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Enterprise Cloud 2.0 Technology Solutions, Strategy and Use Cases
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Infrastructure teams are being pushed to put AI agents to work. But before you give an agent permission to provision services, change configurations, or make other infrastructure decisions, thereʼs a more fundamental question to address: Can it trust your data? Data that works for human-driven automation may not work for autonomous agents. Engineers can spot missing information, investigate inconsistencies, and work around systems they know are unreliable. Agents need much clearer rules. Here are five signs your infrastructure data isnʼt ready for them yet. Five signs…
For decades, one of cybersecurity’s biggest challenges was finding vulnerabilities. AI may be about to reverse that problem. What happens when enterprises can suddenly find more vulnerabilities than their security and infrastructure teams can operationalize, test, patch, and mitigate? This question drove a discussion at the AI Networking Summit 2026 in Dallas that featured Mick Curry of Fidelity, John Feldmayer of eBay, Chris Moretti of Cigna Health, and Tom Gillis of Cisco. The conversation pointed to a fundamental shift in enterprise security: AI is beginning…
As enterprises move from experimenting with AI to deploying agents that can act, communicate, write code, and make decisions, the security conversation is changing too. For decades, enterprise security has focused largely on authenticating people, applications, and infrastructure. Agentic AI introduces something different: autonomous systems that can take action on behalf of the organization and interact with other agents, systems, and potentially other companies. That makes security about more than preventing access. Enterprises need to know what an agent is allowed to do, how far…
The first generation of agentic AI in IT operations focused on capability — giving machines the ability to investigate, reason, recommend, and execute. The next question is more consequential: what happens when those capabilities are organized around responsibility rather than tasks? The industry has grown sophisticated at decomposing operational work across specialized agents — one investigates a signal, another assesses a change, another recommends or executes a remediation. Individually, these capabilities can be powerful; collectively, they don’t necessarily add up to an operational role. Decomposition…
Artificial intelligence has rapidly become part of everyday business operations. Employees are using AI to summarize meetings, write code, analyze data, draft emails, and automate repetitive tasks. Software vendors are also embedding AI into business software and cybersecurity tools. While AI offers enormous productivity benefits, it also introduces cybersecurity risks. Employees are interacting with AI tools that haven’t been approved by IT, uploading sensitive information into public models, or granting AI-powered applications access to corporate data. The question is no longer whether your organization should…
A significant shift has happened in supply and demand, creating challenges on multiple levels across data centers. Not only is the demand for power and floor space increasing, but there is the dramatic shift in costs driven by a massive increase in worldwide demand for silicon, particularly for memory and storage silicon, because of AI. Gartner says that $2.52 trillion will be spent on AI in 2026, growing to $3.33 trillion in 2027¹. Major hyper-scalers alone are expected to spend $650 billion on AI and…
Enterprise AI adoption is moving faster than traditional technology planning cycles can support. New tools appear constantly, technology planning cycles are shrinking, and organizations are under pressure to deliver measurable value without compromising security, reliability, or governance. At the AI Networking Summit 2026 in Dallas, John Feldmeier, Vice President of Site Engineering and Information Technology at eBay, shared how the company is building an AI-enabled workplace while embedding governance from the beginning. The biggest takeaway: scaling enterprise AI is not primarily about deploying more tools….
Enterprise AI adoption is accelerating, but moving quickly is only part of the challenge. Organizations must also protect sensitive data, manage access, maintain visibility, and ensure new AI systems can operate securely at scale. During the AI Networking Summit 2026 in Frisco | Dallas, FedEx Freight leaders Michael Milligan and Prashanth Karne shared how the company is approaching this balance. Their central message: responsible AI governance should not slow innovation. Done well, it creates a repeatable path for scaling enterprise AI securely and confidently. What…
The AI infrastructure market just crossed a threshold. With GPU-backed debt now underwritten at scale, the constraint on AI compute growth is no longer capital — it is creditworthy enterprise demand. Analysts project AI debt financing will become a multi-trillion-dollar credit market by the end of the decade, second only to U.S. mortgages. Every dollar of that financing rests on one thing: enterprises willing to sign multi-year compute commitments. Those enterprises are the ONUG Community. For 15 years, ONUG has been where enterprise IT leaders…
The enterprises that win the AI era won’t be the ones with the most ambitious strategies. They’ll be the ones whose IT teams recognized early that data quality is foundational infrastructure and built accordingly. Most enterprises already know their CMDB drifts from reality. They know source-of-truth data is inconsistent across systems. This isn’t a failure of execution. It’s the predictable result of a system of record trying to track an environment that changes faster than it does. Layering AI on top of that broken foundation…
