Comics artists tell us how they approached the unique character dynamics.

For nearly two decades, the Marvel Cinematic Universe has been so prevalent in pop culture that their entire vibe has infected almost every facet of the creative output of Marvel as a larger comic-book and multimedia company. Projects like Crystal Dy

One stock recently impacted by a whirlwind of volatility is Block—the fintech powerhouse behind Square, Cash App, Tidal Music, and more. The company’s 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 Z’s 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 today’s 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 you’re looking at all of this volatility—the 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 fin—that 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, credit—sometimes 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 poles—between 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 credit—like 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 transaction-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.

In Brief Posted: 11:46 AM PDT · June 14, 2025 Image Credits:Matthias Balk/picture alliance / Getty Images Google reportedly plans to cut ties with Scale AI Meta’s big investment in Scale AI may be giving some of the startup’s customers pause. Reuters reports that Google had planned to pay Scale $200 million this year but is now having conversations with its competitors and planning to cut ties. Microsoft is also reportedly looking to pull back, and OpenAI supposedly made a similar decision months ago, although its CFO said the company will continue working with Scale as one of many vendors. Scale’s customers include self-driving car companies and the U.S. government, but Reuters says its biggest clients are generative AI companies seeking access to workers with specialized knowledge who can annotate data to train models. Google declined to comment on the report. A Scale spokesperson declined to comment on the company’s relationship with Google, but he told TechCrunch that Scale’s business remains strong, and that it will continue to operate as an independent company that safeguards its customers’ data. Earlier reports suggest that Meta invested $14.3 billion in Scale for a 49% stake in the company, with Scale CEO Alexandr Wang joining Meta to lead the company’s efforts to develop “superintelligence.” Topics AI, Google, Meta, Scale AI

Photo Credit: ispace A delay in rangefinder data prevented timely deceleration, causing a hard landing on the lunar surface Highlights Resilience lander lost signal one minute before scheduled moon touchdown Delayed laser rangefinder data caused failure in the landing speed adjust ispace lunar lander crashes on final descent, marking its second mission Advertisement A Japanese spacecraft attempting to achieve the country's first private moon landing instead crashed on the lunar surface, according to mission officials. The Resilience lander, developed by Tokyo-based ispace, lost communication one minute and 45 seconds before its scheduled soft touchdown on June 5 at 3:17 p.m. EDT. The descent was targeted for the Mare Frigoris region on the Moon's near side. ispace had its second problem on the moon when its laser rangefinder broke, which is a big improvement over its prior failure in April 2023.Japan's Resilience Lunar Lander Crashes in Hard Landing, ispace Vows to Learn and RebuildAs per an official statement from ispace, telemetry from Resilience revealed that the rangefinder's delayed data caused a failure in adjusting landing speed. This likely led to a “hard landing”, suggesting the spacecraft hit the moon's surface too fast to survive or complete its mission. The lander, carrying five payloads, such as a Tenacious rover and scientific instruments, crashed with no survivors. The firm's CEO, Takeshi Hakamada, apologised and remarked that the company would use the mission to learn about future missions.The Hakuto-R Mission 2 team launched a 7.5-foot-tall, 2,200-pound Resilience lander into space aboard a SpaceX Falcon 9 rocket in early May. But with a perfect orbit, the lander smashed into the lunar surface at 192 metres – an echo of Mission 1's mission failure in 2023, which crashed because a fault in one of its altitude sensors was not corrected.The Resilience crash adds to private attempts to explore the moon, including the unsuccessful Beresheet and Peregrine missions. Crewed landings such as Odysseus and Blue Ghost prove that dreams of commercial space are possible. The second Hakuto-R mission was a private attempt and a blow to Japan's space ambitions. Failure has not stopped ispace development for Mission 3 and Mission 4 with its