Insights from the WLPA Virtual Hackathon
The Workflow Learning and Performance Alliance (WLPA) recently hosted a virtual hackathon with a focused objective:
To determine where AI can best assist — or even reimagine — the “En” (Engage to Align) and “E” (Evaluate for Impact) stages of the EnABLE 5 Moments of Need® Design Methodology.
With nearly 20 learning and performance professionals collaborating live, the conversation wasn’t about replacing methodology with technology. It was about strengthening performance-first design with intelligent acceleration.
The insights were both practical and forward-thinking.
Why Focus on “En” and “E”?
EnABLE begins with “Engage to Align”, where business challenges and measurable performance outcomes are defined before any solution is designed. It concludes with “Evaluate for Impact”, where workflow data is gathered and analyzed to confirm business results.
These two stages determine whether L&D is viewed as:
- A content provider
or - A strategic performance partner
The hackathon explored how AI could reduce friction, increase diagnostic precision, and improve measurement rigor within these critical phases.
AI in “Engage to Align”: From Administrative Lift to Strategic Leverage
Participants quickly identified that much of the time spent in “Engage to Align” involves preparation, synthesis, and documentation.
AI was seen as a powerful accelerator in five primary areas:
- RIA Impact (RIA) Preparation & Communication
AI can draft:
- Rapid Impact Analysis (RIA) invitations
- Stakeholder expectation-setting emails
- Executive-ready slide decks
- Follow-up summaries
This doesn’t replace the RIA conversation, but it reduces preparation overhead so designers can focus on performance analysis.
- Document & Workflow Extraction
Before alignment discussions even begin, designers often sift through policies, reports, and operational documents.
AI can:
- Convert long documents into concise briefing reports
- Extract tasks and processes from text
- Identify resources mapped to workflows
- Surface potential bottlenecks
This directly supports EnABLE’s workflow-centric analysis approach.
- Performance Gap & Root Cause Analysis
Participants saw strong potential for AI to:
- Analyze operational data and logs
- Identify trends and quality dips
- Draft potential root cause hypotheses
- Prioritize challenges against business goals
Instead of relying solely on stakeholder opinion, AI can introduce data-informed diagnosis early in the process.
- Forecasting Outcomes & Business Impact
AI can model:
- Performance improvement scenarios
- KPI movement projections
- ROI forecasts
This strengthens executive alignment by connecting design conversations directly to measurable business outcomes.
- Stakeholder Engagement & Recommendation Framing
AI can help generate:
- Persona-based recommendations
- Solution mockups
- Structured recommendation options
The result? Faster alignment and clearer communication with decision-makers.
AI in “Evaluate for Impact”: From Reporting to Intelligence
If “Engage” defines value, “Evaluate” proves it.
Participants identified AI’s strongest contribution in moving measurement beyond static reporting.
- Large-Scale Data Parsing
AI can rapidly analyze:
- Survey comments
- Free-response feedback
- Usage data
- Qualitative performance indicators
This dramatically reduces manual coding and speeds insight generation.
- KPI & Indicator Development
AI can assist in:
- Suggesting leading and lagging indicators
- Recommending adoption and impact measures
- Aligning metrics with business priorities
This supports more disciplined measurement planning.
- Real-Time Performance Monitoring
One of the most forward-looking ideas was AI-powered dashboards that:
- Flag performance dips proactively
- Suggest mitigation strategies
- Alert L&D to emerging risks
This transforms “Evaluate for Impact” from retrospective reporting to ongoing optimization.
- ROI & Impact Modeling
AI can suggest optimization opportunities and forecast impact scenarios, strengthening L&D’s business case by combining:
- Usage data
- Performance metrics
- Business outcomes
The Strategic Takeaway
One of the hackathon group’s executive summaries captured the opportunity clearly:
AI can transform the RIA process from a labor-intensive consulting exercise into a scalable, data-driven, and repeatable system — reducing cycle time and strengthening the connection between learning interventions and measurable business outcomes.
But an important theme emerged: AI is not the methodology. EnABLE remains the strategy. AI is the accelerator.
When integrated thoughtfully, AI:
- Reduces administrative load
- Improves diagnostic rigor
- Enhances measurement precision
- Increases stakeholder confidence
- Shortens cycle time
Most importantly, it strengthens the performance-first discipline that defines EnABLE.
Final Reflection
The hackathon reinforced a powerful idea:
The future of performance consulting is not human or AI. It’s human expertise amplified by intelligent systems. When EnABLE’s structured, workflow-centric methodology is combined with AI’s speed and pattern recognition, L&D gains something more than efficiency. It gains performance intelligence, and that moves us closer to what matters most: measurable business impact at every moment of need.
What’s Next for WLPA Members?
- Attend the March 17th MeetUp about AI & Performance Efficiencies: Sign Up Here!
- Consider attending the 5 MoN Summit 2026, April 21-22! Click here for details!