AI And Cybersecurity: The New Administration's 100-Day Reckoning
Just 100 days into the Trump administration, cybersecurity leaders are grappling with a volatile mix of deregulation, rising geopolitical tension, and accelerated adoption of AI.
At the RSAC 2025 conference this week, Snyk hosted a timely panel titled 'The First 100 Days: How AI, Policy & Cybersecurity Collide,' featuring an all-star lineup: Jen Easterly, former CISA Director; Nicole Perlroth, former journalist and partner with Ballistic Ventures; Sumit Dhawan, CEO of Proofpoint; and Peter McKay, CEO of Snyk. Moderated by Axios cybersecurity reporter Sam Sabin, the conversation examined the early signs of disruption and dysfunction—and what it all means for software security, national defense, and innovation.
The discussion was grounded in new findings from a Snyk-commissioned CISO survey, which revealed stark concerns about AI-generated threats, fragmented regulation, and eroding trust between the public and private sectors.
Since January, 70% of surveyed CISOs reported experiencing a cyberattack involving AI. Panelists noted that organizations are rapidly embracing AI to increase productivity, but often without properly considering security implications.
This rush to adopt AI is creating a widening gap between innovation and risk management. At the same time, nearly all CISOs surveyed expressed concern that AI-generated code may be introducing hidden vulnerabilities, suggesting a dangerous disconnect between perceived readiness and the evolving threat landscape.
Peter McKay observed, 'Everybody is just focused on productivity... just get the benefits of AI and we'll figure out security later,' highlighting the widespread rush to adopt AI tools without sufficient safeguards.
The panel addressed the impact of federal workforce reductions and policy reversals, including the rollback of Biden-era AI executive orders. Former CISA Director Jen Easterly described the loss of technical talent from government agencies as damaging to national cyber readiness.
The panelists noted that reported loyalty requirements for federal cybersecurity personnel could further erode morale and independence. Concerns also extended to international partnerships, with reports that allied nations are beginning to limit intelligence sharing with the U.S., reflecting declining trust in the current administration.
AI is drastically accelerating software development cycles, but this rapid pace is straining traditional security frameworks. Panelists highlighted how internal pressure to innovate often overrides caution, leading to insufficiently vetted tools and code.
They stressed the importance of integrating security from the outset rather than as an afterthought, and called for secure-by-design practices to become standard. Without these safeguards, AI tools that can prevent threats may also be exploited to cause harm.
Speakers emphasized that recent setbacks in federal cybersecurity leadership and policy risk reversing years of progress in public-private cooperation. The collaboration that once enabled a strong collective response to cyber threats—most notably in Ukraine—is now showing signs of strain.
Several panelists expressed concern that trust is weakening on both sides, with private companies unsure about their role in threat reporting and mitigation, and government agencies losing key channels for visibility. CISA's partnership-enabling authorities, such as CPAC, were cited as critical tools that are currently on hold.
When asked what single change they would make if given a 'magic wand,' panelists offered a range of pragmatic solutions. Proposals included mandating secure-by-design standards for consumer-grade routers—long a weak link in infrastructure security—and launching a national effort to clean up the open source codebase that underpins most modern applications.
Others called for harmonized, standardized AI development regulations to prevent a patchwork of conflicting state laws. There was also strong support for a software liability regime tied to demonstrable secure development practices, as well as the use of AI to refactor legacy code written in memory-unsafe languages.
As his top policy wish, McKay advocated for a national effort to improve software security at the source: 'If we all just focused on how we can just clean up open source code, we would have been in a better place.'
A unifying theme throughout the discussion was the urgent need for coordination—across sectors, agencies, and borders. The convergence of rapid AI adoption, regulatory rollbacks, and mounting cyber threats is creating a perfect storm. Industry leaders stressed that security cannot be an afterthought, and that public trust and international cooperation hinge on transparency, integrity, and mutual accountability. The panel concluded with a call to preserve the principles of trust and collaboration that once underpinned America's cyber defense strategy—and to ensure those values guide policy moving forward.
Easterly closed with a reflection on her time at CISA and how that should serve as a guiding light moving forward: 'We built trust and catalyzed trust and collaboration, and we did it with integrity, we did it with humility, we did it with transparency, and we did it with character. And that's what you all should demand from your government.'
