Analyst Perspectives

OneStream offers a platform designed to serve the needs of accounting and financial planning and analysis (FP&A) organizations. The software handles financial close and consolidation, planning and budgeting, analysis and reporting. OneStream recently held its annual user conference, Splash, in Las Vegas. In attending this meeting, my focus was on progress the company has made in the areas of predictive artificial intelligence (AI) and generative AI (GenAI) over the past year, since the...

At this stage of the development of Generative AI, there’s much we can see clearly (at least we think we can), but there’s even more likely to surprise us. As that great 20th-century philosopher and hall-of-fame catcher, Yogi Berra, famously said, “It’s tough to make predictions, especially about the future.” The breadth and speed of innovation today in all aspects of GenAI rivals that of the internet in the 1990s, and for the same reason.

I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well software providers’ offerings meet buyers’ requirements. The AI Platforms: Ventana Research Buyers Guide is the distillation of a year of market and product research by Ventana Research.

Embracing artificial intelligence technologies opens doors for innovation and efficiency. Alongside these opportunities, however, come risks. Threat actors are keenly aware of the potential impact of AI systems and are actively exploring ways to manipulate them. In this Analyst Perspective, I explore the world of adversarial machine-learning threats and provide practical guidance for securing AI systems.

ServiceNow is a global software provider that has developed a cloud computing platform that helps organizations manage digital workflows for enterprise operations. The provider uses its annual Knowledge user conference to educate customers and showcase product announcements. Ventana Research had the opportunity to attend the Knowledge 2024 event and provides this analyst perspective to summarize what transpired.

Until recently, dedicated consolidation software had been a sleepy category. First introduced in the 1980s as a tool designed to run on personal computers (freeing the accounting department from reliance on its IT department), offerings basically achieved feature and function parity by the next decade. The last major technology innovation—moving the software to the cloud—began in the mid-2000s. Cloud-based software reduces the cost and complexity of ownership, making dedicated software a more...

The emergence of generative artificial intelligence (GenAI) has significant implications at all levels of the technology stack, not least analytics and data products, which serve to support the development, training and deployment of GenAI models, and also stand to benefit from the advances in automation enabled by GenAI. The intersection of analytics and data and GenAI was a significant focus of the recent Google Cloud Next ’24 event. My colleague David Menninger has already outlined the key...

I recently wrote about the development, testing and deployment of data pipelines as a fundamental accelerator of data-driven strategies as well as the importance of data orchestration to accelerate analytics and artificial intelligence. As I explained in the recent Data Observability Buyers Guide, data observability software is also a critical aspect of data-driven decision-making. Data observability addresses one of the most significant impediments to generating value from data by providing an...

Oracle held an industry analyst summit recently where the focus was on artificial intelligence (AI) and embedded AI. At the event, Oracle demonstrated progress in adding useful AI-enabled capabilities to its business applications, especially in finance and accounting, supply chain, HR and revenue management. To put this into context, across the software industry, AI is already at work in many finance-focused applications that are currently available, albeit often in limited release. We are in...

We’re quickly approaching the moment when it becomes clear that artificial intelligence (AI) and generative AI (GenAI) will not be free. As that happens, we will discover who’s willing to pay how much and for what. After nearly 18 months of unlimited use-case fantasizing, it should be obvious that not all the potential applications of AI can be realized over the next three to five years because they fail a cost/benefit test. In theory, AI’s potential is almost limitless, but so far, little...