Mauro Flores

Chief Data & AI Officer / CDAO. Enterprise transformation and business value through data, AI and engineering.

"You cannot AI your way out of data you don't trust."

I help enterprises turn trusted data and AI into value the business and its customers can feel, and I lead the change in how a company decides so it lasts. An executive who has done the engineering, not just sponsored it.

Most recently EVP, Data Democratisation at Virgin Media O2; currently Strategic Advisor to The Information Lab's leadership team. Open to select CDO, CDAO and EVP Data and AI conversations, in the UK and internationally.

Email Mauro confidentially 3-page CV

EVP, VMO2 (£10bn) · 300+ data org · 11,000+ enabled · £23M attributed, circa £500M enabled · British Data Awards 2026 winner

Watch the 3-minute story Mauro Flores, senior Data and AI executive
EVP, Data Democratisation
Enterprise Data & AI Transformation Remit at VMO2
British Data Awards 2026 winner Transformational Leader 2026, Anaplan Anaplan Connect London 2026 keynote UK Government DSIT roundtable Google Cloud Next 2026 speaker See the evidence →
circa £500M business value enabled or contributed to across data-led initiatives, at least £23M directly attributed since July 2024 on a conservative basis
300+ extended data delivery organisation across employees, contractors and vendor support
11,000+ colleagues enabled to self-serve trusted data at different levels
250+ certified data products built on governed business layers
Award winner British Data Awards 2026, Data Team of the Year (20+ people)

Board-level proof

The Customer Trust Indicator, a CEO priority, runs on the data foundations my team built.

The Consumer team owns the survey and the concept. I co-led, and my team built, the Experience Trust Indicator measurement on the enterprise data foundations we created, turning hundreds of real-world signals into a trusted score. It is now one of the company's most important customer measures.

“One of the most impactful leaders I have ever worked with. His vision and leadership helped democratise data at scale, and he combines strategic thinking with genuine care for his team.”

Terry Glenning · Leader of Change & Transformation, Virgin Media O2

Searches where I fit best

Chief Data & AI leadership CDO, CDAO, Chief Data and AI Officer. Enterprise-wide remit over data, AI, governance, platform and commercial value.
EVP / SVP / VP Data, AI & Transformation Senior functional leadership where the role needs engineering depth, operating-model change and real adoption, not just reporting.
Data & AI value creation PE-backed, scale-up and enterprise roles where the brief is to mature data and AI and convert it into measurable commercial outcomes.

Title-agnostic, remit-led. The same senior role is called Director, Senior Director, Head of, VP or Chief in different companies. I do not screen on title. I screen on scope, authority and total compensation, so please do not hold back a strong search because the title does not say Chief.

01 / Search Snapshot

Everything you need to assess me for a longlist, in one view.

Built so a researcher or partner can lift the essentials straight into a brief. The detail behind every line is in the CV and the public evidence below.

Target roles

CDO, CDAO, Chief Data and AI Officer, EVP or SVP Data and AI, and senior Data, AI and Transformation leadership with genuine authority.

Title-agnostic, screened on remit and economics.

Sectors and environments

Telco, technology and SaaS, financial services, PE-backed mid-market and large enterprise. Strongest where data and AI are central to value, not a back office.

Comfortable in regulated and complex estates.

Geography and work model

UK-based, with a global operating background across the UK, Europe, the US, LATAM and APAC. Permanent roles, hybrid or remote, and open to the right relocation case.

Global operator; British and Mexican national, no UK sponsorship needed.

Scope I lead well

Enterprise transformation and operating-model change that turns data and AI into business and customer value: trusted foundations, AI adoption, governance and data products, with commercial accountability.

Engineering foundation through to ExCo influence.

Availability

Moving to my next executive challenge and open to the right permanent leadership role. Responsive to credible executive searches, and every conversation is handled discreetly.

Discreet, structured executive search.

Compensation

Best suited to senior executive remits (EVP, CDO, CDAO) in enterprise-scale or PE-backed businesses, where base, bonus and long-term incentive reflect enterprise ownership. Total compensation is the gate, not title.

Remit and economics screened together, in confidence.
02 / Track Record

Proof the work moves beyond strategy slides.

The consistent pattern: turning fragmented systems, unclear ownership and low-trust data into trusted capability the business uses, with the commercial outcomes to show for it.

Agentic automation and AI adoption

Problem: teams needed to move from insight requests to delivery faster, without losing trust, quality or control.

Intervention: I led governed adoption of data agents that connect metadata, trusted business layers and workflow tools, so teams can go from a request to a drafted requirement, user stories and a working prototype, with privacy and quality controls built in. I set the framework and governance; my engineering teams built it.