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Forbes
an hour ago
- Forbes
When AI Doesn't Drive Transformational Change: Just A Better Digital Bureaucracy
File cabinets or catalogue drawers inside the laptop screen. Folders standing inside the drawer. AI didn't arrive in a vacuum. It entered workplaces shaped by decades of hierarchy, inertia, and top-down design. In many organizations, it's simply accelerating what already exists. It's a reflection of the systems and structures it enters. This article continues a deep conversation with Gary Hamel—described by The Wall Street Journal as the world's most influential business thinker and a relentless challenger of outdated leadership systems. In our earlier piece, we explored his critique of bureaucracy and his call to decentralize power and rethink management itself. But when we turned to artificial intelligence, his critique deepened. AI, he argued, is not inherently transformational. It becomes transformational only when leaders are willing to reshape the systems it supports. That's the real challenge. Because without a redesign of how power, trust, and judgment flow, AI risks reinforcing old dynamics. Faster dashboards. Smoother check-ins. But the same control loops, just digitized. AI Is A Mirror, Not A Magic Wand 'I've seen a lot of technological disruptions,' Hamel said. 'The personal computer, e-commerce, big data, the mobile revolution, social media. And none of them has fundamentally changed the way our organizations work.' Why? 'Because companies adopt new technologies in very incremental ways—within the logic of existing business models.' When organizations implement AI without rethinking design, they automate what's already there. Layers stay intact. Decisions remain centralized. Metrics multiply. Meaning doesn't. 'There are very few organizations where if you took out 20% of the bureaucracy, anyone would notice—except the bureaucrats.' Technology scales what's embedded in the system. If that system is built for control, AI will optimize it. Not disrupt it. Efficiency Without Alignment Isn't Progress British historian C. Northcote Parkinson famously said, 'Work expands to fill the time available for its completion.' In the AI era, work compresses: what took ten hours now takes two. But what fills the other eight? Often: more meetings, more reviews, more approval chains. A mid-level leader at a global bank described her week as 'completely full, yet largely invisible.' Her calendar was packed with automated syncs and system handoffs. Most decisions required cross-system inputs. She spent hours reviewing dashboards but no time coaching her team, or being coached herself. Change is being declared, but most of it amounts to translation: one process swapped for another, nothing truly reimagined. When Automation Feels Like Stagnation 'AI will become ubiquitous. We'll all use it,' Hamel said. 'But will it be truly transformational? History gives me reason to doubt.' He pointed to the work of MIT economist and Nobel laureate Daron Acemoglu, who argues that many companies adopt AI in ways that bring modest economic benefits but limited innovation. In one of his studies, The Simple Macroeconomics of AI, Acemoglu estimates that AI might increase GDP by just 1.1 to 1.6 percent over a decade—yielding annual productivity gains of around 0.05 percent. Acemoglu's concept of 'so-so automation' is especially relevant here: technologies that reduce costs but don't elevate the work. They don't enhance judgment or meaning. They just make suboptimal systems faster. And that's the risk. Without a deeper redesign, AI becomes a surface fix. A performance booster for the status quo. The outcome might feel like progress—but it's often just efficiency layered on dysfunction. Why Complex Systems Require More Than Code A recent Apple Machine Learning research study (titled The Illusion of Thinking) quietly reinforced this idea. Researchers tested large AI models on logic puzzles like the Tower of Hanoi. While models handled simple versions, performance collapsed with complexity. Even with detailed prompts, they faltered or quit. The insight? These models don't just struggle with accuracy—they break down under constraint. If AI can't solve recursive, multi-step problems reliably, it won't fix a fragmented workflow or compensate for poor design. Not yet. But importantly, that's a structural challenge—not a coding one. Digital Bureaucracy At Scale Efficiency doesn't guarantee clarity. Often, it just means more layers running faster. 