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AI that actually ships

 

As a trusted advisor, I help leaders and teams navigate AI adoption thoughtfully, ethically, and effectively, with a focus on real-world impact.

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I provide pragmatic AI strategy, governance, and delivery support for organizations ready to move beyond pilots and into production.

 

Most organizations do not have an AI problem. They have a delivery problem. I help organizations move AI from experimentation into production responsibly and at scale, reducing wasted effort, risk, and stalled adoption.

Former Head of Engineering with decades of consulting and delivery experience helping organizations adopt and scale AI in regulated and mission-driven environments. I have led teams to move from AI experimentation into production-grade systems, establishing architecture, delivery practices, and operational governance that hold up in real world use.

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*BloomShift also offers career coaching, including support for leaders navigating AI-driven change. If you’re looking for career coaching, please use the top navigation.

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From AI experimentation to production delivery

Led a 40-person engineering organization from AI experimentation to production delivery, establishing repeatable architecture, delivery discipline, and AI-assisted engineering practices.

Enterprise AI discovery with credible paths to production

Led cross-functional teams delivering GenAI and automation prototypes with architectural rigor, facilitating discovery and design workshops that shaped credible paths from exploration to production.

AI systems in high-stakes, multi-vendor environments

Provided technical leadership on a large-scale, multi-vendor system with 80+ integrations across 30+ systems, directing architecture and delivery planning to reduce risk in a highly regulated environment.

Selected delivery experience (anonymous)

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What makes my approach different

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AI is a platform shift. I have led teams through previous platform shifts, including the move to Web 2.0 and the emergence of smartphones, and I bring that experience to AI adoption today.

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What you get:

  • A rare combination of technical depth and business leadership

  • Experience leading teams to build and launch AI into production

  • The ability to translate between executives, legal, security, and engineering

  • A pragmatic, no-nonsense approach focused on outcomes and risk reduction
     

I am not a software vendor, and I am not here to sell tools. I am here to help you make better decisions.

Engagements and timelines

Organizations typically start with an assessment or workshop, then expand into delivery once priorities are clear.

I offer clearly defined AI engagements with specific scopes, timelines, and outcomes.

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AI Maturity Assessment

Strategic assessment

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Duration: 3 to 4 weeks

Purpose: Establish a shared, fact-based understanding of your AI readiness across both business and technology.

Typical outcomes

  • AI maturity assessment across strategy, data, technology, people, and governance

  • Clear gaps between leadership expectations and current capabilities

  • Prioritized roadmap with concrete next steps

  • Executive-ready summary for decision-making

 

AI Use Case Workshop

Strategy and prioritization

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Duration: 1 to 3 full-day workshops, Written report delivered the following week

Purpose:  Identify which AI use cases are worth pursuing and which should be deprioritized.

Typical outcomes

  • Shortlist of viable, high-impact AI use cases

  • Clear prioritization rationale tied to ROI, risk, and readiness

  • Early identification of data, governance, and delivery dependencies

  • Written recommendations and next steps

 

AI Tooling Selection

Advisory

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Duration: 2 to 3 weeks

Purpose:  Select the right AI tools for day-to-day use without creating security, privacy, or adoption issues.

Typical outcomes

  • Stakeholder and team interviews

  • Workflow and usage analysis

  • Independent, vendor-neutral tooling recommendations

  • Clear explanation of trade-offs and adoption implications

 

AI Education and Culture Enablement

Enablement and change management

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Duration: 2 to 4 weeks

Purpose: Support AI adoption by addressing both skills and culture.

Typical outcomes

  • Employee adoption survey and listening sessions

  • Written report on concerns, risks, and adoption blockers

  • Customized AI training sessions

  • Follow-up training tailored to real employee feedback

 

AI Data Readiness

Foundational assessment

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Duration: 3 to 4 weeks

Purpose: Determine whether your data foundation can realistically support AI initiatives.

Typical outcomes

  • Data maturity and quality assessment

  • Identification of gaps blocking AI progress

  • Alignment analysis between business and technical teams

  • Prioritized roadmap for improving AI data readiness

 

Delivering AI to Production


Delivery and technical leadership


This engagement typically follows an assessment or workshop, once priorities and risks are clearly understood. This is a delivery engagement, not just advisory.
 

Duration: 4 to 20 weeks, depending on scope and complexity

Purpose: Move AI systems from experimentation into production safely and sustainably.

How this typically works

  • I provide technical leadership, architecture guidance, and delivery oversight

  • I work with your internal teams or bring in trusted partners for hands-on execution

  • Engagements are scoped around clear production goals, not open-ended experimentation

Typical outcomes

  • Production-ready AI application

  • Scalable, flexible architecture aligned to business needs

  • Delivery plan and rollout steps

  • Risk identification and mitigation planning

  • Post-production monitoring and model drift management

  • Post-production hypercare period

This engagement is appropriate when an organization is ready to commit to production delivery, not exploratory pilots.

 

Responsible AI Governance and Approval Process

Governance setup

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Duration: 2 to 3 weeks

Purpose: Make responsible AI operational without slowing innovation.

Typical outcomes

  • Responsible AI board structure

  • Clear intake and approval process for AI initiatives

  • Defined roles and accountability

  • Integration with legal, security, and leadership workflows

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​Book a 30-minute discovery call to pressure-test your current AI approach and identify where progress is being blocked.

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