Result: faster, governed delivery on trusted foundations, with the operating model and controls to scale AI adoption safely.

VMO2 Data Democratisation

Problem: fragmented reporting, weak ownership, manual workarounds and inconsistent definitions.

Intervention: operating model, governed business layers, 250+ certified data products, self-service, support and culture, including Tableau to the Techs for 2,000+ field technicians and Martian Frontier as a data-culture mechanism.

Result: contributed to circa £500M in business value across data-led initiatives, for example more than £250M of fraud helped prevent and £100M+ in network investment optimisation, with at least £23M directly attributed since July 2024 on a conservative basis. Launched 300+ Tableau dashboards and enabled 11,000+ colleagues to self-serve trusted data.

Gemini Enterprise, conversational analytics and data agents

Problem: business teams needed a trusted, governed way to start using AI with data.

Intervention: I set the framework and product roadmap and managed the Google partnership, governance, privacy and adoption while my engineering team built. Consolidated nine BI and data platforms into a modernised stack along the way.

Result: 2,500 of 5,000 Gemini Enterprise licences deployed, plus conversational analytics and data agents on governed data, with £13M+ TCO reduction from the platform consolidation.

Commercial scale and enablement, Salesforce and MuleSoft

Problem: enterprises needed to adopt integration, data and AI platforms and turn them into value at scale, across a global footprint.

Intervention: I led architecture, enablement, training and certification, and automation across regions, part of the leadership that scaled the MuleSoft EMEA business through its IPO and the Salesforce acquisition.

Result: the MuleSoft EMEA business grew roughly tenfold over that period, with 6,000+ people trained and a certification and enablement engine that scaled customer adoption.

If you are scoping a senior Data and AI leadership hire, I would welcome a confidential note.

Email Mauro confidentially
03 / How I Run Data & AI

Foundations, Adoption, Value, Then Agents.

This is the order I run, and the order is the whole argument. Most organisations start at step four, and that is why their pilots never reach the business.

01

Foundations

Certified business layers with one named owner per domain, and governance that covers ownership, quality, metadata and lifecycle.

Nine platforms into one governed stack

02

Adoption

Self-service on data people actually trust, with the training, support and communities that make it stick inside the business.

11,000+ colleagues self-serving

03

Value

Run as a value centre, not a cost centre. Nothing starts without a case the business has signed off, and realised value is tracked afterwards.

£23M+ directly attributed since July 2024

04

Then agents

AI built only on certified foundations, governed, human in the loop, and owned by a named person in the business.

Test to production in about six months

Run it out of order and you get pilots. Run it in order and the business owns the outcome, which is the only version that survives a change of leadership.

£250M+ fraud helped prevent, per the public Tableau customer story
£13M+ annual platform cost removed through consolidation
6,000+ colleagues trained through the Data & AI University
~24 hrs to detect and shut down a fraud route nobody had seen before

How I lead the change

  • I open with one question: what do you actually own? Not KPIs, not reporting. How do you measure your success, and what makes you successful? It finds the real owners, and it finds the people who will champion the work.
  • I make the partnership a contract. A signed agreement per business domain, with a named sponsor, the domain defined and commitments on both sides. Ownership stops being a conversation and becomes a document.
  • Nothing enters the queue without value signed off by the business. Demand management goes live inside three months, and it takes two signatures rather than one.
  • I rebuild the roles around the outcomes needed, rather than leaving everyone under the same generic title, and I move the targets from products delivered to value delivered.
  • I change behaviour by recognition, not shame. I announce the new way of working before it takes effect, so the argument happens early and in the open, then I recognise the people working the new way and personally help the ones who are stuck.

How I govern AI

  • Every agent has a named owner in the business and a data co-owner, inherited from the certified layer it stands on. No owner, no agent.
  • An agent never exceeds its owner's permissions. Those limits are enforced in configuration, not in the prompt, so the model cannot talk its way past them.
  • Experts evaluate it before launch and keep feeding it afterwards. Where confidence is low the decision goes back to a human, a rule that came out of a real incident rather than a policy document.
  • The gate is real. Agents have been refused production when the data underneath them was not certified, including one the business pushed hard for.

"I did not follow a transformation playbook. I wrote one, and it is on its second version."

I authored the self-service analytics, service agreement and data product playbooks that governed how my function worked, peer-reviewed by the senior team and rewritten as the model matured. They exist to kill four failures I see everywhere: reactive order-taking, technical and business people working apart, nobody owning adoption, and quality nobody can trust. I do not run change as theory, I run it as application, and the measure of my work is whether your people still own it after I leave.

Download the one-page operating model

One page, built to forward: the model, the proof and the career arc.

04 / Public Evidence

Independently verifiable, useful for your due diligence.