larger Apex 1.0 lander.Hakamada mentioned that the priority for the team was now to find out what caused the crash. “Supporters are disappointed,” CFO Nozaki says, “but ispace has yet to cover the moon, and the road does not end, even if Mission 2 didn't go as planned.” For the latest tech news and reviews, follow Gadgets 360 on X, Facebook, WhatsApp, Threads and Google News. For the latest videos on gadgets and tech, subscribe to our YouTube channel. If you want to know everything about top influencers, follow our in-house Who'sThat360 on Instagram and YouTube. Further reading: ispace, Hakuto-R, moon landing, Resilience, lunar exploration Gadgets 360 Staff The resident bot. If you email me, a human will respond. More Related Stories

John Edwards, Technology Journalist & AuthorJune 5, 20254 Min ReadSailGP Australia, USA, and Great Britain racing on San Francisco Bay, CaliforniaDannaphotos via Alamy StockWarren Jones is CTO at SailGP, the organizer of what he describes as the world's most exciting race on water. The event features high-tech F50 boats that speed across the waves at 100 kilometers-per-hour (62 miles-per-hour).  Working in cooperation with Oracle, Jones focuses on innovative solutions for remote broadcast production, data management and distribution, and a newly introduced fan engagement platform. He also leads the team that has won an IBC Innovation Awards for its ambitious and ground-breaking remote production strategy. Among the races Jones organizes is the Rolex SailGP Championship, a global competition featuring national teams battling each other in identical high-tech, high-speed 50-foot foiling catamarans at celebrated venues around the world. The event attracts the sport's top athletes, with national pride, personal glory, and bonus prize money of $12.8 million at stake. Jones also supports event and office infrastructures in London and New York, and at each of the global grand prix events over the course of the season. Prior to joining SailGP, he was IT leader at the America's Cup Event Authority and Oracle Racing. In an online interview, Jones discusses the challenges he faces in bringing reliable data services to event vessels, as well as onshore officials and fans. Related:Warren JonesWhat's the biggest challenge you've faced during your tenure? One of the biggest challenges I faced was ensuring real-time data transmission from our high-performance F50 foiling catamarans to teams, broadcasters, and fans worldwide. SailGP relies heavily on technology to deliver high-speed racing insights, but ensuring seamless connectivity across different venues with variable conditions was a significant hurdle. What caused the problem? The challenge arose due to a combination of factors. The high speeds and dynamic nature of the boats made data capture and transmission difficult. Varying network infrastructure at different race locations created connectivity issues. The need to process and visualize massive amounts of data in real time placed immense pressure on our systems. How did you resolve the problem? We tackled the issue by working with T-Mobile and Ericsson in a robust and adaptive telemetry system capable of transmitting data with minimal latency over 5G. Deploying custom-built race management software that could process and distribute data efficiently [was also important]. Working closely with our global partner Oracle, we optimized Cloud Compute with the Oracle Cloud.  Related:What would have happened if the problem wasn't quickly resolved? Spectator experience would have suffered. Teams rely on real-time analytics for performance optimization, and broadcasters need accurate telemetry for storytelling. A failure here could have resulted in delays, miscommunication, and a diminished fan experience. How long did it take to resolve the problem? It was an ongoing challenge that required continuous innovation. The initial solution took several months to implement, but we’ve refined and improved it over multiple seasons as technology advances and new challenges emerge. Who supported you during this challenge? This was a team effort -- with our partners Oracle, T-Mobile, and Ericsson with our in-house engineers, data scientists, and IT specialists all working closely. The support from SailGP's leadership was also crucial in securing the necessary resources. Did anyone let you down? Rather than seeing it as being let down, I'd say there were unexpected challenges with some technology providers who underestimated the complexity of what we needed. However, we adapted by seeking alternative solutions and working collaboratively to overcome the hurdles. What advice do you have for other leaders who may face a similar