A Canadian Financial Services Firm Built a Board-Ready AI Transformation Narrative in 90 Days
How the full diagnostic-to-coaching engagement produced a quantified ROI story that changed the executive conversation about AI adoption.
Financial Services
~1,400 employees
90-day embedded engagement
NDA Protected
NDA Notice: This case study represents a composite of engagement outcomes. Company name, location details, and identifying information have been redacted under NDA. Metrics are representative of actual diagnostic results.
$312K
Annual recoverable value identified
The Challenge
This 1,400-person financial services company headquartered in Toronto had committed $4.2M annually to AI transformation across operations, compliance, and client services. The board was asking for ROI evidence. The CTO had utilization data showing 73% adoption. The CHRO had engagement data showing stable morale. But neither could explain why productivity gains were not materializing at the rate the vendor projections promised.
- $4.2M annual AI tooling investment across operations, compliance, and client services.
- 73% adoption rate as measured by license utilization.
- Board requesting quantified ROI narrative for next funding cycle.
- The projected 22% productivity gain had materialized at only 8% after 18 months.
- No single team or function identified as the bottleneck; the gap was distributed.
- The CHRO and CTO were presenting contradictory narratives to the board.
The Diagnostic
CultureGuard deployed the full 90-day engagement: a 30-day Energy Leak Detector diagnostic across all three divisions (1,400 employees), followed by 60 days of targeted coaching for the highest-impact managers. The unique challenge here was producing a board-ready narrative that quantified where the AI investment was leaking and what it would cost to recover it.
Process
- 1Read-only metadata scan across Microsoft 365 and Jira for all three divisions.
- 230-day classification of 1,400 employees into behavioral archetypes.
- 3Cost-allocation model: mapping AI license spend to each archetype cohort.
- 4Identification of “recoverable value” – spend allocated to overloaded/masking employees.
- 560-day coaching engagement targeting 12 managers across operations and compliance.
- 6Board-ready report generation with archetype cost breakdown and recovery projections.
Archetype Findings
The diagnostic revealed a clear pattern: the “missing” productivity was concentrated in two archetype cohorts. AI Overload employees (33%) were consuming licenses at high rates but converting at diminishing returns. AI Masks (24%) were maintaining the appearance of productivity while their actual output had plateaued. Together, these two groups represented 57% of the workforce and consumed 64% of AI license spend.
Key Insight: The 57% of employees classified as AI Overload or AI Mask consumed 64% of AI license spend ($2.7M of $4.2M) while delivering only 38% of measurable output gains. The Quiet Multipliers (15%) delivered disproportionate value – 31% of output gains – while consuming only 9% of license spend. This data reframed the board conversation from “Is AI working?” to “Who is AI working for, and why?”
Outcomes
The 90-day engagement produced three deliverables: a behavioral map of the entire organization, a cost-allocation model showing where AI spend was leaking, and a board-ready narrative quantifying recoverable value. The coaching phase targeted the 12 highest-leverage managers, producing measurable shifts within the engagement window.
$312,000
Annual recoverable value
AI license spend that is reallocatable through archetype-targeted interventions.
89
Employees reclassified post-coaching
Employees whose behavioral archetype shifted from Overload/Mask to Amplifier after manager coaching.
14% to 19%
Productivity gap closed
Measured productivity gain moved from 8% toward the 22% projection within 90 days.
Q2 2026
Board narrative delivered
Complete cost-allocation model with recovery projections presented to the board.
Timeline: 90-day embedded engagement (30-day diagnostic + 60-day coaching)
"For 18 months, we had a CTO saying AI was working and a CHRO saying people were fine. CultureGuard gave us the missing layer: who specifically was struggling, why it was costing us money, and what to do about it. The board finally had a story that made sense."
-- Chief Operating Officer (redacted)
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