Public signals you can check without taking the CV at face value: customer stories, interviews, speaking profiles and industry recognition from the data and cloud ecosystem.

Main-stage Keynote

Anaplan Connect London 2026 customer keynote

I gave the main customer keynote at Anaplan Connect London 2026, where I made the case that "you cannot AI your way out of data you don't trust", on transforming a large enterprise to decide and create value with data and AI. Named Transformational Leader 2026 in the Anaplan Customer Awards.

See the Anaplan Connect London 2026 event
Enterprise Case Study

Virgin Media O2 and Tableau customer story

The public Tableau customer story says Virgin Media O2 helped prevent £250m worth of fraud and blocked 92m+ malicious texts.

Read the Tableau VMO2 case study
Executive Feature

Interface Magazine feature

Executive feature on data democratisation at Virgin Media O2, framed as a cultural movement rather than a reporting programme.

Read the Interface Magazine feature
Google Cloud Next Speaker

Google Cloud Next 2026 speaker profile

Public speaker profile connected to enterprise AI, modernisation and human-centred transformation.

See the Google Cloud Next speaker profile
Ecosystem Insights

Atlan, Gartner and ReGovern coverage

Public ecosystem references around data context, governance and enterprise adoption at Virgin Media O2.

Read the Atlan VMO2 data context case
Industry Awards

British Data Awards 2026, Data Team of the Year

Winner, Data Team of the Year (20+ people), plus finalist for Data Transformation of the Year. Judged by independent panel across the UK data and analytics industry.

See the British Data Awards result
Advisory & Policy

UK Government DSIT Roundtable

In June 2026 I represented Virgin Media O2 at a UK Government roundtable convened by the Department for Science, Innovation and Technology (DSIT), alongside Ian Murray MP (Minister for Digital Government and Data) and senior executives from Unilever, Experian, GSK and RELX, advising on enterprise data-value creation, data exchanges and the regulatory safe spaces that compliant data and AI innovation needs.

DSIT on GOV.UK

The 3-minute story

A short version of the career throughline: engineering foundations, enterprise data scale, AI adoption, and the kind of leadership these searches are hiring for.

If the embedded video is blocked on your network, open the video directly. In three minutes it covers the throughline from engineering and SaaS platforms to enterprise data leadership, practical AI adoption and the kind of executive role I am ready for next.

Engineering foundation Computer Systems Engineer, graduated top of the generation, with early depth in Java, API architecture and enterprise platforms.
Enterprise transformation Operating model work across Salesforce, MuleSoft, Peñoles and Virgin Media O2 to enable governed business adoption.
Data and AI leadership Trusted data foundations first, then AI adoption and commercial value, with the authority and stakeholder reach a senior executive role needs.
05 / For Search Partners

Where I am a strong fit.

Written for retained partners and in-house hiring teams. The searches where I add the most value, and an open door for the ones worth a conversation.

Where I am a strong fit

  • Permanent CDO, CDAO or Chief Data and AI Officer roles with enterprise-wide remit
  • EVP, SVP or VP Data and AI roles with engineering, platform and transformation depth
  • PE portfolio companies maturing data and AI ahead of exit or post-acquisition
  • Telco, SaaS, financial services and large enterprises where data and AI drive value
  • Roles reporting to the CEO, board or ExCo with genuine authority, budget and decision rights

If the remit is senior, value-led and the compensation is plausible, send it in confidence. I will respond quickly and, where useful, point you to a strong name.

Start a confidential conversation.

A short note is enough: the company or situation, what kind of role it might be, and location or work model if you know them. If the brief is still forming, send what you have. I read every message personally and reply within 24 hours.

mauro@mauro-flores.com linkedin.com/in/mauroflores Download executive CV (3-page)
CV Downloads

Pick the depth that suits your read.

Same facts, same figures, told at four lengths, plus the one-page operating model if you want the method rather than the history. The three-page CV is my recommended read for a search partner. All PDFs open in a new tab.

Signature one-pager

How I build data and AI capability

The operating model on a single page: Foundations, Adoption, Value, Then Agents, the proof at scale, how I govern AI, how I lead the change, and the full 25-year arc. This is the one to forward to a client or a board.

Download the one-page operating model
Fast teaser

One-page profile

The essentials on a single page: seat, scale, headline value and the career arc, for a ten-second read.

Download the one-page profile
Standard

Two-page CV

The default executive CV: full career, selected highlights and recognition, sized for a retained-search read.

Download the two-page CV
Recommended

Three-page CV

My recommended read: the full track record with the depth and proof points behind every line.

Download the three-page CV
Full dossier

Four-page dossier

The complete dossier for deep due diligence: every role, metric and public proof point in one document.