challenge? Related:Embrace adaptability. No matter how well you plan, unforeseen challenges will arise, so build flexible solutions. Leverage partnerships. Collaborate with the best in the industry to ensure you have the expertise needed. Stay ahead of technology trends. The landscape is constantly evolving; being proactive rather than reactive is key. Prioritize resilience. Build redundancy into critical systems to ensure continuity even in the face of disruptions. Is there anything else you would like to add? SailGP is as much a technology company as it is a sports league. The intersection of innovation and competition drives us forward and solving challenges like these is what makes this role both demanding and incredibly rewarding. About the AuthorJohn EdwardsTechnology Journalist & AuthorJohn Edwards is a veteran business technology journalist. His work has appeared in The New York Times, The Washington Post, and numerous business and technology publications, including Computerworld, CFO Magazine, IBM Data Management Magazine, RFID Journal, and Electronic Design. He has also written columns for The Economist's Business Intelligence Unit and PricewaterhouseCoopers' Communications Direct. John has authored several books on business technology topics. His work began appearing online as early as 1983. Throughout the 1980s and 90s, he wrote daily news and feature articles for both the CompuServe and Prodigy online services. His "Behind the Screens" commentaries made him the world's first known professional blogger.See more from John EdwardsWebinarsMore WebinarsReportsMore ReportsNever Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.SIGN-UPYou May Also Like

For the past two years, it’s been a ghost in the machine of American tech. Between 2022 and today, a little-noticed tweak to the U.S. tax code has quietly rewired the financial logic of how American companies invest in research and development. Outside of CFO and accounting circles, almost no one knew it existed. “I work on these tax write-offs and still hadn’t heard about this,” a chief operating officer at a private-equity-backed tech company told Quartz. “It’s just been so weirdly silent.”AdvertisementStill, the delayed change to a decades-old tax provision — buried deep in the 2017 tax law — has contributed to the loss of hundreds of thousands of high-paying, white-collar jobs. That’s the picture that emerges from a review of corporate filings, public financial data, analysis of timelines, and interviews with industry insiders. One accountant, working in-house at a tech company, described it as a “niche issue with broad impact,” echoing sentiments from venture capital investors also interviewed for this article. Some spoke on condition of anonymity to discuss sensitive political matters.Since the start of 2023, more than half-a-million tech workers have been laid off, according to industry tallies. Headlines have blamed over-hiring during the pandemic and, more recently, AI. But beneath the surface was a hidden accelerant: a change to what’s known as Section 174 that helped gut in-house software and product development teams everywhere from tech giants such as Microsoft (MSFT) and Meta (META) to much smaller, private, direct-to-consumer and other internet-first companies.Now, as a bipartisan effort to repeal the Section 174 change moves through Congress, bigger questions are surfacing: How did a single line in the tax code help trigger a tsunami of mass layoffs? And why did no one see it coming? For almost 70 years, American companies could deduct 100% of qualified research and development spending in the year they incurred the costs. Salaries, software, contractor payments — if it contributed to creating or improving a product, it came off the top of a firm’s taxable income.AdvertisementThe deduction was guaranteed by Section 174 of the IRS Code of 1954, and under the provision, R&D flourished in the U.S.Microsoft was founded in 1975. Apple (AAPL) launched its first computer in 1976. Google (GOOGL) incorporated in 1998. Facebook opened to the general public in 2006. All these companies, now among the most valuable in the world, developed their earliest products — programming tools, hardware, search engines — under a tax system that rewarded building now, not later.The subsequent rise of smartphones, cloud computing, and mobile apps also happened in an America where companies could immediately write off their investments in engineering, infrastructure, and experimentation. It was a baseline assumption — innovation and risk-taking subsidized by the tax code — that shaped how founders operated and how investors made decisions.In turn, tech companies largely built their products in the