Gartner Expert

Apurva Singh

Director Analyst

Apurva Singh is a Director Analyst supporting Infrastructure & Operations leaders in the data lifecycle management domain. She covers structured and unstructured data archiving, data retention, data discovery, data deletion, data storage management services and digital communication governance topics.

Although Apurva dedicates most of her time to the specific needs of Infrastructure & Operations leaders, she also provides advice to technology executives concerning emerging and innovative technologies, disruptive business models and market strategies.

Apurva leads pivotal research on governing Agentic AI and building Enterprise AI Platforms. She guides leaders in establishing risk-tiered autonomy, deterministic guardrails, and execution controls for AI.

Apurva's expertise along with Gartner's research are available to assist Infrastructure & Operations leaders to solve the complex challenges of protecting and managing data whether on-premises, virtualized, hybrid and/or cloud.

Previous experience

Prior to joining Gartner, Apurva held a progressive series of IT consultation roles across fintech, e-commerce, and IT.

Professional background

Ernst & Young, Senior Consultant, 2 years

Amazon, Manager, 1 years

Reliance Industries Limited, Manager, 4 years

Areas of coverage
  • AI, Cloud and Data Center Infrastructure

Education

Certified Information Security Manager

B.Tech(Computer Science)

Read More Read Less

Top Issues That I Help Clients Address

01

Use of Data Archiving solutions to address organization data retention requirements

02

Choosing technology to meet compliance and data discovery requirements

03

Quantifying & Managing Technical Debt: Utilizing the Technical Debt Interest Rate (TDIR) framework to measure legacy IT friction, transforming deferred maintenance into actionable investment

04

Helping clients choose data migration archiving strategy during application retirement

05

Governing Agentic AI for Safe Autonomy: Assisting I&O leaders in building deterministic guardrails, kill paths, and risk-tiered autonomy models.