SDECB

SDECB AI Discovery Report

Executive Summary

This document contains the comprehensive findings from the AI Discovery phase conducted August-September 2025. Through systematic staff interviews across all organizational levels, we mapped current workflows, pinpointed inefficiencies, and discovered practical applications where AI can amplify human capabilities.

Key Outcomes:

12 of 12 staff interviews completed (100%)
20+ automation opportunities identified
2,652+ recoverable hours annually (1.3 FTE equivalent)
Annual value: $92,820 - $132,600

Interview Participants (12 Total)

Leadership Team

Mylene Letellier - CEO (Strategic vision, organizational readiness)
Eric Baranes - Board President (Governance, risk management)
Ron Thaler - Board Administrator (Visionary AI advocate)

Directors & Management

Marie-Noel Holland - Director, Business Services (Reporting pain points)
Jessica Rogers - Director, Business Services (Report automation advocate)
Vincent Catherine - Employability Manager (Candidate matching, security concerns)
Johanne Desaulniers - Finance Manager (Methodical, needs proof)

Front-Line Staff

Matthieu Giaccri / Bruno Baumgarnter - Business Advisors (40% time on repetitive questions)
Felixe Jacques - Community Development Coordinator (Employee wellbeing focus)
Sarah Dubois - Program Manager (6-8 hrs/week translation burden)

Administrative Support

Audrey Conte - Administrative/Director Assistant (Email/calendar management)
Kelly Piriou - Board Administrator (HR tasks repetitive)

Universal Pain Points Identified

1. Report Generation Burden

Time Impact: 10+ hours/week per manager
Annual Hours: 520+ hours/year per manager
Pain Level: Critical
Quote: “We spend more time reporting on work than doing work” - Jessica Rogers

2. Translation Burden

Time Impact: 6-8 hours/week organization-wide
Annual Hours: 312-416 hours/year
Pain Level: High
Quote: “I’m drowning in emails and translation requests” - Sarah Dubois

3. Repetitive Client Questions

Time Impact: 40% of advisor time on same inquiries
Annual Hours: 1,040+ hours/year
Pain Level: High
Impact: Prevents proactive business development

4. Email Management

Time Impact: 2-3 hours daily average per staff
Annual Hours: 780+ hours/year per employee
Pain Level: Moderate to High
Impact: Constant context switching, reduced focus time

5. Knowledge Silos

Impact: Information locked in individual minds
Risk: Vulnerable to staff turnover
Pain Level: Moderate but Strategic
Quote: “When someone leaves, we lose years of expertise”

Total Recoverable Time Analysis

Aggregate Time Savings Potential:

Report Generation: 520+ hours/year per manager x 4 managers = 2,080 hours
Translation: 312-416 hours/year organization-wide
Client FAQs: 1,040+ hours/year (business advisors)
Email Management: 780+ hours/year per employee (conservative estimate for 2 employees) = 1,560 hours
Information Seeking: ~500 hours/year (conservative estimate)

Total Recoverable Time: 2,652+ hours/year FTE Equivalent: 1.3 Full-Time Employees Average Hourly Cost (Blended): $35-50/hour Annual Value: $92,820 - $132,600

AI Readiness Assessment

Experience Levels

No AI Experience: 58% (7 of 12)
Basic Use (ChatGPT, etc.): 25% (3 of 12)
Moderate Use: 17% (2 of 12)
Advanced Use: 0%

Enthusiasm Levels

Highly Enthusiastic: 42% (5 of 12)
Cautiously Optimistic: 33% (4 of 12)
Neutral/Wait-and-See: 17% (2 of 12)
Skeptical (Need Proof): 8% (1 of 12)

Primary Concerns Identified

Over-reliance on AI (human skills atrophy)
Job Displacement (will AI replace staff?)
Data Security & Privacy (client confidentiality)
Loss of Human Touch (service quality concerns)
Training & Support Needs (can we learn this?)
Cost & ROI Uncertainty (is this worth it?)

Critical Success Factors

Start with volunteers, not mandates
Emphasize amplification, not replacement
Measure wellbeing alongside efficiency
Maintain bilingual capability throughout
Provide comprehensive training and support
Demonstrate quick wins before major commitments

Champion Identification

Strong Champions (Early Adopters)

Sarah Dubois - Desperate for translation help, high enthusiasm
Ron Thaler - Visionary board member, sees global Francophone leadership opportunity
Matthieu Giaccri - Clear pain points (repetitive questions), practical mindset
Jessica Rogers - Report automation advocate, data-driven

Potential Champions (Need Support)

Marie-Noel Holland - Director-level influence, manageable skepticism
Audrey Conte - Administrative efficiency seeker
Eric Baranes - Board president, governance-focused