U.S. AdvertisementMicrosoft’s operating systems were coded in Washington state. Apple’s early hardware and software teams were in California. Google’s search engine was born at Stanford and scaled from Mountain View. Facebook’s entire social architecture was developed in Menlo Park. The deduction directly incentivized keeping R&D close to home, rewarding companies for investing in American workers, engineers, and infrastructure.That’s what makes the politics of Section 174 so revealing. For all the rhetoric about bringing jobs back and making things in America, the first Trump administration’s major tax bill arguably helped accomplish the opposite.When Congress passed the Tax Cuts and Jobs Act (TCJA), the signature legislative achievement of President Donald Trump’s first term, it slashed the corporate tax rate from 35% to 21% — a massive revenue loss on paper for the federal government.To make the 2017 bill comply with Senate budget rules, lawmakers needed to offset the cost. So they added future tax hikes that wouldn’t kick in right away, wouldn’t provoke immediate backlash from businesses, and could, in theory, be quietly repealed later.AdvertisementThe delayed change to Section 174 — from immediate expensing of R&D to mandatory amortization, meaning that companies must spread the deduction out in smaller chunks over five or even 15-year periods — was that kind of provision. It didn’t start affecting the budget until 2022, but it helped the TCJA appear “deficit neutral” over the 10-year window used for legislative scoring.The delay wasn’t a technical necessity. It was a political tactic. Such moves are common in tax legislation. Phase-ins and delayed provisions let lawmakers game how the Congressional Budget Office (CBO) — Congress’ nonpartisan analyst of how bills impact budgets and deficits — scores legislation, pushing costs or revenue losses outside official forecasting windows.And so, on schedule in 2022, the change to Section 174 went into effect. Companies filed their 2022 tax returns under the new rules in early 2023. And suddenly, R&D wasn’t a full, immediate write-off anymore. The tax benefits of salaries for engineers, product and project managers, data scientists, and even some user experience and marketing staff — all of which had previously reduced taxable income in year one — now had to be spread out over five- or 15-year periods. To understand the impact, imagine a personal tax code change that allowed you to deduct 100% of your biggest source of expenses, and that becoming a 20% deduction. For cash-strapped companies, especially those not yet profitable, the result was a painful tax bill just as venture funding dried up and interest rates soared.AdvertisementSalesforce office buildings in San Francisco.Photo: Jason Henry/Bloomberg (Getty Images)It’s no coincidence that Meta announced its “Year of Efficiency” immediately after the Section 174 change took effect. Ditto Microsoft laying off 10,000 employees in January 2023 despite strong earnings, or Google parent Alphabet cutting 12,000 jobs around the same time.Amazon (AMZN) also laid off almost 30,000 people, with cuts focused not just on logistics but on Alexa and internal cloud tools — precisely the kinds of projects that would have once qualified as immediately deductible R&D. Salesforce (CRM) eliminated 10% of its staff, or 8,000 people, including entire product teams.In public, companies blamed bloat and AI. But inside boardrooms, spreadsheets were telling a quieter story. And MD&A notes — management’s notes on the numbers — buried deep in 10-K filings recorded the change, too. R&D had become more expensive to carry. Headcount, the leading R&D expense across the tech industry, was the easiest thing to cut.AdvertisementIn its 2023 annual report, Meta described salaries as its single biggest R&D expense. Between the first and second years that the Section 174 change began affecting tax returns, Meta cut its total workforce by almost 25%. Over the same period, Microsoft reduced its global headcount by about 7%, with cuts concentrated in product-facing, engineering-heavy roles.Smaller companies without the fortress-like balance sheets of Big Tech have arguably been hit even harder. Twilio (TWLO) slashed 22% of its workforce in 2023 alone. Shopify (SHOP) (headquartered in Canada but with much of its R&D teams in the U.S.) cut almost 30% of staff in 2022 and 2023. Coinbase (COIN) reduced headcount by 36% across a pair of brutal restructuring waves.Since going into effect, the provision has hit at the very heart of America’s economic growth engine: the tech sector.By market cap, tech giants dominate the S&P 500, with the “Magnificent 7” alone accounting for more than a