As the number of security tools deployed continues to climb, it gets more difficult for enterprise security teams to know, with confidence, their overall state of security.
The AI deployments that appeal to enterprise IT teams are those with real, measurable gains – such as AI-driven customer support chatbots, using AI to automate network operations, and self-hosted AI models for business analytics.
Hyped technologies create staffing pressures. And as technology gets more complex, it’s harder to understand what skills are needed and identify who has them.
Open technology appeals to enterprises that want to avoid vendor lock-in. But to deliver real value, open-model technologies need to do more.
Security used to be an explicit part of networking, as it was in IBM SNA and mainframe security. Can and should networks be the security focus again?
Independent broadband and telecom-infrastructure providers could provide connectivity options in areas where service is thin, if enterprise concerns about business viability and technology operations are addressed.
As a subset of distributed computing, edge computing isn’t new, but it exposes an opportunity to distribute latency-sensitive application resources more optimally.
IBM is focusing its AI initiatives on the business case instead of trying to get customers to focus on AI, and that's what sets it apart.
The justification for HPE buying Juniper may be a mundane, economy-of-scale play or a move to gain Juniper's AI networking technology. Or there may be a vision for something more ambitious.
Despite prevailing cynicism, many enterprises find their primary IT vendor to be the most trusted source of network transformation insight, helping to drive both strategy and purchasing.
