Technical Paper
Strategies for Aligning Client Expectations With Measurable Outcomes
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Summary
Generative AI projects often struggle with adoption due to limited client understanding, unrealistic expectations, and difficulty measuring outcomes. This paper presents a structured framework to align technical solutions with client needs through measurable impact, responsible AI, and data security. It offers practical strategies, case studies, and tools for lifecycle planning and ROI quantification to drive successful GenAI adoption.
Key Highlights
- GenAI Alignment Model: A 4-phase framework to align client goals with AI capabilities through education, pilot KPIs, outcome quantification, and governance.
- ROI Measurement Tools: Uses KPIs and impact scores to link GenAI outputs to business value, enabling clear ROI estimation.
- Trust & Responsibility: Emphasizes bias mitigation, data privacy (e.g., GDPR), and explainability to foster responsible and secure adoption.
