Frazer, Ltd

ENTITY: Frazer, Ltd. (Frazer EMS / Custom Emergency Vehicles)

INDUSTRY: Emergency service vehicle manufacturing (EMS, ambulances, mobile clinics, mobile stroke units)

REGION: Houston, Texas (North America / U.S.)
SIZE: ~317 employees (as evidenced in adoption scorecard)

ENGAGEMENT: AI governance + enablement program (AI Council cadence + Office Hours + training + adoption tracking)

SCOPE: Stand up an AI operating cadence and measurement layer for 2026 rollout:

• Establish AI governance structure (AI Council)
• Implement adoption + ROI tracking (scorecard + time-saved KPI + project/wins logging)
• Prioritize and manage use cases via a unified intake + tracking workflow (AI Tracker)
• Enable teams through AI Day training + ongoing office hours

TRANSFORMATION: Moved from “AI interest / ad-hoc usage” toward a measured, governed adoption program with:

• A visible adoption baseline (users, adoption %, projects)
  
• A quantified ROI lens (hours saved)
  
• A repeatable operating workflow (intake → tracking → review → wins reporting)
  
• A standardized workflow-capture method to fuel automation candidates (“Delegate & Elevate”)

STATUS: Verified reference (in-session evidence + meeting materials)
LAST UPDATED: January 2026 (most recent KPI snapshot shown in-session)

STAKEHOLDERS:

• Executive sponsor (Darren Ward referenced)
  
• Cross-functional AI Council participants (department leaders)
  
• IT/Ops + department owners (tracker mapped by department / ownership)

DELIVERABLE CATEGORY: Adoption measurement + governance/operating workflow + use-case intake + wins reporting

OPERATIONAL IMPACT SUMMARY: 

• Reduced manual effort and improved visibility into adoption progress and ROI by implementing:
  
• Adoption baseline + department rollups
  
• A projects/wins pipeline with quantified time-saved outcomes
  
• A governance cadence (AI Council + office hours) that reinforces consistent execution and accountability 
  
  OPERATING CONTROLS
  
• Clear cadence and ownership: AI Council operating rhythm + office hours
  
• Measurable outcomes: adoption %, active projects, hours saved, wins logged
  
• Structured intake and tracking: AI Tracker replaces scattered spreadsheets
  
• Repeatable workflow capture: “Delegate & Elevate” (record → SOP/process map → automation candidate)

REFERENCE TYPE: Organization engagement

• AI Day Training Package (recording + transcript + notes + attachments; distributed via calendar invite/shared drive)
• AI Adoption Scorecard (Frazer AI Council workbook view: employee base, GPT users, adoption %, active projects, hours saved; department rollups)
• AI Tracker / AI Council Tracker (system to log projects, wins, hours saved, action items; replacing spreadsheet)
• Wins (WIMs) logging framework (tool + department + time saved; one-time vs ongoing discussion)
• “Delegate & Elevate” process-capture methodology (record a workflow → SOP/process map → automation candidate)

7219 Rampart Street
Houston, Texas 77081

WEBSITE: https://www.frazerbilt.com/

• Adoption KPI baseline established: 317 employees; 86 GPT users; 27% adoption (at time of update).
• Delivery pipeline visibility: 5 active projects logged in sheet/workbook.
• Early ROI quantified (time-saved): 427 hours saved (estimated) from logged projects/wins to date.
• Win example (quantified): Safety training creation reduced from 4–5 hours to ~33 seconds (ChatGPT).

  WHAT THIS DEMONSTRATES

• Executive-ready measurement artifacts: Adoption scorecard + wins/time-saved KPI rollups + department-level segmentation.
• Operational intake + accountability workflow: AI Tracker replacing spreadsheet; projects/wins/action items in one system.
• Adoption planning through enablement: AI Day training package + ongoing office hours supporting standardized workflow capture (Loom → SOP → automation candidate)