'People said typists and assistants would disappear. And they did,' Hamel said. 'But now everyone is a typist.' AI hasn't reduced work—it's redistributed it. More typing, more tracking, more dashboards. Leaders now monitor progress more than they shape it. 'You make the cost of sending an email free, and you end up with spam,' Hamel added. 'We're going to have a ton of AI spam.' And not just in inboxes. In workflows. In KPIs. In strategy decks. Synthetic activity masquerading as insight. That's the deeper risk. Not About Replacement—About Realization Some CEOs claim AI could eliminate a big chunk of all entry-level white-collar roles. It's a dramatic claim. But Hamel sees a different story. 'In the last 50 years, only one job category has disappeared completely in the U.S.—elevator operator,' he said. 'Most jobs don't vanish. They evolve.' And that evolution requires clarity. Without a shared understanding of what AI is for and how it will help, employees resist—not out of fear, but out of confusion. That doesn't mean AI adoption is slowing down. If anything, it's accelerating. Gallup's latest research shows that the percentage of U.S. employees who say they've used AI at least a few times a year has nearly doubled in just one year—from 21% in 2024 to 40% in 2025. And yet, the clarity isn't keeping pace. Gallup research also shows that while 44% of employees say their organization has started integrating AI, only 22% say there's been a clear plan or strategy for doing so. Just 30% report that their organization has offered even general guidelines or formal policies for using AI at work. That's a 14-point gap between adoption and guidance. Tools are showing up faster than the structures to hold them. AI Integration Grows Within U.S. Organizations, but Quality Communication Lags The goal isn't to hand out AI like a new software license that everyone must have. It's not even about encouraging universal use. The real question is: what do we want to do with the time, energy, and attention that AI can free up? And are we designing our systems to support deeper thinking, more meaningful work, and generative collaboration—or are we just wrapping bureaucracy in code? Seeing Differently Beats Knowing More 'It's going to be increasingly impossible to know more than the people around you,' Hamel said. 'What adds value is not knowing more, but knowing different.' AI will summarize, calculate, and compose. But it can't sense nuance, identify what matters, or choose what to ignore. That's still a human domain. The role of leaders? Sense-making. Dot-connecting. Perspective building. Leading with purpose. Managing and coaching. Choosing what not to automate. Leadership in an AI era isn't about being faster. It's about being more discerning. Leadership diagnostic: Is your AI strategy designed around your system—or despite it? Culture Is the System Hamel often calls management a 'social technology.' One that hasn't fundamentally changed in decades. And that's the deeper transformation AI can't deliver. Gallup's insights affirm this: the companies most successful with AI are not those with the most powerful tools: they're the ones who invest in trust, learning, and adaptive teams. Systems, tools, culture—they're not separate. They're the same operating environment. Transformation Begins With Design Every organization now has access to the same AI tools, copilots, and dashboards. The differentiator isn't who uses them, it's how they're used. It's being said that AI won't take your job—someone who knows how to use it will. Let's rephrase that: AI won't take your job. But the right systems will decide who thrives with it. If your operating model is built on rigidity, AI will accelerate that rigidity. If your structure is built on shared ownership, curiosity, and distributed trust, AI will amplify those too. The real question is whether your current design can support what you want to scale. Because transformation doesn't begin with automation. It begins with alignment. As Gary reminded me—quoting W. Edwards Deming—'Every organization is perfectly designed to get the results it gets.' And AI will make those results more visible than ever before. The opportunity isn't in the tools. It's in how we build the systems around them.'You have to build organizations that are as amazing as the people inside them,' Gary said. That's still on us.
