Est. 2008

Chief Data Officer · India · Global perspective

September 2026 edition

Ishani Srinivasan

Making trusted data useful in consequential decisions.

Leading article

Making trusted data useful in consequential decisions.

By Ishani Srinivasan · Chief Data Officer

I help enterprises turn data into a trusted part of how decisions are made. My work spans ownership, quality, analytics and responsible AI, with a focus on the business practices that allow technical capability to be used well.

I begin with a decision and the people accountable for it. Understanding their information needs helps identify which data matters, where its limitations sit and who must own its quality. Governance should make those responsibilities workable rather than add a parallel layer of administration.

I bring business owners, technologists and risk colleagues into the same conversation. A useful data strategy is one the organisation can explain, operate and challenge when circumstances change.

Continued on the profile page →

From the desk of Ishani

Trusted data becomes valuable when people can use it responsibly in a decision. I connect ownership, quality and analytical capability to business purpose, with explicit limitations and human accountability for consequential uses.

— Ishani Srinivasan

In this edition

Data governance

Data ownership must resolve a real problem

Naming an owner is only useful if that person can make the decisions needed to keep information fit for purpose.

Data governance · September 2026 · 2 min read

Dispatches from practice

Case 01

Enterprise data ownership

Business functions were maintaining different versions of a critical performance measure. I worked with the accountable owners to define the measure, document its source and agree how exceptions would be handled. The programme treated data ownership as an operating responsibility and gave users a visible path for resolving quality issues.

Case 02

Decision intelligence

An analytics initiative had produced technically sound outputs that were not part of the management routine. We redesigned the work around a specific decision, involved the decision owners in evaluation and made limitations visible in the way findings were presented. Adoption became part of the delivery definition.

Case 03

Responsible AI adoption

Teams wanted to move AI experiments into business use without a consistent review process. I convened product, data, risk and operating leaders to agree evaluation criteria, human accountability and monitoring responsibilities. The approach allowed use cases to be assessed on their actual purpose and exposure rather than on enthusiasm for the technology.

The full record of leadership work →

Appointments

Westmoor Housing FinanceIndependent Director · 2023 — Present

The Responsible Data InstituteAdvisory Board Member · 2020 — Present

Honours

Data Leader of the YearThe Applied AI Forum · 2024

Responsible AI AwardThe Technology Leaders Review · 2023

As reported in

The Applied AI Forum“Governing 220 models without slowing the business” · 2025

The Boardroom Review“The board's role in responsible AI” · 2024

The Leadership Ledger podcast“Episode 120 — Data people can trust” · 2023

The record

Chief Data OfficerAldermoor Group · 2020 — Present

Vice President, Data & AnalyticsFairhaven Holdings · 2016 — 2020

Head of AnalyticsWestmoor Housing Finance · 2013 — 2018

Lead Data ScientistLumen Payments · 2008 — 2013

Letters to the editor

“Made our data trustworthy enough to bet decisions on — and honest about where it was not.”
Hannah Clarke, Chief Executive, Westmoor Housing Finance
“The clearest voice on responsible AI in our boardroom.”
Vikram Sethi, Chair, Risk Committee

An invitation

Correspondence welcome.

Ishani welcomes conversations with boards, chairs, search advisers and editors.

Open to
  • Board appointments
  • Advisory roles
  • Speaking invitations
Write to Ishani

office@ishanisrinivasan.example