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AI-Powered Devices: The Fourth Wave of Enterprise Computing
Enterprise computing enters its fourth wave as client devices transform from passive endpoints to intelligent AI systems. Modern laptops, desktops, and mobile devices now feature built-in NPUs and AI accelerators that bring artificial intelligence directly to where work happens. This shift creates distributed intelligence networks where every device anticipates user needs, optimizes workflows, and collaborates autonomously. Organizations gain enterprise AI at scale, transforming employees into human AI agents with unprecedented access to contextual, personalized computing experiences. The future of work is here—powered by intelligent devices that don't just access AI, but embody it.
Artificial Intelligence
Riding the Wave to Enterprise AI at Scale: The Transformation of Client SolutionsRead More
The “Personal Touch” of AI is Undeniable, Thanks for Impressive Advances in Client SolutionsRead More
The Deepening Impact of “AI Everywhere” is Revolutionizing Client SolutionsRead More
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Revolut breach exposes widespread security weakness -- trust
The Revolut data breach showed what can happen when organizations over-trust and under-verify. Experts warn that countless ...
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How to explain AI risk to the board: What directors need to hear
CISOs must build a narrative on security, reputation and financial impact when discussing AI risks with board members -- and drop...
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Data storytelling techniques can help sell governance efforts
In addition to explaining analytics results, data storytelling can help sell business executives on the need for strong data ...
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Does setting data guardrails slow innovation?
Governance and speed are treated as opposites, but the real variable is design. Four control domains determine whether data ...
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Learn the 6 types of inventory risk
Excess inventory takes up warehouse space and complicates picking efficiency. Learn about other types of inventory risk and how ...
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Why multi-agent systems are an enterprise architecture challenge
Multi-agent systems require strong governance frameworks to ensure agents share consistent assumptions, policies and data, which ...
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Seismic shift in Splunk pricing spotlights AI data management
The era of simply amassing heaps of raw telemetry is over, Splunk users say. Viable AI agents for automated IT ops will depend on...
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Harness makes its case for governing autonomous AI SDLC
Harness aims to govern increasingly autonomous software delivery with risk-based controls, agent context and runtime data.
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How Agile development principles can help with scaling AI deployment
In this podcast, Andrew Sales, chief methodologist at Scaled Agile, says lean and Agile methods can help companies take full ...
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AI ate the first rung of the technology career ladder
As AI automates routine tasks in tech careers, it could deprive junior professionals of learning opportunities. And it may create...