IBM Reveals CEO Expectations, Concerns with AI Implementation
Despite early setbacks, CEOs remain committed to AI, focusing on strategic leadership, measurable ROI, and workforce transformation to turn ambition into
Looks at issues related to artificial intelligence technologies, including cognitive computing, deep learning, and machine learning. Considers also supervised and unsupervised learning and natural language processing.
Despite early setbacks, CEOs remain committed to AI, focusing on strategic leadership, measurable ROI, and workforce transformation to turn ambition into
Foundation models won’t replace radiologists, but they are already redrawing the job description. By catching faint signals, shaving minutes off critical …
As MCP servers become the backbone of multi-agent AI systems, their design and protection demand first-class architectural status.
Agentic AI promises to move industrial automation from rigid workflows to adaptive, intelligent systems. But the path forward isn't purely technical. It …
As AI systems grow more capable, the roles of human programmers may evolve significantly, offering insight into the broader transformation of skilled work in …
By enforcing robust data governance policies, implementing AI-auditing frameworks, fortifying access controls, streamlining documentation, and staying informed …
For companies determined to future-proof their operations, now is the time to reimagine GBS as the orchestrator of enterprise intelligence.
Manufacturers find that the integration of digital twins, AI, and simulation technologies supports advanced plant modeling, simulation, planning, and …
The build-vs-buy decision is not just about cost or control. It’s about aligning an approach to AI with an organization’s long-term digital ambitions, …
In this week’s real-time analytics news: The Linux Foundation launched a new project focusing on secure AI agent-to-agent communications and