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The annual NFL tradition of firing the head coach as the season ends continues. This year, 10 top coaches got the axe, a staggering 31% of all NFL coaches. And they include football legends like John Harbaugh, after 18 seasons with the Baltimore Ravens, and Sean McDermott, who took the Buffalo Bills to the playoffs in eight out of nine seasons. Firing the head coachjust like firing the CEO in the business worldis the easy answer, and it looks good in the media: decisive, forward-looking, taking action. But, most times, this act alone falls short of fixing the problems that contributed to an organizations failures. PART OF A SYSTEM In reality, the CEO is part of a system, and its the system that matters. You can have a B player CEO with a great team and board and deliver significant performance and culture gains. Alternatively, you can have an A player CEO with a weak board and team and fail spectacularly. If you only focus on fixing the CEO, youre not focused on the right problem and cant get to the right solution. Yet CEO turnover is at its highest level in more than a decade, according to a 2026 Spencer Stuart study reported in The Wall Street Journal. In fact, approximately one in nine CEOs were replaced in 1,500 large companies in 2025, including the CEOs of Disney, HP, Lululemon, PayPal and Procter & Gamble. Disney illustrates the downside of this. Just ask Bob Chapek. Sure, he had a rough three years as CEO of Walt Disney Co. before the board summarily fired him and brought back his predecessor, Bob Iger. Disney stock, at $125 a share when Chapek took over in February 2020, had fallen almost 40% to $90 by the time he got the axe on November 20, 2022. Iger arguably is one of the best CEOs in decades, and he rebuilt the company with incredibly successful acquisitions (Pixar, Marvel Entertainment, Star Wars, the Muppets). But his two years back at the top were less than stellar: Disney shares are up 17% since he took over, while the S&P media and entertainment index rose 99% in the same period. Obviously, Chapek alone wasnt the problem, just as Iger alone wasnt the solution. Rarely is the executive at the very top solely responsible for what went wrong. It owes to a multitude of weaknesses: illogical organization models, conflicting agendas, turf battles, reporting structures that dont align with the company strategy, and communication lapses. There is rarely an objective assessment done ensuring the board is aligned with a new CEO or a new market entry for what success looks like, and the structures and talent required to achieve that success. This is especially true in the unforgiving and bottom-line-obsessed world of private equity (PE). The biggest myth in PE (and pro football) is that if you get the CEO right, and you get the strategy right, you will get the numbers you want on the scoreboard. Every CEO is encumbered by their surroundings. A PE board is possibly 50% of the CEOs success or failure, and in my experience, a lack of alignment between how each part defines success is a root issue. Leaders of PE-funded businesses must also operate under very compressed timeframes that leave little room for exiling and replacing a CEO. By the time the CEO has been exiled, it can be even harderor too lateto drive a successful outcome. A TEAM APPROACH This is why, again, even B player CEOs with strong teams and supportive boards find success, while A-rated commanders often falter with the wrong organization structure and fractured boards. The CEO is but one part of a whole system that must play well together, including the board, key team members, business partners, core customers, and suppliers. Yet highly intelligent and competitive people often miss their biggest and most controllable opportunity to ensure their CEO is positioned for success. That is to better manage their own decision-making, accountability, and communication as board members and teammates and ensure the organization is designed for success. Alice Mann is founder and CEO of Mann Partners.
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E-Commerce
AI is helping teams build software and tools faster than everbut that doesn’t mean we’re building smarter. I’ve seen entire prototypes spin up in a day, thanks to AI coding assistants. But when you ask how they were built, or whether they’re secure, you get a lot of blank stares. That’s the gap emerging now, between what’s possible with AI, and what’s actually ready to scale. What looks like progress can quickly become a liability. Especially when no one’s quite sure how the thing was built in the first place. Before you go all-in on AI-assisted coding, check these five fault lines: 1. You can’t govern what you can’t see. Perhaps the most overlooked risk of AI-assisted coding isn’t technical, its operational. In the rush to deploy AI tools, many companies have unintentionally created a layer of “shadow engineering.” Developers use these tools without official policies or visibility, leaving leaders in the dark about what’s being built and how. As Mark Curphey, cofounder of Crash Override, told me: “AI is accelerating everything. But without insight into what’s being built, by whom, or where it’s going, you’re scaling chaos with no controls.” Thats why visibility cant be an afterthought; its what makes both governance and acceleration possible. Platforms like Crash Override are designed to surface how AI is being used across the engineering org, offering a real-time view into whats being generated, where its going, and whether its introducing risk or value. And that visibility doesnt exist in isolation. Tools like Jellyfish help connect development work to business goals, while Codacy monitors code quality. But none of these tools can do their job well if you dont know whats happening under the hood. Visibility isnt about surveillance, it’s about building on a solid foundation. 