should expand it. We dont need to out-compute machines, but we do need to out-human them. That starts with cultivating the very traits that make us irreplaceable: the ability to imagine, empathize, and make meaning. The HIT Framework, or Human-Integrated Thinking, is a call to action for modern leaders. It has three core capacities: 1. Humility. In the age of algorithms, humility becomes a superpower. It allows leaders to admit what they dont know, to question machine decisions, and to build cultures where challenging the output is not just allowed but expected. In my work with a multinational services firm, we introduced an AI Oversight Council composed of technical experts, ethicists, and frontline employees. Emotional intelligence was just as important as engineering know-how. The result? More inclusive innovation and stronger decision-making accountability. 2. Imagination. AI can extrapolate based on whats already known. But only humans can envision what has never existed. At Pixar, creators use AI tools to iterate on lighting and character rendering, but the heart of storytelling remains deeply human. In leadership development retreats I facilitate, we use metaphor, visual facilitation, and speculative prompts to prototype not just strategies, but alternative futures. Imagination isn’t soft; its structural. 3. Trust-building. AI might simulate empathy, but it cant build trust. That requires presence, consistency, and compassion. When AI is used in areas like hiring, product design, or healthcare, the human layer must ask: Whats the emotional impact of this decision? In one life sciences organization I supported, a new AI initiative stalled until leaders reframed the rollout as a human experience, not a technical one. We designed storytelling rituals that allowed employees to share how the changes affected their work and their personal identity. It wasnt about winning hearts and minds. It was about honoring them. The Cost of Ignoring the Human Factor Unchecked, AI systems will reinforce bias, scale inequity, and prioritize efficiency over dignity. A report from the World Economic Forum cites curiosity, emotional intelligence, and interdisciplinary collaboration as among the most critical competencies for the future of work. But how many org charts actually reward those traits? To lead in this era, executives must be able to toggle between data and emotion, logic and empathy, code and context. We need leaders who can read a spreadsheet and a room with equal fluency. The turning point in that same life sciences company didnt come from better code. It came when the executive team made a human shift. They stopped talking about AI in abstract terms and began reflecting on how it would change their relationships with employees, with patients, and with themselves. They invited facilitators, designers, and frontline voices into the quarterly business review. They stopped asking, How do we implement this? and started asking, Who do we want to become through this? That single question reoriented the conversation from compliance to transformation. The story of AI isnt finished, and its not being written by code alone. Its being coauthored by the choices we make every day: how we show up, what we measure, who we include, and what kind of intelligence we prioritize. AI will continue to evolve, but the leaders who rise with it wont just automate workflows; they will humanize systems, cultivate wisdom, and bring courage, imagination, and care to a world that desperately needs it. Because the real competitive edge isnt in how fast you adapt to technologyits in how fully you choose to remain human.
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E-Commerce
If you’re a designer looking for work, where should you live? That depends entirely on the kind of designer you are. Fast Company crunched the data to show you where the opportunities really are.
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E-Commerce
One stock recently impacted by a whirlwind of volatility is Blockthe fintech powerhouse behind Square, Cash App, Tidal Music, and more. The companys COO and CFO, Amrita Ahuja, shares how her team is using new AI tools to find opportunity amid disruption and reach customers left behind by traditional financial systems. Ahuja also shares lessons from the video game industry and discusses Gen Zs surprising approach to money management. This is an abridged transcript of an interview from Rapid Response, hosted by Robert Safian, former editor-in-chief of Fast Company. From the team behind the Masters of Scale podcast, Rapid Response features candid conversations with todays top business leaders navigating real-time challenges. Subscribe to Rapid Response wherever you get your podcasts to ensure you never miss an episode. As a leader, when youre looking at all of this volatilitythe tariffs, consumer sentiment’s been unclear, the stock market’s been all over the place. You guys had a huge one-day drop in early May, and it quickly bounced back. How do you make sense of all these external factors? Yeah, our focus is on what we can control. And ultimately, the thing that we are laser-focused on for our business is product velocity. How quickly can we start small with something, launch something for our customers, and then test and iterate and learn so that ultimately, that something that we’ve launched scales into an important product? I’ll give you an example. Cash App Borrow, which is a product where our customers can get access to a line of credit, often $100, $200, that bridges them from paycheck to paycheck. We know so many Americans are living paycheck to paycheck. That’s a product that we launched about three years ago and have now scaled to serve 9 million actives with $15 billion in