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The U.S. workforce is facing a pivotal challenge: A widening skills gap that threatens economic growth and innovation. While demographic trendslike declining birth rates and a shrinking pipeline of young workersare real, the more actionable issue is the growing mismatch between the skills employers need and those available in the labor market. According to Pearsons recent Lost in Transition research, nearly 90% of U.S. employers report difficulty finding candidates with the right skills, and more than half of workers feel unprepared for the demands of the future workplace. This problem is decades in the making, and its consequences will be global. Without action, this gap threatens economic stability, public health systems, and critical infrastructure. Projections indicate the U.S. could face skills shortages in 171 occupations by 2032. But instead of focusing on the inevitability of demographic change, we should zero in on the skills gapa challenge we can address through education, collaboration, and the smart use of technology. The skills gap is not just a statistic; its a call to action for educators, employers, and policymakers to rethink how we prepare people for work. AI AS A CATALYST FOR WORKFORCE READINESS Artificial intelligence, when thoughtfully designed and applied, is already helping to close the skills gap. When used as a tool for guided learning rather than a shortcut, AI can help bridge the skills gap and equip the workforce to succeed where human touch is required. AI-powered learning tools in educational environments are already accelerating pathways into critical professions by enabling learners to demonstrate measurable improvements in critical thinking and adaptability, as well as build durable skills that employers need most and are essential for thriving in a rapidly changing economy. Employers, too, are leveraging AI to upskill their current workforce, using adaptive platforms to identify and close skills gaps faster than traditional training methods allow. This approach is not about replacing people with technology, but about empowering workers to learn, adapt, and grow alongside digital tools. THE NEW COMPETITIVE ADVANTAGE: LEARNING HOW TO LEARN The ability to learn how to learn is now a core competency for career success. As the shelf life of technical skills shortens, the most valuable workers will be those who can continuously acquire new knowledge and adapt to new roles. AI can support this by personalizing learning experiences, promoting metacognition, and helping people build the confidence to navigate transitions throughout their careers. Were already seeing data showing that AI can promote the real learning and adaptability skills that are needed in the workforce. High school and college students are improving their academic performance and demonstrating critical thinking skill through the use of science-backed AI tools that align with Blooms Taxonomy of Learning framework. AI in education is doing more than raising test scores; it’s teaching students how to learn, adapt, and thrive in an economy where continuous upskilling is the norm. Closing the skills gap will require collaboration across education, business, and government. We need to align AI literacy standards, invest in educator training, and ensure responsible use of technology that prioritizes data privacy, bias mitigation, transparency, and measurable learning outcomes. By focusing on the skills gapand leveraging the best of AI and learning sciencewe can build a workforce that is not only prepared for the future but empowered to shape it. Tom ap Simon is the President of Pearson Higher Education and Virtual Learning
Category:
E-Commerce
Each business has its unique challenges, but one commonality today is that AI is poised to disrupt almost every business everywhere. Organizations arent the only ones rapidly shifting to adopt AIattackers are too, and theyre doing it faster. The implications of this AI arms race are alarming for legitimate businesses around the world. Security teams must rapidly evolve their cyber strategy to meet these new threats, moving away from a reactive posture that detects and then responds after an incident happens. To outpace attackers, organizations will need to be preemptive insteaddeterring, neutralizing, and preventing threats before they happen. HOW AI IS CHANGING THE GAME Anthropic recently revealed that a threat actor group was able to use AI (Claude) to perform 80-90% of an espionage campaign, with only sporadic human intervention, to attack 30 enterprises around the globe. The AI made thousands of requests per second, something even a team of highly skilled human attackers couldnt do. Anthropic concluded that less experienced and resourced groups can now potentially perform large-scale attacks of this nature with the help of AI. That means the barrier to entry for cybercrime has dropped dramatically. Individuals who previously lacked the technical skills to code can now leverage AI tools to create and execute complex attacks. This will inevitability lead to a surge in the number of sophisticated attacks unleashed on business and governments worldwide. Most enterprises and cybersecurity vendors are responding to this change by taking legacy, reactive security approaches and trying to add AI on top of them. The idea is that you should fight AI-powered attackers with AI-powered defenses. However, this is akin to taking a tank and adding AI to it to battle a fleet of drones. Yes, the AI-enabled tank will get better, but it is fundamentally too slow and too expensive to meet the new threat and win. As AI makes large-scale attacks accessible to anyone, its not just the volume of threats that will explode, its their uniqueness. Attackers are no longer limited to reusing the same malware, they can now target specific infrastructure vulnerabilities with single-use attacks. MASS PERSONALIZATION: A NEW FRONTIER FOR ATTACKERS Before AI, attackers built and then reused malicious software (i.e. malware) to attack as many enterprises as possible, but AI changes that entirely. It enables mass personalization: the ability to generate custom, one-off attacks for each target, at scale. As more and more attackers use these types of specialized, single-use malware to target their victims, businesses relying on legacy approaches will experience an exponential increase in breaches. They will face a never-ending battle to contain breaches before they can cause millions or even billions of dollars in damage. The traditional security model, and thus your business, relies on identifying patient zerospotting the first instance of a new threat, then blocking it everywhere else. However, when every attack is unique, there is no patient zero. In a world where even unskilled attackers can use AI to perform thousands of tasks a second, novel threats can be created and evolve faster than legacy, reactive security systems’ ability to observe and respond. This is not a future problem; this is a problem today. Last year, Infoblox classified over 25 million new domains as malicious. Ninety-five percent of them, or about 24 million, were unique to one enterprise, meaning the domains were made to specifically attack a singular organization. Last year, attackers personalized 24 million attacks for enterprises all over the world, each able to initially evade most legacy, reactive security tools. If your executive team and boardroom are not already discussing this, they need to start now. THE FUTURE OF YOUR CYBERSECURITY IS PREEMPTIVE AI has changed the nature of attacks, so now, it must change the nature of our defenses. To combat these threats, its no longer enough to be reactive. Instead, the cybersecurity industry and enterprises must urgently undergo huge changes to become more preemptive in their approaches to security. Gartner analysts are saying the same, predicting that preemptive cybersecurity will make up 50% of IT security spending by 2030, up from almost 5% in 2024. The firm specifically cites AI-enabled attacks as the force behind this change. Its time for a mindset shift. Leaders must see the security fight with a higher-level view. Instead of just focusing on using AI to speed up how fast they can detect and respond to individual fires, they must focus more of their energy and investment on using new approaches to stop the fires from ever starting. By developing strategies to preempt threats, teams can beat attackers to the punch, stopping threats before they can wreak havoc on their businesses. Scott Harrell is CEO of Infoblox.