2. Productivity is up. So is your risk exposure. A 2025 study Apiiro, an application security firm, found that AI-assisted developers are shipping 3 to 4 times more code with GenAI tools. But they’re also generating 10 times more security risks. These weren’t just syntax errors. The increase included hidden access risks, insecure code patterns, exposed credentials, and deep architectural flawsissues far more complex and costly to resolve over time. 3. AI-generated code is a potential legal risk. Because AI coding tools are trained on vast libraries of public code, they can generate snippets governed by restrictive open-source licenses. That raises important compliance questions, especially with licenses like GPL or AGPL, which could, in theory, require companies to open-source any software built on top of that output. But its worth clarifying: No company has been sued (yet) for using AI-generated code. The lawsuits weve seen (like the GitHub Copilot class action) have targeted the AI toolmakers, not the teams using their output. And the majority of GitHubs claims were ultimately thrown out. Still, this is a fast-evolving area with real implications. Auditboards 2025 study found that 82% of enterprise organizations were already deploying AI tools, but only 25% report having any sort of official governance in place. That disconnect may not be a courtroom issue today, but its a visibility and audit issue that leaders cant afford to ignore. 4. Speed is great, until only one person knows how it works. The “bus factor” has long described a worst-case scenario: What happens if the one person who knows how your software works suddenly disappears? “Powered by AI, an average developer becomes 100 times more productive. A superstar becomes 1,000 times,” Curphey noted. “Now imagine two of them are pushing all of that code into production. If they disappear, the company’s in serious trouble.” But the goal isnt zero riskits coverage. Just like test cases help ensure software is resilient, teams need to ensure knowledge and ownership are distributed. That includes understanding whos building what, where the AI is involved, and how those systems will be maintained over time. Ironically, GenAI can help with this. It can surface patterns, identify gaps, and map ownership in ways traditional tooling cant. More than just a productivity boost, it can be a tool for reducing fragility across your team and your codebase. 5. It’s easy to end up with “software slop.” Good, scalable AI-assisted code starts with the prompt. AI will generate exactly what you ask for. But if you don’t fully understand the technical constraints, or the risks you’re overlooking, it might give you code that looks good but has critical flaws in security or performance under the hood. You certainly don’t have to be a developer to use these tools well. But you do need to know what you don’t know, and how to account for it. As Curphey notes in a company blog post, If you wouldnt accept that level of vagueness from a junior engineer, why would you accept it from yourself when prompting? Otherwise, you’re moving fast and creating a kind of digital brain rot: systems that degrade over time because no one really understands how they were built. FROM VIBE CHECK TO REALITY CHECK The takeaway: AI may accelerate output, but it also accelerates risk. Without rigorous review and governance, you may be shipping code that functions, but isn’t structurally sound. So while AI is changing how software gets built, we need to be sure we’re building on a solid foundation. It’s no longer enough to move fast or ship often. As leaders, we need to understand how AI is being used inside our teams, and whether the things getting built are actually stable, scalable, and secure. Because if you don’t know what your team is using AI to build today, you may not like what you’re shipping tomorrow. Lisa Larson-Kelley is founder and CEO of Quantious.
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E-Commerce
Indian Prime Minister Narendra Modi on Thursday pitched India as a central player in the global artificial intelligence ecosystem, saying the country aims to build technology at home while deploying it worldwide.“Design and develop in India. Deliver to the world. Deliver to humanity,” Modi told a gathering of some world leaders, technology executives and policymakers at the India AI Impact Summit in New Delhi.Modi’s remarks came as India one of the fastest-growing digital markets seeks to leverage its experience in building large-scale digital public infrastructure and to present itself as a cost-effective hub for AI innovation.The summit was also addressed by French President Emmanuel Macron, Google CEO Sundar Pichai and U.N. Secretary-General António Guterres, who called for a $3 billion fund to help poorer countries build basic AI capacity, including skills, data access and affordable computing power.“The future of AI cannot be decided by a handful of countries, or left to the whims of a few billionaires,” Guterres said, stressing that AI must “belong to everyone.” India aims to ramp up its AI scale India is using the summit to position itself as a bridge between advanced economies and the Global South. Indian officials cite the country’s digital ID and online payments systems as a model for deploying AI at low cost, particularly in developing countries.“We must democratize AI. It must become a tool for inclusion and empowerment, particularly for the Global South,” Modi said.With nearly 1 billion internet users, India has become a key market for global technology companies expanding their AI businesses.Last December, Microsoft announced a $17.5 billion investment over four years to expand cloud and AI infrastructure in India. It followed Google’s $15 billion investment over five years, including plans for its first AI hub in the country. Amazon has also pledged $35 billion by 2030, targeting AI-driven digitization.India is also seeking up to $200 billion in data center investment in the coming years.The country, however, lags in developing its own large-scale AI model like U.S.-based OpenAI or China’s DeepSeek, highlighting challenges such as limited access to advanced semiconductor chips, data centers and hundreds of local languages to learn from. The summit has faced troubles The summit opened Monday with organizational glitches, as attendees and exhibitors reported long lines and delays, and some complained on social media that personal belongings and display items had been stolen. Organizers later said the items were recovered.Problems resurfaced Wednesday when a private Indian university was expelled from the summit after a staff member showcased a commercially available Chinese-made robotic dog while claiming it as the institution’s own innovation.The setbacks continued Thursday when Microsoft co-founder Bill Gates withdrew from a scheduled keynote address. No reason was given, though the Gates Foundation said the move was intended “to ensure the focus remains on the AI Summit’s key priorities.”Gates is facing questions over his ties to late sex offender Jeffrey Epstein. Associated Press
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