third of the index’s total value. Workforce numbers tell a similar story, with tech employing millions of Americans directly and supporting the employment of tens of millions more. As measured by GDP, capital-T tech contributes about 10% of national output.AdvertisementIt’s not just that tech layoffs were large, it’s that they were massively disproportionate. Across the broader U.S. economy, job cuts hovered around in low single digits across most sectors. But in tech, entire divisions vanished, with a whopping 60% jump in layoffs between 2022 and 2023. Some cuts reflected real inefficiencies — a response to over-hiring during the zero-interest rate boom. At the same time, many of the roles eliminated were in R&D, product, and engineering, precisely the kind of functions that had once benefitted from generous tax treatment under Section 174.Throughout the 2010s, a broad swath of startups, direct-to-consumer brands, and internet-first firms — basically every company you recognize from Instagram or Facebook ads — built their growth models around a kind of engineered break-even.The tax code allowed them to spend aggressively on product and engineering, then write it all off as R&D, keeping their taxable income close to zero by design. It worked because taxable income and actual cash flow were often notGAAP accounting practices. Basically, as long as spending counted as R&D, companies could report losses to investors while owing almost nothing to the IRS.But the Section 174 change broke that model. Once those same expenses had to be spread out, or amortized, over multiple years, the tax shield vanished. Companies that were still burning cash suddenly looked profitable on paper, triggering real tax bills on imaginary gains.AdvertisementThe logic that once fueled a generation of digital-first growth collapsed overnight.So it wasn’t just tech experiencing effects. From 1954 until 2022, the U.S. tax code had encouraged businesses of all stripes to behave like tech companies. From retail to logistics, healthcare to media, if firms built internal tools, customized a software stack, or invested in business intelligence and data-driven product development, they could expense those costs. The write-off incentivized in-house builds and fast growth well outside the capital-T tech sector. This lines up with OECD research showing that immediate deductions foster innovation more than spread-out ones.And American companies ran with that logic. According to government data, U.S. businesses reported about $500 billion in R&D expenditures in 2019 alone, and almost half of that came from industries outside traditional tech. The Bureau of Economic Analysis estimates that this sector, the broader digital economy, accounts for another 10% of GDP.Add that to core tech’s contribution, and the Section 174 shift has likely touched at least 20% of the U.S. economy.AdvertisementThe result? A tax policy aimed at raising short-term revenue effectively hid a time bomb inside the growth engines of thousands of companies. And when it detonated, it kneecapped the incentive for hiring American engineers or investing in American-made tech and digital products.It made building tech companies in America look irrational on a spreadsheet.A bipartisan group of lawmakers is pushing to repeal the Section 174 change, with business groups, CFOs, crypto executives, and venture capitalists lobbying hard for retroactive relief. But the politics are messy. Fixing 174 would mean handing a tax break to the same companies many voters in both parties see as symbols of corporate excess. Any repeal would also come too late for the hundreds of thousands of workers already laid off.And of course, the losses don’t stop at Meta’s or Google’s campus gates. They ripple out. When high-paid tech workers disappear, so do the lunch orders. The house tours. The contract gigs. The spending habits that sustain entire urban economies and thousands of other jobs. Sandwich artists. Rideshare drivers. Realtors. Personal trainers. House cleaners. In tech-heavy cities, the fallout runs deep — and it’s still unfolding.AdvertisementWashington is now poised to pass a second Trump tax bill — one packed with more obscure provisions, more delayed impacts, more quiet redistribution. And it comes as analysts are only just beginning to understand the real-world effects of the last round.The Section 174 change “significantly increased the tax burden on companies investing in innovation, potentially stifling economic growth and reducing the United States’ competitiveness on the global stage,” according to the tax consulting firm KBKG. Whether the U.S. will reverse course — or simply adapt to a new normal — remains to be seen.

