Stephanie McReynolds is a Sr. Director Analyst in the cost and value team at Gartner, focused on research for CIOs and AI leaders. Her research covers how organizations create, measure, and sustain business value from AI and how AI is reshaping enterprise cost structures. Stephanie is a seasoned business and technology professional, with significant expertise in emerging technology markets and AI.
Before joining Gartner, Stephanie served as a go-to-market executive responsible for marketing and product management at high growth start-ups in the AI Governance, Data Governance, Analytics, and Data Infrastructure markets.
Stephanie has a track record of bringing new products to market, as well as leading category creation initiatives. She joined Gartner from governance vendor, OneTrust, where she led product marketing for their core products. Prior to OneTrust, Stephanie started the marketing teams at Ambient.ai and Alation. Stephanie was recognized for creating the Data Catalog market category while leading marketing at Alation.
Earlier in her career, Stephanie led product management teams at Oracle and PeopleSoft, focused on analytic technologies spanning databases, integration, & business intelligence.
OneTrust, Vice President of Product Marketing, 2 years
data.world, Chief Marketing Officer, 1 years
Ambient.ai, Head of Marketing, 1 years
Alation, Senior Vice President of Marketing, 5 years
Trifacta, Vice President of Marketing, 1 years
ClearStory Data, Vice President of Marketing, 2 years
Teradata, Senior Director of Product Marketing and Technical Marketing, 2 years
Oracle, Director of Product Management, 7 years
Business Objects, Senior Product Marketing Manager, 1 years
E.piphany, Senior Product Marketing Manager, 2 years
Cost and Value Management
M.A., International Policy Studies, Stanford University.
B.A., International Relations, Stanford University.
AI Investment & Portfolio Strategy, focused on investment strategy; initiatives/use case selection; portfolio management
AI Value Thesis, focused on types and sources of value form AI; enterprise outcomes
AI Value Scaling, focused on initiative/use case selection; go/no go decisions; governance and guardrails
AI Value Realization, focused on value measurement; value optimization; value communication
AI Cost Management, focused on cost visibility; cost governance, controls, and guardrails