Most Important Takeaway

Enterprise platforms that serve as the workflow backbone across departments — connecting hyperscalers, language models, and systems of record — are not threatened by the AI wave but strengthened by it. Replacing a mature workflow platform with generated code costs roughly 10x more when you factor in GPU infrastructure, token costs, lost context, and the human capital diverted from other work. The winners in the AI era will be companies that act as the “AI control tower” integrating all the nodes of an enterprise, not those trying to rebuild existing platforms from scratch.

Summary

Actionable Insights and Key Patterns:

• AI augments platforms, it does not replace them. Language models answer questions; workflow platforms close cases. The distinction matters because businesses need deterministic outcomes that traverse multiple departments (HR, finance, legal, compliance) with full data context. Leaders should invest in AI that enhances their existing platform investments rather than attempting costly replacements.

• The “SaaS Apocalypse” is overstated for horizontal platforms but real for narrow tools. Companies serving a single department with low-value, easily replicated functions are vulnerable to AI-generated code. Horizontal platforms spanning the enterprise with deep integrations (ServiceNow claims 800+ system-of-record integrations) have a durable moat. Evaluate your software stack: if a tool is single-function and low on the CEO’s priority list, it is at risk.

• Implementation speed is a competitive weapon. ServiceNow reports major enterprise deployments going live in under 30 days, enabled by autonomous AI-native platform capabilities. This compresses the traditional months-long implementation cycle, letting customers run more projects faster rather than fewer projects slowly. When evaluating platforms, time-to-value should be a top criterion.

• Headcount growth will decouple from revenue growth. McDermott predicts companies will dramatically reduce net new hiring as AI agents take on tactical workloads. He notes 90% of ServiceNow’s customer service cases are now handled by agents. The career implication: differentiate your skill set so it cannot be easily replicated by an agent. Critical thinking, judgment, human relationship management, and trust-building remain human advantages.

• 2.2 billion AI agents entering the workforce soon. This will outnumber human workers in many contexts. Organizations should plan for a hybrid human-agent workforce and develop governance frameworks now.

• Enterprise AI adoption is still early but accelerating. Only ~11% of companies (using Brazil as an example) have moved past the experimentation phase. First movers are decisive: they want prescriptive, industry-specific guidance, fast deployment, and clear ROI — not discovery sessions. If you sell to enterprises, come with a point of view and a plan, not questions.

• Career advice from McDermott’s trajectory: Control what you can control — work ethic, desire, and willingness to learn. Build EQ through direct human interaction (he credits serving 500 customers a day at his deli). Never break a promise. Ask for the shot and make the most of it. Agency and leadership can be taught but must be practiced, not just studied.

• Security is a massive adjacent opportunity. Cybercrime is a $1 trillion/month problem. The convergence of IT and OT (operational technology) security — covering networks, devices, manufacturing tools, medical devices, and critical infrastructure — is becoming a platform play. Leaders should think about security holistically across both digital and physical assets.

• The hyperscaler precedent. The fear that cloud hyperscalers would “eat software” proved unfounded; they became partners and distribution channels. The same pattern is likely with LLM companies — they will be important but will not replace workflow platforms.

Chapter Summaries

The Deli Origin Story

McDermott bought a deli at 16 for $7,000 on a promissory note, consolidating multiple part-time jobs. He identified three customer segments (blue-collar workers, seniors wanting delivery, and kids drawn by arcade games) and learned that knowing your customer and treating them with dignity is the foundation of any business. The EQ built from 500 daily customer interactions proved more valuable than any formal training.

Getting the Shot at Xerox

McDermott’s defining career moment came when he refused to leave a Xerox interview without a job offer, telling the hiring manager he had never broken a promise to his father. The manager broke company policy to hire him on the spot. Twenty-five years later, that manager remained a close friend. The lesson: care deeply about people, recognize uniqueness, and give others their shot.

Leadership in the Age of AI

McDermott reframes the anxiety around rapid change as inspiration. He advises leaders to lean into disruption rather than seek escape hatches. He created a “Blueprint for Agentic Business” white paper to train his organization and customers on the distinction between language models and enterprise platforms, calling it “a big unlock” for CEO-level understanding.

Platform vs. SaaS and the “SaaS Apocalypse”

The key distinction: platforms span multiple departments and integrate hundreds of systems of record; single-function SaaS tools serve one department. Platforms have high switching costs and deep data context accumulated over decades. Attempting to replicate a platform with AI-generated code costs 10x more and loses the deterministic, contextual execution that enterprises require. Software mistakes are never forgiven the way human mistakes are.

The AI Control Tower Vision

ServiceNow positions itself as the central nervous system connecting hyperscalers, language models, systems of record, and data lakes. With the acquisitions of MoveWorks (agentic front door), Veza (identity), and Armis (OT security), the company integrated each in roughly 20 days. The zero-copy data architecture allows transactions across external systems without moving data.

Enterprise AI Adoption Today

Adoption varies by industry and geography. Financial services firms are moving fastest, healthcare is in modernization mode, and public sector is focused on consolidation. The US leads in AI consumption. Customers are impatient, decisive, and want prescriptive solutions — not exploratory workshops. They expect AI-driven outcomes with predictable, fast time-to-value.

The Future of Work and Headcount

McDermott predicts net new hiring will dramatically decrease even at growth companies. Agents will handle tactical workloads while humans focus on engineering innovation, relationship management, and judgment calls. The bar for human skill differentiation is rising. Companies that adopted AI should show expanding margins, improving revenue per employee, and re-accelerating growth.

Daily Life as a Global CEO

McDermott structures his day around time zones: Europe first, then the US, then Asia. He emphasizes direct customer and employee contact — 72 one-on-one calls with quota-carrying reps scheduled in one month alone. He closes with large-format leadership talks (800 Brazilian executives the previous evening), believing that uncertain times are when real leaders matter most.