TechCrunch
an hour ago
- TechCrunch
Week in Review: Meta reveals its Oakley smart glasses
Welcome back to Week in Review! Lots in store for you today, including Wix's latest acquisition, Meta's new smart glasses, a look at the new Digg, and much more. Have a great weekend! Smart specs: Meta and Oakley have teamed up on a new pair of smart glasses that can record 3K video, play music, handle calls, and respond to Meta AI prompts. They start at $399 and have double the battery life of Meta's Ray-Bans. A $499 limited-edition Oakley Meta HSTN model will be available starting July 11. Unicorn watch: Wix bought 6-month-old solo startup Base44 for $80 million in cash after it quickly gained traction as a no-code AI tool for building web apps. Created by a single founder and already profitable, Base44's rapid rise made scooping it up irresistible. Sand to the rescue: Finland just turned on the world's largest sand battery — yes, actual sand — which stores heat to help power the small town of Pornainen's heating system and cut its carbon emissions. The low-tech, low-cost system is built from discarded fireplace soapstone, is housed in a giant silo, and can store heat for weeks, proving you don't need fancy lithium to fight climate change. You just need a pile of hot rocks. This is TechCrunch's Week in Review, where we recap the week's biggest news. Want this delivered as a newsletter to your inbox every Saturday? Sign up here. News Image Credits:Rebecca Bellan We're back, baby: VanMoof is back from the brink with the S6, its first e-bike since bankruptcy — and it's sticking to its signature custom design, despite that being what nearly killed the company. Backed by McLaren tech and a beefed-up repair network, the new VanMoof promises smoother rides, smarter features, and (hopefully) fewer stranded cyclists. Space lasers: Baiju Bhatt, best known for co-founding Robinhood, is now building lasers in space. His new startup, Aetherflux, has raised $60 million to prove that beaming solar power from orbit isn't a fantasy, with a demo satellite set to launch next year and early backing from the Department of Defense. Techcrunch event Save $200+ on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Save $200+ on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Boston, MA | REGISTER NOW Oh no: One of SpaceX's Starship rockets exploded during a test in Texas, likely pushing back the vehicle's next launch, which had been tentatively set for June 29. SpaceX says the blast, caused by a pressurized tank failure, didn't injure anyone, but it's yet another setback in a rocky year for the company's ambitious mega-rocket program. That lossless feeling: Spotify's long-awaited lossless audio tier still hasn't launched, but fresh hints buried in the latest app code suggest that it's under active development and could be closer than ever. But with years of delays and no official timeline, fans might want to temper their excitement until Spotify confirms the rollout. I can Digg it: Digg's reboot has entered alpha testing with a fresh iOS app aimed at becoming an AI-era Reddit alternative. The app offers a clean, simple design with curated communities, AI-powered article summaries, and gamified features like 'Gems' and daily leaderboards. We want you: The U.S. Navy is speeding up how it works with startups, cutting red tape and zeroing in on real wins like saved time and better morale. Department of the Navy CTO Justin Fanelli says it's leading with problems, hunting for game-changing tech in AI, GPS, and system upgrades. And with Silicon Valley finally paying attention, the Navy's becoming a go-to partner for innovators ready to shake things up. Cash ain't king: Mark Zuckerberg is throwing out massive cash — up to $100 million — to lure top AI talent from OpenAI and DeepMind. But OpenAI's Sam Altman says none of his key people have bitten, praising his team's mission over money. Meanwhile, OpenAI keeps pushing ahead with new AI models and even hints at launching an AI-powered social app that could outpace Meta's own shaky attempts. Before you go Image Credits:Cluely San Francisco's latest startup saga? Cluely's after-party for YC's AI Startup School blew up on Twitter, drawing 2,000 party crashers, but it became the 'most legendary party that never happened' after getting shut down by cops before a single drink was spilled. Founder Roy Lee's viral marketing may have promised chaos, but the real party's waiting. Maybe once the weather warms up?
Yahoo
an hour ago
- Yahoo
Wedbush Boosts IBM Target to $32
Wedbush kept an Outperform on IBM (NYSE:IBM) and lifted its price target to $325 from $300, betting on a new AI-fueled growth phase. Analysts led by Daniel Ives cited fresh field checks showing robust demand for IBM's software cloud and AI offerings. IBM features prominently on Wedbush's AI 30 list, reflecting conviction that it's underowned despite strong YTD performance. Warning! GuruFocus has detected 10 Warning Signs with ADI. The firm points to IBM's $6 billion+ GenAI book as a runway for sustained top-line expansion, with ongoing product launches aimed at capturing emerging use cases. A key catalyst is the continued shift toward hybrid cloud and containerized AIWedbush expects 75% of AI workloads to run in containers by 2027. On the ground, Ives' team sees momentum across WatsonX, AI agents, Red Hat, and OpenShift as enterprises lean on IBM to architect AI strategies. Looking further ahead, IBM's quantum roadmapincluding the upcoming Quantum Nighthawk chip and its Quantum Starling platformpositions it to tackle the multibillion-dollar quantum computing market. IBM's blend of legacy hybrid-cloud strength, accelerating GenAI adoption, and early quantum forays differentiates it from peers. As more enterprises seek productivity gains from AI, IBM's broad portfolio could unlock higher-margin software growth and defend its leadership in enterprise IT. Investors should monitor GenAI revenue cadence, container penetration rates, and early quantum milestones to validate whether IBM's renaissance accelerates toward that $325 target. This article first appeared on GuruFocus. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
