Noise // Signal
AI Enablement & Productivity Transformation
Client: Confidential Mid-Market SaaS
Engagement: AI Strategy · Tool Enablement · Change Leadership · Measurement Framework
Principal: Mike Van Amburg
Context
When I arrived, the organization had no structured AI adoption and no metrics for productivity. Teams were still operating on manual workflows, with inconsistent visibility into efficiency or output quality.
The leadership team wanted to “use AI,” but lacked a strategy, guardrails, or a way to quantify benefit.
Objective
Establish an AI-enablement program that measurably improves productivity, upskills employees, and builds an internal capability to sustain compounding gains.
Intervention
I led a three-phase initiative:
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Discovery & Baseline – Audited team workflows and created a baseline productivity model covering development velocity, QA throughput, and meeting-to-execution lag.
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Enablement & Training – Delivered multiple company-wide AI teaching events and focused tool-enablement sessions for engineering, design, and operations. Introduced prompt-engineering practices, context documentation standards, and safe-use frameworks.
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Leadership & Governance – Worked directly with the C-suite and senior leaders to define a top-down AI strategy, integration roadmap, and KPI framework. Embedded AI performance metrics in quarterly OKRs and instituted “AI champion” roles within each team.
Outcomes
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Productivity uplift: ≈ 30 % increase in output across tracked teams within the first quarter.
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Future potential: early-stage process automation and workflow-pattern reuse expected to drive additional double-digit gains over 12 months.
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Capability building: 100 % of senior leaders trained on AI decision frameworks; > 70 % of staff actively using AI tools in daily work by project close.
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Cultural impact: Shift from “AI curiosity” to AI competence — every team now has measurable goals tied to intelligent tooling adoption.
Why it matters
This engagement proved that sustainable AI adoption starts with education, structure, and measurement, not tools alone.
The company now runs on a living AI-enablement framework that compounds productivity and serves as the foundation for future automation and data-driven decision-making.