👥 Featuring:
Host: Alex (The Strategy Stack)
Opening & Setup (Part 6 — Implementing and Scaling the AOM)
Alex opens the final session of the initial Agentic Operating Model (AOM) series, focusing on execution and growth. This part moves from theory and value creation (Part 5) into the practical steps to implement and scale agents across an enterprise.
Context: Part 6 concludes the core AOM series, setting the stage for future discussions on multi-company agent ecosystems.
Why Implementations Fail
Most AOM initiatives don’t fail because of technology — they fail due to execution errors and organizational misalignment:
Treating AOM as just a tech project → systems are technically correct but disconnected from business outcomes.
Weak governance → lack of clear rules causes trust breakdown before scaling.
Starting too big → trying to launch too many agents at once creates chaos and fragmentation.
Isolated agents without memory → no shared context prevents collective learning.
Best practice:
Create joint ownership between business and tech teams, establish policy-as-code, start small and focused, and build a shared memory layer early
The Four Phases of Implementation
Phase 1 — Foundation (Months 0–3)
Map decision bottlenecks and high-friction workflows.
Encode strategic intent (goals, constraints, success metrics).
Build a minimal viable memory layer to unify data.
Form an Agentic Governance Council spanning strategy, tech, compliance, and ops.
Phase 2 — Pilot (Months 3–6)
Deploy 2–3 interconnected agents within one domain.
Run in shadow mode: agents recommend actions, humans execute.
Launch transparency dashboards for visibility.
Train staff on oversight and escalation processes.
Phase 3 — Scaling (Months 6–12)
Expand into adjacent domains while standardizing APIs and vocabularies.
Implement tiered autonomy (low → high risk).
Introduce enterprise-level KPIs like autonomy ratio and decision speed.
Use playbooks and a central scaling team to manage rollouts.
Phase 4 — Continuous Evolution (Year 2+)
Agents analyze their own performance and suggest workflow improvements.
Governance evolves into a strategic decision layer.
Integrate with external agent networks for partnerships.
Continuously add new domains and business models.
Choosing the First Pilot Domain
Criteria for selection:
High impact, contained complexity
Clear metrics (e.g., “reduce handling time by 20%”)
Manageable risk (avoid highly regulated areas early)
Engaged stakeholders eager to innovate
Example: a telecom provider modernizes customer onboarding in a single region, aiming for a 15% activation rate increase.
Scaling Models
Three primary approaches:
Hub-and-Spoke → centralized core team with distributed business-unit deployments.
Domain Wave Expansion → deep expertise in one domain, then expand sequentially.
Network-First Scaling → early focus on cross-functional agents spanning multiple departments.
Best practice:
Standardize data vocabularies early to enable agent interoperability.
Governance & Trust at Scale
Policy-as-code → encode compliance and ethics directly into agent operations.
Tiered autonomy levels (0–3) → from proposing actions to full autonomy with monitoring.
Transparency dashboards → real-time visibility of agent decisions.
Ethics oversight board → prevent bias and systemic risk.
Update rules quarterly and maintain full traceability for regulators and stakeholders.
Measuring Success & ROI
Key metrics:
Cost per decision → operational efficiency.
Signal-to-action latency → organizational agility.
% decisions made by agents → cognitive leverage.
Model improvement rate → learning and intelligence growth.
Revenue from agent-driven initiatives → innovation yield.
Successful escalation rate → governance health.
Looking Ahead: Multi-Company Agent Ecosystems
By 2030, up to 40% of enterprise agents will interact across multi-company networks:
Healthcare clusters → shared diagnostic agents for coordinated care.
Retail ecosystems → connected inventory agents balancing global supply and demand.
Banking coalitions → shared fraud detection networks.
90-Day Action Plan
Weeks 1–4: Establish governance council, map bottlenecks, and build minimal memory layer.
Weeks 5–8: Launch initial agents in one domain, operate in shadow mode, gather feedback.
Weeks 9–12: Review, refine playbooks, and prepare for next domain rollout.
Key Takeaways
Success requires disciplined execution, not just technology.
Start small, prove value, scale systematically, then evolve continuously.
Governance and trust are the foundation for sustainable agent networks.
Each new agent should strengthen the entire system, creating a continuously learning organization.
Hit subscribe to get it in your inbox. And if this spoke to you:
➡️ Forward this to a strategy peer who’s feeling the same shift. We’re building a smarter, tech-equipped strategy community—one layer at a time.
Let’s stack it up.
A. Pawlowski | The Strategy Stack
