About this book:

The book *Leading Work in the Age of AI* presents a practical playbook for leaders navigating the shift to AI-augmented and hybrid work. It argues that the fundamental unit of work is no longer the individual but the "human-plus-tool system," requiring a redesign of roles, rituals, and measurement to build productive, humane, and future-proof organizations.

The foundation of this new era is a "new work compact" centered on an "Automate, Augment, Protect" framework. Leaders must deliberately assign routine tasks to AI (Automate), use AI to multiply human value in judgment and creativity (Augment), and ring-fence work that requires empathy, ethics, and high-stakes decisions for humans alone (Protect). This requires shifting from managing activity to managing outcomes. This means redesigning roles around rising skills like problem-framing and prompt engineering, moving from annual training to continuous, just-in-time learning systems, and hiring for adaptive capacity—the ability to learn and reason—over specific tool knowledge.

To operationalize this shift, the book outlines strategies for designing hybrid work that actually scales. It advocates for a clear operating agreement that defines the purpose of the office (e.g., for high-bandwidth collaboration on "Studio Days") and elevates asynchronous communication as a primary mode. The default should be written work first, which makes decisions searchable and accessible across time zones. To combat "meeting sprawl," a clear taxonomy is proposed, distinguishing between Decision, Design, Alignment, and Ceremony meetings, and replacing many status syncs with written updates. The emphasis is on protecting attention and designing for clarity, not just convenience.

A practical roadmap for AI adoption is detailed, starting with a diagnostic of high-friction workflows rather than a search for tools. Success hinges on small, controlled pilots with clear hypotheses, guardrails, and a mix of outcome, adoption, and quality metrics. A structured evaluation rubric helps leaders decide whether to scale, adjust, or stop. The book stresses integrating AI into existing systems rather than adding more tools, and decommissioning what is replaced to avoid "tool sprawl." Governance is not an afterthought; it’s a lightweight, risk-based system of checklists, human-in-the-loop checkpoints, and audit trails that makes fast movement safe.

The book covers core management practices adapted for this new reality. Performance measurement must shift from busyness (tickets closed, reports written) to outcomes (resolution quality, cycle time, decision clarity). Hiring and onboarding should focus on adaptive capacity, using scenario-based interviews and 30/60/90-day plans to accelerate contribution in a remote environment. Data practices are elevated to a leadership responsibility, with clear ownership, quality metrics, and bias checks. Legal and compliance are integrated from the start through vendor diligence, transparent policies, and clear escalation paths. Customer-facing AI requires careful design, focusing on transparency, graceful escalation to humans, and quality control that builds trust rather than eroding it.

Finally, the book looks ahead to the next decade. It advocates for scenario planning to stress-test strategy against plausible futures—whether AI becomes a cheap utility, faces heavy regulation, becomes highly autonomous, plateaus, or drives specialization. Rather than trying to predict one future, the goal is to build resilient capabilities that work across scenarios: data readiness, governance clarity, learning agility, ecosystem flexibility, and human-centric design. Leaders should prepare by creating a resilience dashboard, tracking signals for different scenarios, and treating their organization as a learning system that can adapt as the landscape shifts. The core promise is that by focusing on human dignity, transparent systems, and continuous experimentation, leaders can build organizations that are not just productive, but resilient and humane.

What You'll Find Inside:

• A framework to categorize work into Automate, Augment, and Protect buckets, ensuring AI handles routine tasks while humans focus on judgment and empathy.
• Practical blueprints for designing hybrid operating agreements that prioritize asynchronous communication and intentional in-office 'Studio Days.'
• Step-by-step guidance on building an AI adoption roadmap, featuring 30/60/90-day pilot plans and objective evaluation rubrics.
• Leadership habits and coaching scripts designed to shift management focus from auditing AI outputs to developing human critical thinking and discernment.
• A comprehensive 'Leader’s Toolbox' filled with ready-to-use templates for role redesign, performance measurement, and ethical AI governance.

Who's It For:

This book is designed for business unit leaders, team managers, and HR or L&D professionals who need to move beyond AI hype and implement durable operating models. It is especially beneficial for those managing hybrid or distributed teams who want to future-proof their organizations through systematic role redesign and responsible automation. Founders and executives in mid-market companies will find the relentlessly practical templates and financial ROI models essential for scaling AI initiatives safely.