Cloud & AI for the Enterprise
Avoid tech sprawl by learning how to evaluate and prioritize emerging technologies for real business impact. Emerging technologies are arriving faster than most organizations can evaluate them. From generative AI to quantum computing, the pressure to “stay ahead” often leads to bloated roadmaps, fragmented investments, and diluted outcomes. The result: more complexity, less clarity, and … Read more
As AI adoption accelerates, organizations are elevating the CDO role to align data strategy with business outcomes. In 2024, it seemed inevitable that AI transformation would deepen the alignment between data and infrastructure. Many expected the percentage of chief data officers reporting to CIOs to rise sharply. Instead, Forrester’s 2025 data revealed the opposite: a … Read more
Most agentic AI deployments rely on vendor platforms because building agentic architectures in-house is far more complex than advertised. Enterprise interest in agentic AI is surging. The promise is clear: autonomous systems that can reason, plan, and act across workflows without constant human prompting. But while vendor marketing paints a picture of plug-and-play intelligence, the … Read more
Learn how to implement enterprise-grade AI agents that solve real business problems and deliver measurable ROI. AI agents are no longer experimental. They’re being deployed to automate workflows, accelerate decision-making, and reduce cost across core business functions—from customer service to supply chain. But most enterprises still struggle to move beyond isolated pilots and fragmented use … Read more
How to move beyond experimentation and deploy AI agents that drive measurable business outcomes. AI agents are no longer a novelty. Most large enterprises have tested them—some in customer service, others in IT operations or finance. But few have moved beyond isolated pilots. The result: fragmented value, mounting shadow IT, and missed opportunities to scale … Read more
Learn how enterprise IT teams can reduce AI agent development costs while preserving performance and reliability. AI agents are no longer experimental. They’re being deployed across enterprise workflows—from customer support to internal knowledge retrieval—with expectations of speed, accuracy, and measurable ROI. But as adoption scales, so do costs. Model tuning, infrastructure, integration, and oversight all … Read more
AI agent performance monitoring: scalable, efficient, and time-saving strategies for enterprise IT environments. AI agents are now being embedded across enterprise workflows—from customer support to IT service desks to internal knowledge retrieval. But as adoption grows, so does the complexity of managing performance. Spot-checking outputs manually doesn’t scale, and it doesn’t surface the patterns that … Read more
Here are practical AI agent applications that are driving measurable ROI across enterprise workflows and systems. AI agents are no longer experimental. They’re quietly reshaping how large organizations handle decisions, workflows, and service delivery. But many teams still struggle to identify where agents can deliver real value—beyond chatbots and automation pilots. The key is to … Read more
How to build, train, deploy, and improve AI agents faster—without compromising control or ROI. AI agents are moving from experimental pilots to core infrastructure. Whether automating support, optimizing workflows, or augmenting decision-making, they’re becoming embedded in enterprise systems. But speed matters. The longer it takes to build and refine these agents, the more value is … Read more
Learn how to design and deploy AI agents that deliver measurable ROI by solving real business tasks. AI agents are no longer experimental. They’re being deployed to handle customer queries, automate workflows, and assist with decision-making. But most implementations fall short—not because the technology isn’t ready, but because the agent isn’t tailored to the task. … Read more