Analyst Perspectives

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...

ISG Software Research recently published the 2025 Buyers Guide for Real-Time Data, providing an assessment of 43 software providers offering products used by analytics and data professionals to facilitate the use of real-time data. The Real-Time Data Buyers Guide research includes five reports which are focused on overall Real-Time Data, Application Integration, Messaging and Event Processing,...

Earlier this year I was a guest at the PROS 2025 Outperform conference in Las Vegas, Nevada. PROS is a well-established price optimization and revenue management software provider that, although well-known within the airline and hospitality industries, has a lower profile outside of these specific verticals. An original premise of PROS was to offer advanced analytics and pricing as well as...

Databricks recently hosted its Data+AI Summit in San Francisco, an event that attracted 22,000 attendees. That’s a far cry from the Spark Summit I attended in 2016. As pointed out in my coverage of Databricks massive funding round earlier this year, the company was originally founded as a provider of cloud-based Apache Spark services. Since its inception, Spark has been associated with processing...

One of the key questions that will need to be solved if agentic artificial intelligence is to fulfill its potential is which technologies and providers will serve the role of orchestrating communication and integration between the various models, applications and data repositories involved. ISG Research defines agentic AI as software designed to execute business processes through autonomous...

My colleagues have recently described how agentic artificial intelligence (AI) has the potential to revolutionize enterprise computing by automating the handling of static and dynamic complexity to enable software to take action without the need for human intervention. Put simply, agentic AI is the orchestration of the execution of discreet business tasks by a combination of software components...

I have previously explained how increased enterprise focus on artificial intelligence (AI) and agentic AI is a forcing function for enterprises to take long-overdue steps to improve data management and data governance. Data is integral to AI: large volumes of data are required to train models, while data freshness is important for inferencing in interactive applications and data quality is...

A little under a year ago, I explained how Google was positioning its BigQuery product as a unified data platform for processing data in multiple formats, across multiple locations, for multiple use cases—including business intelligence (BI) and artificial intelligence (AI)—using a combination of multiple data engines, including SQL, Spark and Python. The evolution of BigQuery as the focus of...

The artificial intelligence (AI) landscape is undergoing dramatic transformation, with enterprises rapidly adapting to a world where AI is no longer just a possibility but a necessity. ISG Market Lensresearch of 300 enterprises shows that AI initiatives were the second largest category of IT spending for 2024, behind customer experience initiatives. Furthermore, enterprises plan to increase 2025...

The six costliest words in managing a finance department are, “We’ve always done it this way.” The record-to-report (R2R) cycle describes the process of finalizing and summarizing the financial activities of a business for a specific accounting period—typically a month, quarter or fiscal year. It is important to note that R2R exclusively covers the activities between recording (keeping the books)...

I recently described how business data catalogs are evolving into data intelligence catalogs. These catalogs combine technical and business metadata and data governance capabilities with knowledge graph functionality to deliver a holistic, business-level view of data production and consumption. The concept of the knowledge graph has been part of the data sector for decades, but adoption has...

We live in a time of uncertainty, not unpredictability. Especially when a business finds itself on an undefined journey with an unclear destination—whether caused by internal events or the world at large—having plans to deal with a range of outcomes increases the odds of success. Or, at least enduring the least amount of damage. Managing an organization in uncertain times is always hard, but...

Domo is best known as a business intelligence (BI) and analytics software provider, thanks to its functionality for visualization, reporting, data science and embedded analytics. Additionally, as I recently explained, the company’s platform addresses a broad range of capabilities that includes data governance and security, data integration and application development, as well as the automation...

Founded as Software Development Laboratories in 1977, Oracle is a behemoth in the software industry, generating more than $50 billion in revenue in its fiscal year 2024. Originally focused solely on the relational database market, the software provider operated as Relational Systems, Inc. for several years before adopting the name Oracle in 1982. The company went public in 1986 and became one of...

It has been a little over a decade since the term data operations entered the analytics and data lexicon. It describes the application of agile development, DevOps and lean manufacturing by data engineering professionals in support of data production. DataOps was initially seen as antithetical to traditional data management approaches, which typically included batch-based and manual tools and...

Natural language interfaces for business intelligence products existed long before the emergence of generative artificial intelligence. Large language models have allowed BI providers to accelerate the delivery of functionality to convert natural language questions into analytic queries and generate summarizations and recommendations from data and charts. Features that enable natural language...