Analyst Perspectives

Artificial intelligence (AI) is not a feature you just turn on. It requires readiness work that many HR organizations still have not done.

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...

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...

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...

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.

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...

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...

Revenue leaders entered 2026 under intense pressure to adopt enterprise artificial intelligence (AI), modernize their go-to-market operations and improve forecast accuracy at the same time. Many organizations are responding by adding new sales tools, AI assistants and workflow applications to an already crowded technology stack. The unintended consequence is that revenue teams often end up with...

To achieve an autonomous enterprise, a strategy alone is not sufficient. Organizations need software architectures that can support artificial intelligence (AI) at full scale within defined governance and security boundaries. This must be foundational, not an afterthought.

I have recently written about the importance of context in relation to agentic artificial intelligence, including the growing use of Model Context Protocol to enable LLMs, agents and applications to communicate with data platforms, file systems and development and productivity tools, and the importance of semantic data modeling to provide agreed definitions that reflect the meaning of entities,...

The shift roster has always been a place where strategy becomes personal. It decides who works, when they work and how predictable their lives can be from one week to the next. When scheduling becomes more automated, the consequences show up immediately in worker sentiment, manager workload, overtime spend and service levels. That is why the rise of artificial intelligence (AI)-driven scheduling...

I recently explained how providers addressing the full combination of artificial intelligence and data requirements through integrated AI and data platforms are increasingly attractive as enterprises look to accelerate initiatives and reduce costs and complexity. One example of a software provider that has combined AI and data capabilities is Microsoft with its Fabric data platform. First...

As an authoritative source, the ISG Index has delivered independent, fact-based insights for 94 consecutive quarters, supporting Wall Street, service and software providers and enterprises in tracking key technology and market shifts.

The quickest way to derail an HR analytics effort is to publish a dashboard that people do not believe. You can feel it in the meeting when the questions stop being about decisions and start being about whether the numbers are real. Leaders ask for “the actual headcount,” HRBPs keep their own trackers, and the room quietly agrees the system is helpful but not authoritative. At that point, the...

I recently attended Enterprise Connect, a significant industry conference covering contact centers, customer experience (CX) and telephony. I wrote my initial coverage here. Now, a few weeks later, I’d like to offer some thoughts about what my observations mean and where the industry goes from here.

By now it should be obvious that artificial Intelligence (AI) and agents in all of their forms are on the brink of changing how finance and accounting departments operate. The basic outlines are already in place, but it’s not clear how or how rapidly day-to-day operations will evolve, as well as (by definition) what surprises are in store.

The software industry has entered one of its most consequential pricing and value inflection points since the shift to cloud computing. AI is not an incremental capability layered onto existing software; it is fundamentally redefining how software should create value and, in turn, how that value must be priced. The traditional model of seat-based subscription pricing was designed for systems that...

Agentic commerce represents the next phase of digital commerce evolution, where AI agents powered by large language models (LLMs) mediate, decide and execute transactions on behalf of consumers and enterprises. The rapid adoption of generative AI platforms now reaching hundreds of millions to billions of monthly users has accelerated a fundamental shift from search-driven engagement to...

Artificial intelligence (AI) just became the operating system for enterprise security. That was the clearest signal coming out of the RSAC 2026 Conference, and it materially changes how CIOs and CISOs should evaluate security platforms, operating models and investment priorities over the next 12–24 months.

Recruiting technology still carries the fingerprints of an earlier operating model, one where hiring was managed as a series of isolated requisitions and success was measured by how efficiently a team could move a candidate from application to offer. That model created durable strengths around workflow, compliance and visibility, and most organizations still need those strengths. The problem is...