With an impressive track record evaluating cloud providers and their technology stacks, Maryanne Baines is an authority on the intricate dynamics of the enterprise software market. We sat down with her to unpack ServiceNow’s recent strategic moves, which have placed it in a direct competitive showdown. Our conversation explored the company’s confidence in its integrated platform strategy versus single-function tools, the practical ways it’s helping customers quantify the value of AI investments, and its disciplined architectural approach to absorbing major acquisitions without diluting its core platform.
Forrester’s Charles Betz called Salesforce’s Agentforce IT a “credible threat,” yet you seem unconcerned. Could you provide a concrete customer anecdote that illustrates how your integrated “platform for work” delivers unique value that a more commoditized or single-function tool could not replicate?
It’s easy to see why an analyst might label a new product a threat, but the view from inside a customer’s operations tells a different story. Think of a large financial services firm I recently worked with. They were struggling with new employee onboarding. Using a collection of separate tools, getting a new hire set up required IT to provision a laptop, HR to process payroll, and Facilities to assign a desk—three separate tickets in three different systems. What ServiceNow offers isn’t just a better IT ticketing system; it’s a single workflow that orchestrates that entire process. The moment HR initiates the “onboard new employee” workflow, it automatically triggers tasks for IT and Facilities on the same platform. That holistic, cross-departmental automation is something a commoditized, function-specific tool simply can’t touch, and it’s the core of the “platform for work” value proposition that inspires such confidence.
You mentioned the AI Control Tower helps customers quantify a portfolio of savings and productivity gains. Can you walk us through the specific metrics a manager sees on that dashboard and explain, step-by-step, how they would use that data to justify their investment to leadership?
Absolutely. The AI Control Tower is designed to translate technology into the language of business: dollars and cents. A manager logs in and sees a dashboard that isn’t just about abstract activity; it’s a portfolio of tangible results. Key metrics right at the top would be things like “Automated Resolution Rate,” showing the percentage of issues solved by AI without human touch, and “Agent Time Saved,” quantified in hours and then translated into a dollar figure based on the company’s own operational costs. The manager can then walk into a COO’s office, not with a vague story, but with a clear report. They can say, “Last quarter, we implemented this AI. The Control Tower shows our agents handled 15% more complex issues because the AI deflected thousands of routine requests, saving us X amount of dollars in operational costs. That’s a direct return on our investment, and here’s the dashboard to prove it.” It moves the conversation from a cost center justification to a strategic business investment with a quantifiable payoff.
Charles Betz raised concerns about acquisitions like Veza creating a divergent portfolio. Using your three-layer platform model—data, workflow, and experience—can you detail the architectural decisions and integration process for Moveworks to ensure it avoids that “bolted-on” feel you mentioned?
That concern is valid, as the enterprise software landscape is littered with failed, clunky acquisitions. ServiceNow’s architectural discipline is its defense. Think of their platform as a three-layer cake. At the bottom, you have the data layer—the single source of truth for everything happening in the enterprise. In the middle is the powerful workflow engine that acts on that data. And at the top is the experience layer, how users interact with it all. The $2.85 billion acquisition of Moveworks is a perfect example of an “experience layer” play. The architectural decision isn’t to simply place Moveworks’ chatbot on top of the platform and call it a day. Instead, they will deconstruct its AI assistant and agentic reasoning capabilities and weave them directly into the Now platform’s code. This means the new conversational AI will be natively powered by the data and workflow layers beneath it, creating a seamless experience. It avoids that jarring, “bolted-on” feeling where you know you’re using two different products glued together. An acquisition like Veza, focused on identity, would be integrated differently, its logic woven across all three layers to enforce security policies on data, within workflows, and at the user experience level.
What is your forecast for the evolution of AI-powered workflow automation in the enterprise over the next three to five years?
My forecast is a dramatic shift from task automation to true process orchestration driven by agentic AI. Today, we’re still largely focused on using AI to handle discrete, repetitive tasks—resetting a password, checking a ticket status. Over the next three to five years, the focus will be on AI agents that can manage complex, multi-step business processes from end to end. Imagine an AI that doesn’t just process an invoice but can detect an anomaly, cross-reference it with supply chain data, communicate with the vendor to resolve the discrepancy, and then complete the payment, all without human intervention. The “AI control tower” concept will become the standard, a central nervous system for a company’s automation strategy. Enterprises will demand a single platform to build, manage, and measure the ROI of these sophisticated AI agents, moving far beyond the fragmented and siloed automation efforts we often see today.
