May 18, 2026 · 24m · big-technology
How Agentic AI Changes The Workplace — With Jacqui Canney and Kellie Romack
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
Alex Kantrowitz interviews ServiceNow executives Jacqui Canney and Kellie Romack about deploying agentic AI across enterprise workflows, examining how automated agents scale productivity, drive workforce reskilling, and redefine governance without displacing employees.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Alex holds 29% of the talking time here. How this is scored →
Alex as informed peer 5.0 Guest teaching 4.4 Guest disagreement 1.4 Alex pushing back 4.0
speaking balance: gold is Alex, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 14:43 Jacqui dismisses the linear career assumption
Jacqui rejects the premise that employees still seek traditional linear career ladders, arguing that people want adaptable career paths and employers must prioritize agility over static roles.
Hardest push from Alex ▶ 16:10 Alex challenges redeployment as a precursor to layoffsAlex bluntly cuts through corporate jargon, asserting that employees view internal redeployment programs as merely delaying imminent layoffs.
Biggest teaching moment ▶ 11:05 Kellie breaks down the 90% autonomous IT service deskKellie provides concrete production numbers showing 90% automated ticket resolution and explains how 85% of staff transitioned into higher-value fields like SecOps and AIOps.
Alex holds their own ▶ 5:19 Alex reframes the practical nature of AI automationAlex synthesizes the conversation to clarify that enterprise automation delivers massive value by eliminating mundane internal data queries rather than building speculative AI sales agents.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Alex as informed peer | Guest teaching | Guest disagreement | Alex pushing back | Why |
|---|---|---|---|---|---|---|
| Scaling People Operations and Reallocating Capacity | 4 | 3 | 1 | 5 | Alex pushes back directly on Jacqui's claim about doubling capacity without layoffs, probing whether AI actually automated entire jobs rather than just tasks, and demands a concrete use case. | |
| Reimagining Workflows: The Sales Commission Transformation | 6 | 4 | 1 | 2 | Kellie and Jacqui detail how re-architecting sales commission inquiries cut resolution times from four days to eight seconds. Alex contributes sharp domain analysis, pointing out that valuable automation often removes internal administrative drag rather than deploying external AI salespeople. | |
| Upskilling Employees and Empowering Managers with AI | 5 | 4 | 1 | 4 | Alex challenges the training narrative by identifying middle management bottlenecks where ultra-productive individuals disrupt traditional team management. Jacqui validates this tension and explains how ServiceNow trains managers to provide psychological safety. | |
| Autonomous IT Service Desk and the Evolving Role of Managers | 6 | 6 | 2 | 4 | Alex introduces the Silicon Valley theory that AI will eliminate middle managers entirely, and later defines organizational models like the hourglass and diamond structures. Kellie counters with real-world data showing their IT desk shifted 85% of workers to higher-tier operations. | |
| Career Progression, Adaptability, and AI Competency Assessments | 5 | 5 | 2 | 6 | Alex confronts the corporate redeployment narrative with a sharp critique: 'redeploy today, lay off tomorrow.' Kellie and Jacqui counter by explaining their enterprise AI skill assessments and wide-career growth strategies. | |
| AI Control Tower, Governance, and Citizen Development | 5 | 5 | 2 | 5 | Alex refuses to accept that all AI use is centrally sanctioned, pushing on the reality of shadow IT. Kellie concedes the growing gray zone between citizen developers and core IT and explains their governance tower. | |
| Scaling Autonomous Support and Final Leadership Takeaways | 4 | 4 | 1 | 2 | Kellie outlines the stair-step progression from human-in-the-loop to human-on-the-loop in autonomous customer support, followed by concise leadership principles for navigating AI transformation. |
Statements from this episode (11)
Canney: ServiceNow scaled from 14K to 30K employees without adding HR headcount
“But out of that process and governance, we were able to come up with the use cases that deployed agents and AI into our people operations space, and it did double the output, more than double the output of what our people could do in people operations to serve…”
Romack: ServiceNow reduced commission inquiry time from four days to eight seconds
“It used to take four days. So we reimagined it. We put AI on it with security, and we did it in eight seconds. Four days to eight seconds.”
Romack: Enterprises must redesign workflows for AI rather than automate old processes
“Don't just take AI and shove it on top of what you already do on old process. Don't automate the old, reinvent to the new, and rethink how's a better way to engage in the business so we can get those higher value works.”
Romack: ServiceNow has achieved 95% internal AI adoption
“And that's how we have 95% adoption across the company with AI.”
Romack: AI resolves 90% of ServiceNow's internal IT tickets autonomously
“We were able to move 90% of everything that came through the IT service desk, 90, 90%, from first touch to resolution autonomously with AI.”
Romack: ServiceNow redeployed 85% of IT desk staff to higher-value roles
“We took 85% of those people, and we moved them to higher value jobs. We moved them to SecOps. We moved them to AIOps, right? We moved them to EBCs. And now I have 15%, and I'm coming back to the point of your, point that you made, we have 15% left on that IT s…”
Canney: Easier to teach AI-native hires the enterprise than vice versa
“We need people who can demonstrate they have the agility, they have the adaptability. We can teach them if they're AI native, which is like how we hire, we can teach them the enterprise. We can teach people a lot of things that maybe is easier to do than teach…”
Canney: ServiceNow assessed its entire company on role-specific AI capabilities
“We assess the whole company on AI capability. So that we knew, and we didn't use it as A scare tactic or anything like that. It was like, how to do better in your job. So each role, and the assessments were built around the roles that you had, so we didn't all…”
Romack: ServiceNow runs an AI Control Tower monitoring all internal agents in real time
“So we have a AI control tower that we can look at any point in the day, see how many AI agents are running, both ServiceNow and third party, what the adoption is, how, how people are using that, what the metric is, and what the values created, and what the lon…”