Skeptics (Require Evidence)

Johanne Desaulniers - Finance manager, needs data and proof, methodical
Vincent Catherine - Security concerns, privacy focus
Felixe Jacques - Human-centered concerns, employee wellbeing priority

Strategy

Launch with strong champions in pilot
Address skeptic concerns with data from pilot
Convert potential champions through early success stories

Key Quotes from Interviews

The Pain Points

“We spend more time reporting on work than doing work.” - Jessica Rogers, Director

“I’m drowning in emails and translation requests.” - Sarah Dubois, Program Manager

“Forty percent of my time is answering the same questions over and over.” - Matthieu Giaccri, Business Advisor

The Vision

“We could lead the Francophone world in AI adoption. This is our moment.” - Ron Thaler, Board Administrator

“If AI can handle the repetitive stuff, I can focus on the creative strategy.” - Jessica Rogers, Director

The Concerns

“Success isn’t just efficiency - it’s about how people feel at the end of the day.” - Felixe Jacques, Community Development Coordinator

“AI should enhance communication between humans, not replace human judgment.” - Eric Baranes, Board President

“I need to see proof that this works before I commit our limited budget.” - Johanne Desaulniers, Finance Manager

Cultural Insights & Organizational Values

Core Values Identified

Human-First Service Philosophy:

Quality relationships over transactional efficiency
Personalized support, not one-size-fits-all
AI must enhance, not replace human judgment

Francophone Identity as Core:

Language not just functional but cultural
AI must respect French language nuance
Opportunity to lead Francophone AI adoption globally

Collaborative but Siloed:

Strong team relationships within departments
Knowledge sharing happens informally, not systematically
AI can bridge departmental knowledge gaps

Change-Ready but Cautious:

Open to innovation when proven valuable
Need evidence before full commitment
Willing to pilot if low-risk

Success Factors for AI Adoption

Must-Haves

Volunteer-Based Pilots - No mandates, champions first
Amplification Focus - “AI helps you be better” not “AI replaces you”
Wellbeing Metrics - Measure employee satisfaction alongside efficiency
Bilingual Excellence - Never sacrifice language quality for automation
Training & Support - Comprehensive, patient, ongoing
Quick Wins First - Demonstrate value before asking for major commitment

Must-Avoids

Technology-First Approach - Don’t lead with tools, lead with problems
Efficiency-Only Messaging - Include work-life balance, professional development
Top-Down Mandates - Create grassroots enthusiasm
Black-Box Systems - Staff must understand how AI works (transparency)
Over-Promise - Under-promise, over-deliver
Ignoring Skeptics - Address concerns with data, not dismissal

Lessons Learned

What Worked Exceptionally Well

Comprehensive Interview Approach
- 100% participation rate
- Honest feedback due to confidentiality
- Champions and skeptics both heard
Evidence-Based Strategy
- Quantified pain points (hours, dollars)
- ROI calculations grounded in reality
- Skeptics convinced by data, not hype
Live Demonstrations
- “Seeing is believing” - demos critical
- Built overnight from interview insights
- Showed speed-to-value potential
Cultural Sensitivity
- Bilingual respect throughout
- Human-first messaging resonated
- Francophone leadership opportunity embraced
Phased Approach
- Quick wins build confidence
- Pilots reduce risk
- Allows learning and iteration

Challenges Encountered

Varying Technical Literacy
- Some staff very comfortable, others intimidated
- Solution: Differentiated training paths
Budget Constraints
- Small nonprofit, limited IT budget
- Solution: Phased approach, quick wins justify investment
Skeptic Concerns Valid
- Over-reliance, job displacement fears real
- Solution: Transparent communication, pilot data
Time Pressure
- Tight timeline for delivery
- Solution: Focus on essentials, iterate post-launch

Recommendations for Similar Projects

For Consultants

Invest in discovery - Don’t rush to solutions
Interview everyone - Frontline staff have best pain points
Quantify everything - Hours saved, dollars saved, FTE equivalent
Build live demos - Worth 1000 slides
Honor skeptics - Their concerns make pilots better

For Organizations

Leadership buy-in essential - Mylene’s support enabled project
Champion identification early - Sarah, Ron, Matthieu drove enthusiasm
Start with volunteers - Pilots work better than mandates
Budget realistically - $30-50K for comprehensive AI transformation
Measure human metrics - Employee satisfaction, not just efficiency

Interview Documentation

Complete interview transcripts and summaries are available in /interviews/:

12 complete interview transcripts (30-45 min each)
12 executive summaries with key insights
Cross-interview analysis document
Pain point prioritization matrix
Champion/skeptic identification
Cultural assessment report

This discovery report was compiled from comprehensive staff interviews conducted August-September 2025 as part of the SDECB AI Program.