AI/ML
IT Asset Management (ITAM) has undergone significant transformations in response to the evolving IT landscape ... The rise of the cloud has introduced new complexities, such as the need to manage SaaS applications and maintain visibility into cloud assets. The integration of AI has further accelerated these changes, driving ITAM teams to collaborate more closely with other IT stakeholders ... This shift is essential for addressing the multifaceted challenges of modern IT environments ...
AI roles now dominate tech market growth, according to ICT in Motion: The Next Wave of AI Integration, a new report from the AI Workforce Consortium ...
The observability landscape has transformed dramatically over the past decade. What began as traditional application performance monitoring (APM) has evolved into something more sophisticated and deeply essential to business operations. As we look at where the industry is headed, three themes have emerged that will define the future of how organizations monitor and manage their digital infrastructure ...
The biggest change in Cloud Managed Services 2.0 is how it unites domains that once operated in isolation. CloudOps, FinOps, DevOps, SecOps, and AIOps now work as a single, cohesive team instead of separate departments competing for resources and priorities. This matters because modern businesses operate at a pace that leaves traditional methods behind ...
Most teams go straight to the usual suspects when performance tanks in the cloud: app bugs, code regressions, maybe even the cloud provider itself. However, the real bottleneck is hiding in plain sight more often than not: the network ...
Your company's knowledge base is the engine that will power your AI agents. It's the structured data repository that an AI system uses to understand, reason, and make decisions ... Thus, transferring accurate knowledge is crucial. Incomplete or poor-quality data can reduce agent performance, accuracy, and even increase agent bias. Here are five steps to ensuring that your company's knowledge base transfer is optimal ...
Enterprises experience consistent year-over-year revenue growth from their generative AI initiatives and steady investment into AI and agentic projects, according to a new study from Google Cloud ...
AI agents are already transforming the enterprise ... But while the models are advancing fast, most enterprise systems still aren't ready for agent-to-agent AI. The reason is simple but consequential: the environments we've built don't support autonomous action ...
In Part 12, the final installment in the series, the experts present some final predictions about AI's future impact on APM and Observability ...
AI plays a transformative role in both APM and observability by turning raw data into actionable insights, enabling faster, more accurate detection and resolution of issues ...
The next generation of AI is already here. It may have been mere months since organizations adopted generative AI (GenAI), but now there's a new kid on the block and it promises to offer even greater benefits to businesses and IT operations teams in particular ... The key to success will be to avoid repeating the adoption mistakes of the past and to start small with manageable projects ...
The race toward AI maturity is on, but most enterprises are running uphill. According to new research from S&P Global Market Intelligence and Vultr, more than half of organizations expect to reach the "Transformational" stage of AI maturity by 2027 — a phase defined by widespread, embedded AI use across business operations. Yet as AI embeds deeper into real-time systems and mission-critical workflows, the gap between ambition and operational readiness is becoming harder to ignore ...
Enterprises are racing to leverage AI in their database environments — but most are skipping the guardrails. According to Quest research, 67% of organizations say AI is already critical to their database operations. Yet fewer than half report having a formal governance framework in place to manage it. That mismatch puts businesses at risk — operationally, financially, and reputationally ...
Shadow AI represents both the greatest governance risk and the biggest strategic opportunity in the enterprise. Organizations that will thrive are those that address the security threats and reframe shadow AI as a strategic indicator of genuine business needs. IT leaders must shift from playing defense to proactively building transparent, collaborative, and secure AI ecosystems that employees feel empowered to use ...
In today's enterprise landscape, two seismic shifts are converging: the mainstreaming of hybrid work and the rapid adoption of AI-enhanced applications. While both promise productivity gains and competitive advantage, they also expose a hidden Achilles' heel, application performance ...
A new study by the IBM Institute for Business Value reveals that enterprises are expected to significantly scale AI-enabled workflows, many driven by agentic AI, relying on them for improved decision making and automation. The AI Projects to Profits study revealed that respondents expect AI-enabled workflows to grow from 3% today to 25% by the end of 2025. With 70% of surveyed executives indicating that agentic AI is important to their organization's future, the research suggests that many organizations are actively encouraging experimentation ...
Respondents predict that agentic AI will play an increasingly prominent role in their interactions with technology vendors over the coming years and are positive about the benefits it will bring, according to The Race to an Agentic Future: How Agentic AI Will Transform Customer Experience, a report from Cisco ...
Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...
Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...
CEOs are committed to advancing AI solutions across their organization even as they face challenges from accelerating technology adoption, according to the IBM CEO Study. The survey revealed that executive respondents expect the growth rate of AI investments to more than double in the next two years, and 61% confirm they are actively adopting AI agents today and preparing to implement them at scale ...
A major architectural shift is underway across enterprise networks, according to a new global study from Cisco. As AI assistants, agents, and data-driven workloads reshape how work gets done, they're creating faster, more dynamic, more latency-sensitive, and more complex network traffic. Combined with the ubiquity of connected devices, 24/7 uptime demands, and intensifying security threats, these shifts are driving infrastructure to adapt and evolve ...
We're inching ever closer toward a long-held goal: technology infrastructure that is so automated that it can protect itself. But as IT leaders aggressively employ automation across our enterprises, we need to continuously reassess what AI is ready to manage autonomously and what can not yet be trusted to algorithms ...
Much like a traditional factory turns raw materials into finished products, the AI factory turns vast datasets into actionable business outcomes through advanced models, inferences, and automation. From the earliest data inputs to the final token output, this process must be reliable, repeatable, and scalable. That requires industrializing the way AI is developed, deployed, and managed ...
Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...
While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...