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  • for Month: 2026/05
IT service management (ITSM) is at an inflection point. For two decades, ITSM platforms have operated as structured systems of record and workflow orchestration layers, capturing tickets, routing tasks and enforcing process consistency. That model assumed humans were the primary actors and automation was deterministic, limited and rule-based. That assumption no longer holds. Artificial... Read More

Topics: ITSM, Observability, AIOps, IT & Technologies, AI & Technologies, AI and Machine Learning, IT Management & Operations, Autonomous IT, AI-Driven Workflow


A core challenge faced by enterprises due to the rapid rise of generative artificial intelligence (GenAI) and agentic AI is how to operationalize AI systems that rely on vast volumes of unstructured and multimodal data without compromising governance, scalability or performance. While early retrieval‑augmented generation (RAG) experiments fuelled interest in vector databases, many organizations... Read More

Topics: Data Platforms, Generative AI, AI & Technologies, AI & Machine Learning


Learning is often an afterthought for the business, even when leaders say it is not. You can see it in how learning gets funded, how it is supported and how it is threaded throughout the business. Too often, learning enters the conversation at the end when it should be there from the beginning. That applies to the technology, the content, the support model, the team structure and the broader... Read More

Topics: Employee Engagement, Learning Management, Talent Management, Workforce Management, Employees & HCM - Business & Technologies


Most technological innovations associated with the 1980s are now more likely to be found in a museum than a home or data center. Video cassette recorders, portable cassette players, compact discs, camcorders and fax machines have mostly been relegated to the trash heap. Mainframes and personal computers remain in use today but are largely unrecognizable from their 1980s counterparts in terms of... Read More

Topics: Data Platforms, AI & Technologies


There is a familiar refrain echoing across boardrooms and pipeline reviews that the channel is underperforming, that partners are not delivering and that ecosystems are noisy and inefficient and somehow past their prime. The implication is that something fundamental has broken. That conclusion is convenient, but it is wrong. The channel is not broken. What is broken is how most organizations... Read More

Topics: partner management, Office of Revenue - Business Technologies


Artificial intelligence (AI) is not a feature you just turn on. It requires readiness work that many HR organizations still have not done. That may sound blunt, but it reflects a reality that is getting lost in the current excitement around AI in HR. The market is moving quickly. Providers are rolling out copilots, assistants, recommendation engines and more advanced agentic capabilities across... Read More

Topics: Employee Engagement, Learning Management, Talent Management, Workforce Management, Payroll Management, Total Compensation Management, Employees & HCM - Business & Technologies


To mitigate cost and complexity, artificial intelligence (AI) and data initiatives must be aligned. Enterprises cannot afford fragmented approaches that duplicate effort or slow deployment, particularly as competitive pressure increases. Many providers have offered both AI platform and data platform capabilities for some time, but they have often addressed requirements with dedicated products... Read More

Topics: Analytics, Data Platforms, AI & Technologies, AI & Machine Learning


A distinct security category is emerging around protecting artificial intelligence (AI) itself, driven by the shift from pilot projects to embedded operational use. As AI becomes part of everyday workflows, the risk surface expands beyond traditional controls. Enterprises now need visibility into how employees prompt and rely on AI systems, how autonomous agents execute tasks and where sensitive... Read More

Topics: Data Governance, Cybersecurity, Generative AI, IT & Technologies, AI and Machine Learning, Data Controls, Visibility, Behavior Monitoring, Policy Enforcement, Control Plane


Revenue leaders entered 2026 under pressure to deliver predictable growth while navigating tighter budgets, higher expectations from finance and rapid adoption of enterprise artificial intelligence (AI). Many organizations are responding by slowing hiring or reassessing the size of their sales teams, even as pipeline targets and growth expectations remain unchanged. The result is a growing... Read More

Topics: Revenue Performance Management, Revenue Lifecycle Management, Office of Revenue - Business Technologies


Artificial intelligence (AI) isn’t a feature gate. It creates value when you’ve defined the decisions you want to improve and you have the data and workflows to support it, with permissions and consent boundaries that hold up in the real world and an audit trail that can explain what happened, why, and what the AI touched. Too many HR tech buying cycles begin with a shortcut: grab an RFI... Read More

Topics: Employee Engagement, Talent Management, Workforce Management, Payroll Management, Total Compensation Management, Employees & HCM - Business & Technologies


Agentic AI is rapidly emerging as the next phase of enterprise automation, moving beyond static workflows and copilots toward systems capable of autonomous reasoning, decision-making and action. Enterprises are increasingly experimenting with AI agents to augment customer service, IT operations and business processes, yet many struggle to operationalize these systems at scale. The challenge is no... Read More

Topics: Governance, Generative AI, AI & Technologies, AI & Machine Learning


The emergence of cloud computing has had an enormous impact on all segments of the IT industry, including data platforms. All providers of data platform products have enabled their products to be deployed in the cloud and/or consumed as cloud-hosted managed services. To date, the cloud has arguably had the largest impact on analytic data platforms, where cloud infrastructure led to the emergence... Read More

Topics: Data Platforms, Data Lakehouse, AI & Technologies


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