Analyst Perspectives

ISG recently published the 2025 ISG Buyers Guides for DataOps, providing an assessment of 51 software providers offering products used by data engineers, data scientists, and data and AI professionals to facilitate the use of data for analytics and AI needs. The DataOps Buyers Guide research generated three reports and five quadrants assessing providers in relation to overall DataOps, Data...

I recently wrote about the evolving requirements for operational data platforms to support artificial intelligence (AI) workloads. Operational data platforms providers are rapidly updating their products, driven by the development of intelligent applications infused with contextually relevant recommendations, predictions and forecasting that are in turn driven by machine learning (ML), generative...

Agentic AI is moving from pilots to production systems that execute work across enterprise applications, data platforms and business processes. As I’ve argued before, the value of AI is realized in action, not just answers, and enterprises are investing accordingly. One of the key questions now is how to coordinate the actions among different agents. My colleague Matt Aslett’s perspective on...

It’s clear that the contact center industry is experiencing a generational technological transformation. The effects of artificial intelligence (AI) and the automation it delivers have been extraordinary. But this isn’t the first time something like this has happened. People with long memories can recall the disruptive effects of CTI, for example, which enabled screen pops and integration of...

A little over two years ago, I observed that the pendulum of fashion in the data management sector was swinging away from multiple best-of-breed tools and toward consolidated platforms. Enterprise software portfolios take time to evolve, but the trend toward consolidation has clearly been evident in the product strategies of large data management providers since then. Many providers have combined...

Managing corporate income taxes effectively is important since these represent the second or third biggest expense for many enterprises. However attractive minimizing them might be, following all applicable tax laws and regulations is equally as important because failure to pay what the laws require can result in significant monetary fines and, potentially, reputational risk. Since there can be...

I have previously written about the critical importance of data management to the development of artificial intelligence (AI) applications and agentic AI. The importance of data management is nothing new, but automation of business processes and decision-making raises the stakes in terms of the expectations and the risks. The need for enterprises to have trust in their data governance and data...

I have written several times this year about Model Context Protocol (MCP) and its importance in enabling agentic artificial intelligence (AI) use cases. Numerous data platform, data management, data operations and real-time data software providers have added support for MCP to their products in recent months. MCP has become so ubiquitous, in fact, that it is easy to forget the protocol was only...

There is a shift underway in how enterprises structure their software stacks in relation to contact centers. Multiple factors have coalesced to reduce the importance of the traditional call handling infrastructure (i.e., the ACD) as the foundational element of the tech stack. It no longer has to be the focus of buying or deployment decisions. It’s been superseded by a more extensible (but...

Tokenization is an emerging topic for business software providers. Tokenization is the process of representing something valuable or complex with a simple computer-readable substitute to enhance security or improve the efficiency and usability of a system. Tokens are already widely used in commerce. It’s now common for sensitive data used in a transaction, such as a bank account number or credit...

The recent Oracle AI World event did not unveil much that was stunning “new” news for its business applications, because much of what has been evolving was presented already and has been in front of analysts for some months. What was on display, though, was steady progress to its advancing capabilities coming out every quarter. The company has focused on the development of agents and an agentic...

Oracle NetSuite’s presentations and announcements at its recent user group meeting, SuiteWorld, focused on an initiative called NetSuite Next, a set of artificial intelligence (AI), generative AI (GenAI) and agentic AI capabilities that will be an inherent part of the NetSuite suite of applications starting in 2026. The company’s objective is to facilitate customers’ transition to this AI-centric...

I recently explained the significance of data management as an enabler of strategic adoption of artificial intelligence. Data management enables enterprises to ensure that data is valid, consistent and trusted for operational use cases and analytic decision-making. Large volumes of data are required to train models, making data management and data governance critical to AI. Data quality and data...

There's a saying among military historians that amateurs debate strategy while professionals talk about logistics. In a similar vein, those rooted deeply in the workings of information technology (IT) pay close attention to data because it is fundamental to the proficiency and effectiveness of any IT system. Visionaries speak of data being the oil or gold of the information economy; practitioners...

We live in a time of uncertainty, not unpredictability. Planning charts the course of an enterprise through a sea of uncertainties, making fact-based predictions of potential outcomes to inform decision-making by executives and managers. Companies do a lot of planning—some formal but much of it informal. People in companies plan sales, they plan how to produce products and deliver services. They...

I am struck by the blizzard of software announcements this year describing new features for CX tools that are “agentic,” meaning autonomous tools take actions without (much) human intervention. Industry conversation about agentic AI has proceeded ahead of clarifying definitions and a sense of how it fits on a continuum of rapid AI development.

The era of ever-liberalizing trade that began in earnest in the 1950s (albeit with periodic ups and downs) came to an epochal end in the 2010s. Over the past decade, the ever-more demanding environment for supply chain planning and execution has forced enterprises to take a more strategic approach to managing these processes. The need for resiliency and adaptability in a rapidly changing world...

Artificial intelligence (AI) is no longer a futuristic concept but a current reality, and enterprise leaders are recognizing its profound impact on the IT sector. The development and deployment of AI-driven applications across various industries hinge on a robust IT infrastructure and skilled expertise. The words of industry leaders reinforce this sentiment: Amazon's CEO Andy Jassy indicates that...

As we stand precariously at the intersection of technology and business strategy, ServiceNow’s Knowledge ’25 conference unveiled “the art of the possible” for what service automation can mean in our efficiency-seeking world. ServiceNow has long been a champion of transforming the mundane into the extraordinary, and in the era of AI, it aims to harness the potential of intelligent automation. The...

The need for effective cybersecurity strategies remains a priority as enterprises face ever-increasing complex cyber threats. Nonetheless, the conventional approach in which IT departments, especially Chief Information Officers (CIOs) and Chief Information Security Officers (CISOs), exclusively manage the procurement of cybersecurity software, is showing its limitations. A crucial shift is...