π― Determining Whether a Foundation Model Meets Business Objectives
To evaluate the true value of a foundation model, itβs essential to look beyond technical accuracy and assess whether the model is delivering measurable business outcomes. These outcomes vary based on the use case, such as productivity improvement, customer satisfaction, or automation.
π οΈ 1. Task Effectiveness (Task Engineering)β
π Definition:β
- Assess if the model completes the intended task accurately, efficiently, and with minimal human intervention.
π§ Questions to Ask:β
- Does the model follow the task prompt reliably?
- Can the model handle edge cases and task variations?
- Is the output actionable and correct?
π Example Metrics:β
- Task completion rate
- Error rate in task-specific outputs
- Manual correction rate
π 2. Productivity Gainsβ
π Definition:β
- Measure how the model reduces human effort or speeds up processes.
π§ Indicators:β
- Time saved per task or interaction
- Reduction in support tickets or manual review
- Number of tasks automated per user or team
π Example Metrics:β
- Average response time
- Tasks completed per hour
- Cost savings in labor or operations
π£ 3. User Engagement & Satisfactionβ
π Definition:β
- Evaluate how users interact with and benefit from the AI, especially in customer-facing or collaborative use cases.
π§ Signals:β
- Are users adopting and returning to use the GenAI application?
- Are users satisfied with the responses or experience?
π Example Metrics:β
- User satisfaction (CSAT/NPS)
- Session duration or return usage
- Drop-off or bounce rates in AI workflows
π§© 4. Alignment with Strategic Goalsβ
π Definition:β
- Determine whether the model supports broader business initiatives such as innovation, revenue growth, or customer retention.
π Examples:β
Business Goal | Model KPI Example |
---|---|
Improve customer support | First-contact resolution rate |
Enable content automation | Time to publish marketing material |
Enhance personalization | Conversion rate from AI recommendations |
β 5. Iterative Evaluation and Feedback Loopβ
π Importance:β
- Business needs and user behavior evolve. Continuous monitoring ensures that the model continues to drive value.
π Techniques:β
- Collect user feedback and corrections
- Monitor changes in KPIs after model updates
- A/B test models or prompting strategies
π Summary Checklistβ
Objective Category | Examples |
---|---|
Task Engineering | Completes task correctly and efficiently |
Productivity | Reduces time, effort, or cost |
User Engagement | Users adopt, enjoy, and trust the system |
Strategic Alignment | Supports key business KPIs |
Continuous Evaluation | Monitored and iteratively improved |
By aligning foundation model evaluation with business outcomes, organizations can ensure their GenAI investments deliver real-world impact β not just technical performance.