John Edwards, Technology Journalist & AuthorJune 4, 20254 Min ReadRancz Andrei via Alamy Stock PhotoIt may be hard to believe, but some senior executives actually believe that AI's arrival isn't a ground-shaking event. These individuals tend to be convinced that while AI may be a useful tool in certain situations, it's not going to change business in any truly meaningful way. Call them skeptics or call them realists, but such individuals really do exist, and it's the enterprise's CIOs and other IT leaders who need to gently guide them into reality. AI adoption tends to fall into three mindsets: early adopters who recognize its benefits, skeptics who fear its risks, and a large middle group -- those who are curious, but uncertain, observes Dave McQuarrie, HP's chief commercial officer in an online interview. "The key to closing the AI adoption gap lies in engaging this middle group, equipping them with knowledge, and guiding them through practical implementation." Effective Approaches The most important move is simply getting started. Establish a group of advocates in your company to serve as your early AI adopters, McQuarrie says. "Pick two or three processes to completely automate rather than casting a wide net, and use these as case studies to learn from," he advises. "By beginning with a subset of users, leaders can develop a solid foundation as they roll out the tool more widely across their business." Related:Start small, gather data, and present your use case, demonstrating how AI can support you and your colleagues to do your jobs better and faster, recommends Nicola Cain, CEO and principal consultant at Handley Gill Limited, a UK-based legal, regulatory and compliance consultancy. "This could be by analyzing customer interactions to demonstrate how the introduction of a chatbot to give customers prompt answers to easily addressed questions ... or showing how vast volumes of network log data could be analyzed by AI to identify potentially malign incidents that warrant further investigation," she says in an email interview. Changing Mindsets Question the skeptical leader about their biggest business bottleneck, suggests Jeff Mains, CEO of business consulting firm Champion Leadership Group. "Whether it’s slow decision-making, inconsistent customer experiences, or operational inefficiencies, there's a strategic AI-driven solution for nearly every major business challenge," he explains in an online interview. "The key is showing leaders how AI directly solves their most pressing problems today." When dealing with a reluctant executive, start by identifying an AI use case, Cain says. "AI functionality already performs strongly in areas like forecasting, recognition, event detection, personalization, interaction support, recommendations, and goal-driven optimization," she states. "Good business areas to identify a potential use case could therefore be in finance, customer service, marketing, cyber security, or stock control." Related:Strengthening Your Case Executives respond to proof, not promises, Mains says. "Instead of leading with research reports, I’ve found that real, industry-specific case studies are far more impactful," he observes. "If a direct competitor has successfully integrated AI into sales, marketing, or operations, use that example, because it creates urgency." Instead of just citing AI-driven efficiency gains, Mains recommends framing AI as a way to free-up leadership to focus on high-level strategy rather than day-to-day operations. Instead of trying to pitch AI in broad terms, Mains advises aligning the technology to the company's stated goals. "If the company is struggling with customer retention, talk about how AI can improve personalization," he suggests. "If operational inefficiencies are a problem, highlight AI-driven automation." The moment AI is framed as a business enabler rather than a technology trend, the conversation shifts from resistance to curiosity. Related:When All Else Fails If leadership refuses to embrace AI, it’s important to document the cost of inaction, Mains says. "Keep track of inefficiencies, missed opportunities, and competitor advancements," he recommends. Sometimes, leadership only shifts when management’s view of the risks of staying stagnant outweigh the risks of change. "If a company refuses to innovate despite clear benefits, that’s a red flag for long-term growth." Final Thoughts For enterprises that have so far done little or nothing in the way of AI deployment, the technology may appear optional, McQuarrie observes. Yet soon, operating without AI will become as unthinkable as running a business without the internet. Enterprise leaders who delay AI adoption risk falling behind the competition. "The best approach is to embrace a mindset of humility and curiosity -- actively seek out knowledge, ask questions, and learn from peers who are already seeing AI’s impact," he says. "To stay competitive in this rapidly evolving landscape, leaders should start now." The best companies aren't just using AI to improve; they're using the technology to redefine how they do business, Mains says. Leaders who recognize AI as a business accelerator will be the ones leading their industries in the next decade. "Those who hesitate? They’ll be playing catch-up." he concludes. About the AuthorJohn EdwardsTechnology Journalist & AuthorJohn Edwards is a veteran business technology journalist. His work has appeared in The New York Times, The Washington Post, and numerous business and technology publications, including Computerworld, CFO Magazine, IBM Data Management Magazine, RFID Journal, and Electronic Design. He has also written columns for The Economist's Business Intelligence Unit and PricewaterhouseCoopers' Communications Direct. John has authored several books on business technology topics. His work began appearing online as early as 1983. Throughout the 1980s and 90s, he wrote daily news and feature articles for both the CompuServe and Prodigy online services. His "Behind the Screens" commentaries made him the world's first known professional blogger.See more from John EdwardsWebinarsMore WebinarsReportsMore ReportsNever Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.SIGN-UPYou May Also Like