Executive AI leadership

I build AI operating models that move enterprises from ambition to governed production delivery.

Architected Centrilogic's AI Factory and the COE, Landing Zone, and Agent Factory patterns behind it, then used those foundations to help teams deliver governed AI in regulated enterprise environments.

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"When architecture drives outcomes and challenges demand clarity, Dave Manning is the person I trust to lead."
Lokesh Kumar Padmanaban, Cloud Solutions Architect
Dave Manning
20+ years

Enterprise Transformation

Architecture, Strategy, and Delivery Leadership

AI Factory

AI Operating Model Architect

COE, Landing Zone, and Agent Factory Patterns

3 director roles

Leadership Progression

Architecture, Consulting, and Technical Strategy

Regulated + F500

Trust Environments

Financial Services, Public Sector, and Enterprise Delivery

Mandate

The differentiator is not whether I have worked with AI. It is whether I can define the system that decides what gets funded, how risk is governed, how teams execute, and how results hold up under scrutiny.

Executives do not need another polished online resume. They need evidence that a leader can connect strategy, governance, architecture, delivery, and team development into a durable AI capability.

That is the role I play: translating business ambition into a governed operating model, then helping teams use that model to ship production systems with clarity, repeatability, and executive confidence.

Why this matters

From strategy deck to delivery system.

The strongest signal for an SVP-level audience is not the breadth of keywords. It is visible judgment about what to standardize, where to govern, and how to scale AI delivery without losing trust.

  • Operating model ownership, not just project participation
  • Named strategic artifacts with delivery consequences
  • Technical depth that still reads clearly at executive altitude

Build the operating model

Design the structures that let executives fund AI with confidence and let delivery teams execute repeatedly.

AI Factory delivery modelAI COE frameworkAI Landing Zone and Agent Factory patterns

Lead governed production delivery

Translate architecture, governance, tooling, and business priorities into AI systems that hold up in production.

Genesys + Salesforce + Azure OpenAI contact-centre agentRole-based GenAI knowledge assistant for regulatory contentAudit-ready workflows in regulated environments

Grow teams executives can trust

Recruit, coach, and align architects while connecting technical depth to proposals, SOWs, and executive decisions.

Architecture practice leadershipProposal and SOW ownership on strategic accountsBusiness translation across AI, cloud, and enterprise transformation

Industries

Financial servicesPublic sectorManufacturingTechnologyEducation

Transformation patterns

AI operating modelsProduction agentsKnowledge systemsContact-centre transformationEnterprise roadmapsRFP and SOW automation

What leaders hire me for

Standing up an AI practiceMoving from pilots to governed productionBuilding executive confidence in architecture decisionsCoaching architecture teams through change

Operating Model

The system behind repeatable AI delivery.

This is the proof surface that matters most to an executive audience: not just what shipped, but the operating logic that lets teams ship under governance, budget pressure, and real stakeholder scrutiny.

Mandate and portfolio alignment

The operating model starts by deciding what deserves investment, where risk needs to be managed, and how success will be measured across a portfolio of use cases rather than a series of isolated pilots.

What executives need

  • Prioritized use-case portfolio tied to business value
  • Governance posture aligned to regulated environments
  • Roadmaps executives can sponsor, defend, and sequence

What delivery teams get

  • Bid and no-bid discipline for internal demand
  • Shared operating metrics for velocity, quality, and auditability
  • Clear language across sponsors, architects, and delivery leaders

Grounded in prior proof

  • Enterprise IT roadmaps delivered across financial services, public sector, and manufacturing
  • Technical detail translated into proposals, SOWs, and program direction

Contact

The best-fit conversations are about standing up an AI capability, fixing the gap between strategy and delivery, or evaluating whether executive AI leadership is needed now.

  • Standing up an AI practice or operating model
  • Moving enterprise AI from pilots to governed production delivery
  • Hiring a strategic leader for architecture, AI, or transformation
  • Connecting executive sponsorship to technical execution and measurable outcomes

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