A Decision-Based Metric Framework for AI-Driven Projects
Introduces the Decision Impact Score and Project Success Score to evaluate AI-driven projects through sequential decisions, failure propagation, and project-level outcomes.
Read on SSRN →
Enterprise AI · Decision Intelligence · Management
Turning enterprise AI ambition into measurable value.
I work at the intersection of enterprise technology, artificial intelligence, and decision systems connecting business needs, technology execution, adoption, and measurable outcomes.
VK
About
A practitioner-led perspective on how organizations adopt, measure, and scale technology.
Vinay Kumar Polamarasetty works across enterprise software, artificial intelligence, and decision systems. His work has contributed to large-scale initiatives spanning ERP, CRM, CPQ, analytics, and AI-enabled solutions across heavy-equipment dealerships in construction, agriculture, and mining. His focus is on translating complex business needs into systems, processes, and technology solutions that improve operational effectiveness at scale. Alongside his industry work, he researches how organizations can evaluate AI adoption, decision quality, and enterprise value.
Research
Frameworks for measuring enterprise AI adoption, project decisions, and business value.
AI Adoption as an Experimental System: A Framework for Measuring Enterprise AI Value
Examines enterprise AI adoption as an iterative system and introduces a framework built around adoption, implementation, and change readiness.
Read on SSRN →Measuring Enterprise AI Value: A Closed-Loop Framework for Adoption, Decision Intelligence, and ROI Optimization
EAVOF, the Enterprise AI Value Optimization Framework, connects adoption readiness, decision intelligence, and ROI optimization in a closed-loop model for enterprise AI.
What I am trying to solve
How can organizations move beyond isolated AI experimentation and measure whether their AI initiatives are creating durable operational and business value?
Book
A practical reflection on how management is evolving through the AI lens.
The Management Shift: Through the AI Lens
The book brings together practical observations on how project and product management are evolving in the age of AI, while keeping the focus on decision making, execution, and the human side of management.
View on AmazonManagement is not disappearing in the age of AI. It is becoming more intentional.
A concise book for practitioners navigating the changing relationship between people, decisions, systems, and intelligent tools.
Speaking
Sharing applied research on enterprise AI, decision systems, and management.
A Sequential Decision-Based Metric Framework for AI-Driven Projects
Accepted for presentation at the INFORMS Annual Meeting 2026. The talk focuses on evaluating AI-driven projects through sequential decisions, Decision Impact Score, Project Success Score, and failure propagation.