Talent in. Tech jobs out.

WIL runs the Training-to-Outcome Framework: a five-phase, AI-powered program that has taken 790 participants from first contact to a verified tech job across 5 cohorts and 2 programs. 82% interview rate. 8.03x government ROI. Open and replicable.

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790

Participants trained

Across 5 cohorts and 2 programs

82%

Interview rate with AI tools

vs. 2–5% industry baseline (16–40× improvement)

192

Jobs tracked within 12 months (DTTP 2.0)

Outcome verification with employer partners ongoing

8.03×

Government ROI over 10 years

Methodology and sources: 2025 Impact Report.

The framework

Five phases. One job.

Every cohort runs the same five phases: recruitment, training, mentorship, work experience, and AI-powered placement. The model is documented and open.

1
Targeted Recruitment & Assessment
2–4 weeks
Reach talent through inclusive community networks, then assess readiness and role fit using structured, merit-based evaluations.
Key activities
- Outreach through inclusive community partner networks
- Skills and motivation assessment
- Role fit and track placement
Equity-deserving share
82%
Women (DTTP 2.0)
49%
2
Cohort-Based Technical Training
12–16 weeks
Industry-aligned curriculum delivered by expert instructors and validated by employer partners. AI-assisted learning accelerates competency.
Key activities
- Track-specific curriculum (AI PM, Engineering, Data, UX, Cloud)
- AI-augmented practice, feedback, and code review
- Weekly employer talks and project critiques
Completion rate
75%
Completions
612
3
Mentorship & Community
Throughout program
Every participant is paired with industry mentors and a peer cohort. Mentorship is the strongest predictor of outcomes.
Key activities
- 1:1 industry mentor pairings
- Weekly group coaching
- Alumni network access
Mentorship participants
590
Attendance
87–94%
4
Work-Integrated Learning
4–12 weeks
Real client projects and hackathons give participants employer-validated work experience before they apply for jobs.
Key activities
- Employer-sponsored capstone projects
- Hackathons with judged deliverables
- Portfolio and case-study writing
Work placements
532
Placement rate
97%
Hackathon projects
160+
5
AI-Powered Job Placement
Up to 12 months post-program
AI tooling for resume, interview prep, and targeted applications produces an 82% interview rate (16 to 40 times the industry baseline) and 192 jobs tracked within 12 months.
Key activities
- AI resume and profile tooling
- Mock interviews with AI coaching
- Targeted employer introductions
- 12-month outcome verification
Interview rate
82%
Jobs verified (DTTP 2.0)
192+
Government ROI (10yr)
8.03×

Programs

5 cohorts, 2 programs, 790 participants.

The Diverse Tech Talent Program (DTTP) is WIL's flagship. DTTP 1.0 ran three cohorts in 2023 and 2024. DTTP 2.0 ran two cohorts in 2025 and added AI-powered job search.

DTTP 1.0

April 2023 – March 2024

The first large-scale proof that the Training-to-Outcome Framework moves talent to top employers. Fast.

DTTP 1.0 ran three cohorts from April 2023 to March 2024. 500 participants trained, 420 completed, 50 percent got jobs within four months of graduation. DTTP 1.0 is where we built and validated the Training-to-Outcome Framework.

Trained: 500+
Completions: 420
Employers: 55

Three cohorts: Product Management, Web Development, UX/UI Design
50 percent of graduates had jobs within four months
55 employer partners including University of Toronto, SE Health, and Critical Mass

DTTP 2.0

September 2024 – August 2025

Two AI-native cohorts. 82% interview rate. 192 jobs tracked within 12 months.

DTTP 2.0 ran two cohorts in 2025. We added AI-assisted job search, interview prep, and portfolio tooling to the framework. Participants hit an 82% interview rate (16 to 40 times the industry baseline) and 192 jobs tracked within 12 months.

Trained: 290+
Completions: 192
Employers: 32

Two cohorts: AI Product Management and No-Code & Web Development
82% interview rate using AI tools (16 to 40 times the industry baseline)
192 jobs tracked within 12 months (verification ongoing)

AI-powered placement

82% interview rate.

DTTP 2.0 participants used AI tools to build resumes, practice interviews, and target applications. The interview rate came in at 82%. The industry baseline is 2 to 5 percent.