credit supply to our customers in a span of a couple short years. The more we can be out testing and launching product at a pace, the more we know we are ultimately delivering value to our customers, and the right things will happen from a stock perspective. Block is a financial services provider. You have Square, the point-of-sale system; the digital wallet Cash App, which you mentioned, which competes with Venmo and Robinhood; and a bunch of others. Then you’ve got the buy-now, pay-later leader Afterpay. You chair Square Financial Services, which is Block’s chartered bank. But you’ve said that in the fintech world, Block is only a little bit finthat comparatively, it’s more tech. Can you explain what you mean by that? What we think is unique about us is our ability as a technology company to completely change innovation in the space, such that we can help solve systemic issues across credit, payments, commerce, and banking. What that means ultimately is we use technologies like AI and machine learning and data science, and we use these technologies in a unique way, in a way that’s different from a traditional bank. We are able to underwrite those who are often frankly forgotten by the traditional financial ecosystems. Our Square Loans product has almost triple the rate of women-owned businesses that we underwrite. Fifty-eight percent of our loans go to women-owned businesses versus 20% for the industry average. For that Cash App Borrow product I was talking about, 70% of those actives, the 9 million actives that we underwrote, fell below 580 as a FICO score. That’s considered a poor FICO score, and yet 97% of repayments are made on time. And this is because we have unique access to data and these technology and tools which can help us uniquely underwrite this often forgotten customer base. Yeah. I mean, creditsometimes it’s been blamed for financial excesses. But access to credit is also, as you say, an advantage that’s not available to everyone. Do you have a philosophy between those polesbetween risk and opportunity? Or is what you’re saying is that the tech you have allows you to avoid that risk? That’s right. Let’s start with how do the current systems work? It works using inferior data, frankly. It’s more limited data. It’s outdated. Sometimes it’s inaccurate. And it ignores things like someone’s cash flows, the stability of your income, your savings rate, how money moves through your accounts, or how you use alternative forms of creditlike buy now, pay later, which we have in our ecosystem through Afterpay. We have a lot of these signals for our 57 million monthly actives on the Cash App side and for the 4 million small businesses on the Square side, and those, frankly, billions of transaction data points that we have on any given day paired with new technologies. And we intend to continue to be on the forefront of AI, machine learning, and data science to be able to empower more people into the economy. The combination of the superior data and the technologies is what we believe ultimately helps expand access. You have a financial background, but not in the financial services industry. Before Block, you were a video game developer at Activision. Are financial businesses and video games similar? Are there things that are similar about them? There are. There actually are some things that are similar, I will say. There are many things that are unique to each industry. Each industry is incredibly complex. You find that when big technology companies try to do gaming. They’ve taken over the world in many different ways, but they can’t always crack the nut on putting out a great game. Similarly, some of the largest technology companies have dabbled in fintech but haven’t been able to go as deep, so they’re both very nuanced and complex industries. I would say another similarity is that design really matters. Industrial design, the design of products, the interface of products, is absolutely mission-critical to a great game, and it’s absolutely mission-critical to the simplicity and accessibility of our products, be it on Square or Cash App. And then maybe the third thing that I would say is that when I was in gaming, at least the business models were rapidly changing from an intermediary distribution mechanism, like releasing a game once and then selling it through a retailer, to an always-on, direct-to-consumer connection. And similarly with banking, people don’t want to bank from 9 to 5, six days a week. They want 24/7 access to their money and the ability to, again, grow their financial livelihood, move their money around seamlessly. So, some similarities are there in that shift to an intermediary model or a slower model to an always-on, direct-to-consumer connection. Part of your target audience or your target customer base at Block are Gen Z folks. Did you learn things at Activision about Gen Z that has been useful? Are there things that businesses misunderstand about younger generations still? What we’ve learned is that Gen Z, millennial customers, aren’t going to do things the way their parents did. Some of our stats show that 63% of Gen Z customers have moved away from traditional credit cards, and over 80% are skeptical of them. Which means they’re not using a credit card to manage expenses; they’re using a debit card, but then layering on on a trnsaction-by-transaction basis. Or again, using tools like buy now, pay later, or Cash App Borrow, the means in which they’re managing their consistent cash flows. So that’s an example of how things are changing, and you’ve got to get up to speed with how the next generation of customers expects to manage their money.
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E-Commerce
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