Download the four-page dossier
Career arc

25 years, in two halves.

The first half I built the technology: engineer, architect, founder, and I taught engineering at university. The second half has been about leadership, people and culture, which is what actually changes an organisation. I can still hold a room full of engineers because I was one. That is the advantage, not the headline.

2000 · Mexico Acer Where the engineering started: hardware and systems, working on the machines themselves.
2001 - 2002 · Mexico MBSystems Networks, software, hardware and systems integration for enterprise clients including Ford.
2002 - 2007 · Mexico Tahi Systems Founder and CEO. Built a technology business from zero, owning sales, delivery and the P&L.
2007 - 2012 · Mexico Peñoles Group transformation in a 60,000-person mining major, and the first enterprise BI capability. Taught engineering at Tec de Monterrey alongside it.
2012 - 2015 · UK Infomentum Senior practice lead, headhunted to the UK. Helped move the firm from Oracle Gold to Platinum partner.
2015 - 2023 · Global MuleSoft, then Salesforce Grew the EMEA P&L roughly tenfold through IPO and a $6.5B acquisition, and founded the global data strategy capability.
2023 - 2026 · UK Virgin Media O2 EVP, Data Democratisation. A 300+ extended organisation inside a £10bn regulated business.

Hardware and systems, consultant, university lecturer, founder, then executive. I have been the engineer doing the work, the founder carrying the revenue and the teacher in front of the room, which is why growing people is not a slide in my strategy, it is the strategy.

Show the full role-by-role history
The Information LabJul 2026 - Present
  • Strategic Advisor Jul 2026 - Present

Advisor to the MD and leadership team of the UK's longest-standing Tableau partner on strategy, positioning and growth in a changing enterprise data market. Alongside the executive search.

Virgin Media O2Aug 2023 - Jun 2026
  • EVP, Data Democratisation Aug 2023 - Jun 2026

Led enterprise data and AI transformation across a £10bn regulated business, running a 300+ extended data organisation. Full detail in the track record above.

SalesforceJul 2018 - Aug 2023
  • Sr. Director, Global Data Strategy & Intelligence Feb 2023 - Aug 2023
  • Sr. Director, Global Data Strategy & EMEA Training Feb 2021 - Feb 2023
  • Director, Global Data Strategy & Training and Certification Jul 2018 - Feb 2021

Built trusted data foundations and intelligence products used across the business, and led global learning-platform and certification operations with commercial and P&L discipline through the MuleSoft integration.

MuleSoftNov 2015 - Jul 2018
  • Head of Global Data Strategy & EMEA Training & Certification Jan 2017 - Jul 2018
  • EMEA Regional Lead, Training & Certification Nov 2015 - Dec 2016

Built the EMEA Training and Certification business from early-stage foundations to a scaled regional capability through MuleSoft's scale-up, IPO and Salesforce acquisition, owning the regional P&L, and founded the global data strategy capability (roughly tenfold growth over the period).

Infomentum2012 - 2015
  • Senior Practice Lead, Oracle Middleware & Digital Transformation 2012 - 2015

Led Oracle middleware and digital transformation across delivery, pre-sales and R&D (WebLogic, WebCenter, ADF, SOA Suite, Java), helping the firm move from Gold to Platinum Oracle partner. Headhunted to the UK from Mexico.

Industrias Peñoles2007 - 2012
  • Head of Digital Transformation 2007 - 2012

Led enterprise digital transformation for a mining and metals group of roughly 60,000 people, selecting Oracle middleware as the backbone, moving the programme from technology implementation into business adoption, and introducing enterprise BI capability.

Tecnológico de Monterrey2007 - 2008
  • University Professor, Computer Systems & Software Engineering 2007 - 2008

Taught computer systems and software engineering, an early expression of the education and enablement thread that runs through the whole career.

Tahi Systems2002 - 2007
  • Founder & CEO 2002 - 2007

Built a technology business from zero, delivering middleware, custom software, portals and data-centric enterprise solutions across government, higher education and commercial clients, owning full commercial delivery and P&L.

MBSystems2001 - 2002
  • Consultant, Networks, Software & Systems Integration Aug 2001 - Aug 2002

Started a consulting career across network solutions, software, hardware and systems integration for major enterprise clients, including Ford.

Acer2000 - 2001
  • Hardware and Systems 2000 - 2001

Where the engineering career began. Building, configuring and repairing machines, then moving into networks and software. I qualified as a Computer Systems Engineer at Tec de Monterrey, studying while I worked.

At this level, success is not measured by the platforms we build. It is measured by the clarity we bring to decisions, the trust we earn with customers, and the confidence with which the business moves forward.