Big Tech is in the midst of an M&A spree in the AI space, and ServiceNow’s recent acquisition of the data analytics software firm Pyramid Analytics serves as a noteworthy example. Thanks to its embeddable advanced analytics, decision intelligence capabilities, and AI-driven insights, Pyramid Analytics’ software holds the potential to shape ServicesNow’s broader automation strategy beyond workflow digitalization.
As an enterprise tech industry leader, ServiceNow has positioned itself as a critical player in accelerating business automation, simplifying IT service management, human resources and customer service workflows. Connecting the dots, it seems that the company has much bolder ambitions, aiming to move beyond business workflows to become the AI-native nerve center of enterprise operations.
It’s an ambitious vision that requires far more than process efficiency optimization. The acquisition, announced earlier this month, aims to eliminate one of the most critical bottlenecks prohibiting enterprise acceleration – the friction involved with moving from insights to action.
Pyramid’s chief executive officer Omri Kohl summed it up when he said that “disjointed tools lead to slow decisions, no decisions or bad decisions.” His statement perfectly illustrates why ServiceNow swooped to buy his company. When business insights arrive too slowly, the opportunity to take action disappears. That’s why today’s AI-enhanced business intelligence is primarily a tool for driving reactive, rather than proactive, decisions.
Accelerating Business Intelligence
Traditional BI systems such as Tableau, PowerBI and ThoughtSpot can be remarkably powerful, but as long as people use them as human-managed, dashboard-first solutions, they operate at pedestrian speeds, unable to keep up with the pace of business operations.
When a user makes a request for a simple insight, such as identifying the regions with the highest turnover or their most at-risk suppliers, it triggers a disjointed process. After the request is submitted, it joins a queue where it sits and waits until a data analyst is available to create and refine an appropriate database query. Only once that’s done will the user receive the report or dashboard they requested, often several days or even weeks later. But business moves faster than this, and the insight may well be obsolete by the time it’s received.
Kohl built Pyramid to address this problem. The company’s key innovation is its decision intelligence platform, which enables users to ask complex questions about business data in their own words, without having to create SQL queries. This makes BI much more accessible, eliminating the need for specialized data analysts to assist, replacing them with instant, visualized answers to user’s questions. Pyramid’s powerful embedded analytics solutions allow these experiences to be injected into third-party apps, and it’s all enhanced by the platform’s centralized data engineering automation pipelines, metrics management, business logic modeling and governance capabilities.
In late 2024, Pyramid rolled out what the company refers to as “generative business intelligence,” because of the way it dramatically speeds up the time it takes to generate valuable insights. “With GenBI, BI is now truly self-service, because anyone can ask a question in natural language, without any expertise in data exploration,” Kohl told TechBullion in an interview last year, “and receive the insights they need in under a minute.”
From Instant Insights to Immediate Action
ServiceNow isn’t buying Pyramid because of what it can do, but rather because of what it can potentially enable when combined with the larger company’s own workflow tools.
By making Pyramid-powered analytics part of the natural business workflow, ServiceNow’s powerful AI agents, such as its Now Assist tools, will be able to take actions immediately on the insights that the analysis layer generates. For instance, instead of having a human worker read a chart and open a ticket manually, it will be possible to configure an AI agent to do all of this automatically. Humans would only be involved to the extent required to make a critical decision.
For this to work, ServiceNow likewise needs unified metrics management and business logic integration. Through its semantic layer, Pyramid ensures that terms such as “customer churn” and “supplier exposure” mean the same thing across finance, marketing, sales and support systems. This “shared language” is vital for scaling automation without creating organizational confusion.
Forrester analyst Charles Betz believes that the value of this capability is truly profound. “Pyramid adds an analytics and semantic layer that can define metrics in a way that both humans and AI agents can rely on,” he explained to The Register.
“Natural‑language querying is one expression of that,” he continued, “but the deeper value for customers is moving analytics closer to action — embedding trusted, shared meaning directly into workflows, suitable for agentic automation, rather than treating semantics as purely a design time problem and analytics as a downstream reporting use case.”
Pyramid’s semantic layer can become the lynchpin that connects instant insights with autonomous action, ensuring that the data is trustworthy and reliable for AI agents and human decision-makers alike.
Fulfilling ServiceNow’s Broader Vision
ServiceNow has already emerged at the forefront of the agentic AI push, having developed powerful agents for generating code and documents, performing research and summarizing information. It recently enhanced these agents with the acquisition of a company called Moveworks, which brings better natural language understanding capabilities to its agents. With Pyramid, these capabilities can be further enhanced with a more robust data infrastructure.
By integrating data-driven insights with agentic action in a single, seamless platform, ServiceNow believes it can distinguish itself from rivals such as Salesforce, which acquired Tableau, and Microsoft, which owns Power BI. While those firms have also eagerly embraced AI agents, they treat insight and execution as two different things, creating significant friction for users.
Kohl highlighted the value of integration in a November interview with AI Time Journal, when he explained that the most reliable way to ascertain the impact of AI is by observing how people spend their time. Presently, most workers spend hours on manual tasks such as preparing data, looking at reports and visualizations and related work.
“When AI-powered decision intelligence is working, that balance shifts,” he pointed out. “You see fewer people buried in manual preparation and more people engaging with insights, evaluating scenarios, and taking action. Technical teams become enablers instead of bottlenecks. Business users begin answering their own questions without waiting in line for a report.”
Pyramid is set to become a key enabler within ServiceNow’s Workflow Data Fabric, which is designed to enable agents to go beyond responding to requests and proactively dig up insights and take actions based on what they find. It does this by connecting data across systems, adding business context via a unified data catalog and applying policy-based governance, so AI understands how companies work and takes trusted action.
As tech ecosystem commentator Derek du Preez pointed out, ServiceNow’s leadership apparently believes that whoever controls the engagement layer will be the one that captures the most value. If the company’s agentic solutions don’t deliver on this, the suite risks becoming a commoditized data repository.
“These agents don’t just assist with tasks within individual applications,” du Preez wrote. “They orchestrate work across systems, accessing ServiceNow’s Workflow Data Fabric to pull information from connected sources and execute actions across departmental boundaries.”
Autonomous and Intelligent Business Operations
With Pyramid as its data intelligence layer, ServiceNow can transform itself into a kind of central operating system for AI agents, connecting information signals, intelligence, security and execution into everyday business workflows. While Oracle, IBM, Salesforce and SAP all offer some of these elements, none have brought them together as seamlessly as ServiceNow seemingly plans to do. If it succeeds, workflows will become more fluid. Business users will ask questions, receive trusted answers, take immediate actions, and then immediately move onto their next question.
It’s a vision that shares similarities with Kohl’s ideal of “end-to-end analytics automation,” which he defines as a combination of data ingestion, scenario analysis and decision support operating within a single platform. “For years, companies have been trying to pull together many different tools to achieve this,” he told AI Time Journal. “The real breakthrough is having a single platform that allows AI to support every aspect of the data journey from source to user, all made easier with AI automation.”
If everything goes to plan, ServiceNow will effectively revamp its identity. No longer will it be seen as a simple enterprise productivity tool, but as the essential engine that sits at the heart of autonomous, intelligent business operations.