Category:
E-Commerce
CIOs are grappling with how to leverage AI, but most are asking the wrong question. Its not about an AI strategy. Its about a business strategy powered by AI. At Samsara, when we focused AI on clear business problems, we cut support chat volume by 59% with virtual agents, our IT help assistant auto-resolved 27% of tickets during the pilot, and engineers accepted about 40% of suggested code from AI code-assist, freeing teams to ship faster and tackle harder work. My takeaway is that if you treat AI as a separate initiative, youll chase tools. If you treat it as leverage on a business KPI, youll create impact. The VC Mindset: Investing in AI My philosophy on AI investment mirrors how a Venture Capital firm manages its portfolio. While every investment should strive for success, organizations must adopt a portfolio mindset: expecting only 10% of AI pilots to yield a high return. This crucial insight is what drives a VC firm, and what should drive your AI funnel. This means maintaining an active, well-fed funnel of AI investments. Working diligently to narrow this funnel through rapid pilots and experimentation allows businesses to move fast and fail quickly on small, contained experiments to find the few truly transformative applications. This approach is crucial given the sheer volume of AI solutions available. The typical vendor evaluation process might involve vetting three or four key solutions. In the AI space, that number can balloon into the thousands. Applying a VC mindset allows us to efficiently triage and prioritize, focusing our resources where the potential business impact is highest. Scaling AI Through Change Management Investment is only half the battle. The most sophisticated AI tool is worthless if employees don’t use it effectively. Success demands a robust AI change management program that builds new organizational muscles. 1. Driving Adoption: A Top-Down and Bottom-Up Engine True organizational change requires synchronized effort from the C-suite to the front lines. This is the top-down and bottom-up mandate for AI adoption. Top-Down Commitment: This begins with the CEO and C-suite making AI a core business priority. At Samsara, two of our four company priorities are explicitly AI-relatedone focused on internal efficiency, and the other on product innovation. This executive mandate, championed by leaders like our CEO and reinforced through my partnership with our CFO, ensures AI initiatives are treated as strategic imperatives, not discretionary projects. Bottom-Up Application: While CIO organizations are natural early adopters, the people best positioned to apply AI are those who live with the business problems dailyin supply chain, finance, sales, and operations. These colleagues have a nuanced, first-hand understanding of where AI tools can create the most value. And they can bridge this gap by empowering those teams to identify and lead implementation. 2. Scale Literacy with an AI Champions Network To connect the top-level vision with bottom-up execution, businesses must actively cultivate AI literacy. At Samsara, weve implemented a two-pronged approach to ensuring that AI skills and uses are being scaled across our business. AI Champions Network: Our AI Champions are a bridge to realizing our AI ambitions. We identify individuals across every function with a strong understanding of technologythe natural thought leadersand designate them as AI Champions. We give them concrete roadmaps for how to use AI in their specific function, making them evangelists who drive enablement and comfort within their teams. General Education: We use channels like our daily Slack digest to deliver short, 5-minute to 10-minute lessons to provide general AI education and demystify the technology for all employees. 3. Frame AI as Partnership, Not Replacement Any companys ethos on AI should be clear: AI wont replace people who embrace it. They should position these tools to their staff as partners that will better their teams and outputs, freeing them up for higher-value work. As I alluded to above, for our R&D and BizTech teams, weve implemented AI Code Generator tools. Our teams accept, on average, over 40% of the prebuilt code suggested, accelerating development cycles and allowing them to focus on complex, innovative challenges. On the service side, our use of AI chat agents has driven a 59% reduction in chat ticket volume in customer support, allowing staff to focus on complex issues. Similarly, our internal Generative AI-powered help assistant for the IT Help Desk resolved 27% of tickets with no human touch during the pilot, freeing up IT staff for strategic work. The CIOs Evolving Role In this new era, the CIO’s job is to stay intensely agile. They must mirror the companys need for external innovation with a commensurate drive for internal modernization. The path to AI success is not paved with technology alone, but with strategic discipline and cultural transformation. The new CIO mandate is simple: Stay intensely agile. Mirror the companys need for external innovation with an equivalent drive for internal modernization. The path to AI success is not paved with technology alone, but with strategic discipline and cultural transformation. Stop chasing the latest platform and start asking: What is the core business problem we need to solve? Anchor your investments in quantifiable business value, embrace a venture-style portfolio approach to experimentation, and aggressively equip your employees to be partners of AI, not its victims. This shift from technology buyer to strategic portfolio manager is the key to enduring competitive advantage.
Category:
E-Commerce
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