October 5, 2026 4 min Creating the conditions for AI at scale As AI becomes more accessible, the organizations creating measurable value are redesigning work, building trust, and aligning people, governance and outcomes from the start.
Intro

For many organizations, the question is no longer whether to invest in AI, but how to demonstrate tangible business value from AI initiatives and investments.

Senior technology leaders explored what separates organizations creating measurable outcomes from those struggling to move beyond experimentation during two ServiceNow-hosted discussions at the WSJ Technology Council Summit. Across a private executive masterclass and a mainstage leadership discussion featuring Kellie Romack, Chief Digital Information Officer at ServiceNow, several themes emerged around leadership, operating models, and governance. Together, they point to a broader reality: scaling AI is becoming less about technology and more about the decisions leaders and their teams make on how work gets done.
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Table of Contents
Intro Redesigning work is where AI value starts AI fluency becomes a competitive advantage Governance creates the confidence to scale The next leadership mandate
Redesigning work is where AI value starts

AI delivers the greatest impact when organizations reinvent the way work is performed rather than applying AI to existing processes.

Long-standing workflows, extra layers of approval, and organizational silos can limit the value of even the most promising AI initiatives. One example shared during the discussions described a process with 16 manual handoffs, illustrating why automation alone is rarely enough. 

Organizations must first define the outcome they are trying to achieve, then reengineer the process around it. Romack reinforced this point during the mainstage discussion, emphasizing the need to understand the problem rather than layer AI onto existing ways of working. She also noted that some of the most meaningful returns go beyond efficiency gains, instead coming from how organizations choose to reinvest the capacity AI creates.
AI fluency becomes a competitive advantage

For Romack, trust and transparency are essential to successful AI adoption. On the mainstage, she emphasized that "AI shouldn't be scary. It can't be a black box. Move a black box to a glass box, and help educate and bring everybody along."

As organizations embed AI more deeply into everyday work, employees need confidence in how systems operate, how decisions are made, and where human oversight remains critical. One participant compared the relationship between people and AI to racing: data and intelligence can improve speed and performance, but a human remains at the wheel making context-dependent decisions. Leaders must be deliberate about which decisions AI should support, which decisions people should continue to own, and how those responsibilities fit together.

This is about more than AI training or adoption programs. It requires AI fluency across the workforce, where employees can critically assess AI outputs, apply judgment, redesign ways of working, and actively shape how human and digital capabilities complement each another. Romack shared examples from ServiceNow's own transformation efforts, describing how AI initiatives were paired with workforce development and career growth conversations. Organizations that treat workforce readiness as a strategic priority, rather than an afterthought, will be better positioned to scale AI successfully.
Governance creates the confidence to scale

The summit discussions framed governance not as a constraint, but as an enabler of speed and scale. One analogy resonated particularly strongly: brakes do not stop a car from moving. They provide the control needed to travel faster with confidence. Participants argued that governance plays a similar role in AI transformation, creating the guardrails that allow organizations to accelerate without losing accountability or control. 

This perspective was reinforced during the mainstage conversation, where Romack stressed that "governance cannot be an afterthought." Instead, policies, permissions, infrastructure, and architecture need to be considered alongside AI initiatives from the beginning. She also highlighted the importance of building visibility into adoption, value creation, and business outcomes, ensuring leaders understand not only how AI is being used, but whether it is delivering the results the organization expects. 

And with governance comes accountability. Executives agreed cross-functional alignment and accountability are critical to success. As AI initiatives increasingly span technology, operations, security, risk, legal, business teams, and more, the organizations making progress are establishing shared ownership of governance and business outcomes.
The next leadership mandate
As organizations move from experimentation to enterprise adoption, the CIO mandate is expanding beyond technology operations and governance, which is now table stakes. Technology leaders are increasingly expected to help redesign business processes, elevate roles and work, orchestrate intelligence across human and digital systems, and connect AI investments directly to business value. Some CIOs are also tasked with leading enterprise-wide transformation and helping their organizations adapt to new ways of working. 
 
To get there, as Romack put it, organizations should "start with value and end with value." AI initiatives will increasingly be judged not by how many pilots are launched, but by how effectively they improve outcomes for customers, employees, and the business.
Continue the Conversation Explore additional executive perspectives from the ServiceNow Executive Circle community on AI leadership, transformation, and business value, and watch the full WSJ Technology Council Summit mainstage discussion. Explore Executive Insights Watch the Full Discussion