Akanksha Pandey is a Director Analyst advising CIOs and AI leaders on how to manage technology spend as AI accelerates and democratizes technology decisions across the enterprise. At Gartner, Akanksha focuses on helping CIOs navigate the shift to business-led technology spending, where AI, cloud, and digital investments increasingly originate outside IT while accountability for cost and outcomes remains with the CIO.
Akanksha's work enables CIO's strengthen governance across enterprise-wide technology investments. She helps leaders improve accountability for cost and value, increase visibility into technology spend, and ensure investment decisions are grounded in realistic expectations. Her work focuses on enabling CIOs to manage AI-driven cost growth while maintaining financial discipline and supporting sustainable innovation.
Before focusing on CIO and AI leadership research, Akanksha developed a foundation in behavioral science and data-driven decision-making, which continues to shape her perspective on technology adoption and governance.
She was a Behavioral Insights for Policy Fellow at the Centre for Social and Behaviour Change, where she applied behavioral science to real-world problems, focusing on how incentives, context, and decision environments influence outcomes. This experience informs her current work, particularly in understanding why AI adoption and cost challenges are often behavioral, not just technical. Earlier, Akanksha worked as a Consultant with Nine Dot Nine Mediaworx, where she analyzed digital learning adoption and user behavior to improve program effectiveness, building early insight into how technology scales across users.
She also worked with the University of Chicago Center in Delhi, supporting growth strategy through data analysis and stakeholder communication. This strengthened her ability to translate data into clear, actionable insights for decision-making.
Technology Financial Management
Managing AI-driven technology costs as adoption accelerates across the enterprise,
Governing technology investments across the organization
Creating clear accountability for technology costs and business outcomes
Improving visibility into enterprise-wide technology spend and value
Behavioral implications of AI that stall adoption and scaling