TechSpective’s Artificial Intelligence section covers AI the way people actually working with it need it covered — not as a trend to celebrate or fear, but as a set of real developments with real implications for how we work, what we build, and how we stay secure.
The emphasis here is on what things mean, not just what happened. When a new model drops or a major platform ships an agentic capability, the coverage examines what it actually changes and for whom. When research surfaces about enterprise AI adoption rates or AI security risks, the analysis connects those findings to decisions that organizations and practitioners have to make. Topics include large language models and generative AI, agentic systems and autonomous agent risk, AI PCs and on-device inference, AI infrastructure and data readiness, and the security implications of deploying AI in production environments.
The AI content space is saturated with hype and hot takes. This section is built around a different standard — contributors with enough technical grounding and enough industry experience to tell the difference between a genuine inflection point and a well-funded press tour.
The archive spans 28 pages of AI coverage developed during the period when enterprise AI moved from theoretical to operational. If you want signal rather than noise, this is a good place to start.
This week, the financial world woke up to a reality that many in the ivory towers of traditional publishing and data services thought was still a decade away. Anthropic, once seen as the “safety-first” academic sibling of the AI world, […]
The artificial intelligence arms race has entered a new, deeply personal phase. With its recent rollout of “Personal Intelligence,” Google is moving beyond generic chatbots to create a truly context-aware digital assistant. This isn’t just another feature update; it’s a
Lenovo’s Qira announcement at CES 2026 is not just another assistant launch. With Qira, Lenovo stakes a claim for where personal computing is headed: away from app-hopping and prompt repetition, toward an ambient layer of intelligence that persists across devices,
Lenovo’s Qira is a Bet on Ambient, Cross-device AI—and on a New Kind of Operating System Read More »
When fans think about the Super Bowl, they think about the spectacle—the precision of the plays, the roar of the crowd, the halftime show, the moments that become instant history. What they don’t think about is what makes all of
Super Bowl LX Runs on Data: How NetApp Helps Power the World’s Biggest Game Read More »
Reports surfaced this week confirming what many industry observers had long suspected but feared to articulate: China has launched a “Manhattan Project” for semiconductors. This massive, state-backed initiative has a singular, existential goal—to reverse-engineer the ultra-complex lithography machines currently monopolized
The Silicon Manhattan Project: China’s Atomic Gamble for AI Supremacy Read More »
I’ve had a lot of conversations about AI over the past couple years—some insightful, some overhyped, and a few that left me questioning whether we’re even talking about the same technology. But every now and then, I get the opportunity
Agentic AI and the Art of Asking Better Questions Read More »
While the headlines of the ongoing AI revolution are often dominated by large language models and generative software, the silent war is being fought in the data center. The hardware required to feed, train, and infer upon these models is
Enterprise AI World 2025, co-located with KMWorld 2025, offered a clear signal this year: the era of “drop a chatbot on the intranet and call it transformation” is over. The conversations shifted toward AI that sits inside real work—capturing tacit
AI-powered search tools promise something irresistible: type a question and instantly surface the most relevant information across your entire organization. It’s efficient, intuitive, and already reshaping how people work. But this ease of discovery also reveals a problem many companies
AI Search Is Exposing Hidden Access Pathways—Identity Security Must Catch Up Read More »
Enterprises are racing to adopt AI, but most run into the same problem once they move past early experiments: progress gets slower, not faster. Technology often isn’t the primary issue. The real drag comes from the organizational systems wrapped around
The Friction Slowing Enterprise AI — and How Companies Are Trying to Fix It Read More »
