Despite the significant investments that many organizations have put into generative artificial intelligence, most are not seeing the productivity gains that they expected. Simply adopting new technologies is no longer enough to drive productivity gains, if it ever were. In today’s rapidly evolving digital workplace, leaders face the ongoing challenge of translating digital investments into ...

At AWS re:Invent 2025, Amazon Web Services Inc. faced a dual mandate: Speak to millions of longstanding cloud customers while countering a persistent narrative that the company is lagging in artificial intelligence. In our view, AWS chose a distinctly pragmatic path. Rather than chasing the holy grail of what we call “messiah AGI,” or artificial ...

Henry Ford is often credited with saying, “If I had asked people what they wanted, they would have said faster horses.” This statement remains one of the most powerful warnings against incremental thinking. Optimizing for what already exists rarely delivers transformation. Especially when all signs point to the fact that it is failing. Customer service ...

As you would expect this year, some of the conversation at this week KubeCon/CloudNativeCon North America 2025 in Atlanta felt a little bit like a support group. We’re all trying to get past the hype, and come to grips with the risks and opportunities artificial intelligence presents for the cloud native development community. However, there’s also ...

In the race to deploy agentic artificial intelligence systems across workflows, an uncomfortable truth is being ignored: Autonomy invites unpredictability, and unpredictability is a security risk.  If we don’t rethink our approach to safeguarding these systems now, we may find ourselves chasing threats we barely understand at a scale we can’t contain. Agentic AI systems ...

Our latest forecast indicates that it will take a decade or more for artificial intelligence factory operators and model builders to reach breakeven on their massive capital outlays. Our projections call for nearly $4 trillion in cumulative capital spending outlays by 2030, with just under $2 trillion in cumulative AI revenue generated in that timeframe. ...

The data center as we know it is being reimagined as an “AI factory” – a power- and data-optimized plant that turns energy and information into intelligence at industrial scale. The tech stack is flipping from general purpose central processing unit-centric systems to graphics processing unit-centric accelerated compute, optimized for parallel operations and purpose built ...

The White House’s recent executive orders on artificial intelligence and the launch of America’s AI Action Plan have made one thing clear: The United States intends to lead the world in AI. To be sure, the policy direction is ambitious: Accelerate innovation, strengthen infrastructure and ensure fairness and safety. But as important as these goals are, rules ...

Large language models seem like magic. These artificial intelligence models write poetry, draft legal arguments and debug code with a fluency that suggests true understanding. But there is no magic, only patterns. An LLM learns language the same way a cryptographer cracks a code: by analyzing a massive volume of text and inferring the rules ...

For the past decade, software has been the primary constraint in most technology development. At the edge, hardware advances in processor speed, multi-threading and memory were incremental, while the real breakthroughs came from software innovation. Today, that dynamic has flipped. Hardware has quickly become the critical factor as multiple trends converge, including renewed focus on ...