About | Zanor AI

Leadership

Founder & Managing Director

Practitioner-led leadership spanning strategy, governance, and orchestration of production-grade AI transformation in energy and industrial settings.

Dr. Asaad Abdollahzadeh

Dr. Asaad Abdollahzadeh is an AI and data science leader with more than two decades of experience in energy, engineering analytics, and enterprise AI transformation.

His work spans the full AI lifecycle, from strategy and opportunity framing to production adoption across enterprise operations.

Key highlights

More than 23 years of experience in oil and gas digital transformation
Built and scaled enterprise AI in global organisations including BP, Halliburton, and PETRONAS
Led AI programmes delivering hundreds of millions in measurable operational value
Built and scaled enterprise and startup AI and data functions from the ground up
Board-level advisor on AI governance, transformation strategy, and operating model design
Built and led AI and data teams of 60+ specialists in enterprise environments
Author of 30+ publications in journal and conference
Advisor, technical committee member, and reviewer for international energy and industrial conferences
Recipient of two national awards for AI solutions in energy

Dr Asaad combines deep domain expertise with hands-on AI engineering and transformation leadership.

He works with organisations as a strategic partner in AI-first transformation, designing, leading, and orchestrating programmes with client and partner teams to achieve measurable operational and financial impact.

Our Specialist Network

A Curated Network of Senior Specialists, Experts, and Architects

Zanor AI is a principal-led practice. For each engagement, we assemble the right team from a trusted network of senior specialists across key AI-first transformation areas. This means you get the exact expertise your programme requires, led by a principal who stays accountable for the outcome.

Our model remains to design, lead, and orchestrate programmes. Where needed, this specialist network enables targeted delivery across selected workstreams.

Strategy, Governance and Operating Model

Enterprise AI Strategy and Responsible AI Specialist

Specialist in AI-first maturity and value assessment, enterprise AI strategy, and responsible AI governance. Focuses on identifying priority use cases, defining decision ownership, and setting model risk and control requirements for regulated organisations.

Enterprise Transformation and Operating Model Specialist

Transformation specialist in operating model design and execution roadmaps. Focuses on organisational design, capability build-out, and phased plans that move AI from lighthouse initiatives to scaled enterprise adoption.

AI Platforms and Data Foundations

Enterprise Data and Value Chain Intelligence Architect

Specialist in enterprise data platforms and operational analytics across complex industrial environments. Expertise includes integrating operational, engineering, and financial data to enable value chain optimisation and enterprise intelligence.

AI Platform and MLOps Architect

Specialist in production AI infrastructure, model lifecycle management, and scalable machine learning platforms. Expertise includes MLOps pipelines, AI platform architecture, and targeted deployment support for enterprise AI systems.

Industrial AI and Advanced Analytics

Industrial Analytics and Advanced Modelling Expert

Data science specialist with experience applying advanced analytics and optimisation techniques to large industrial systems. Focus areas include predictive analytics, operational optimisation, and intelligent decision systems.

Physics-Informed Machine Learning Expert

Expert in combining engineering models with AI to build robust industrial intelligence solutions. Focus areas include physics-informed AI, engineering analytics, and hybrid modelling approaches.

Subsurface and Engineering Intelligence Expert

Domain expert in engineering analytics and subsurface modelling with experience applying advanced data science techniques to energy systems and production optimisation.

AI Products, Systems and Enterprise Integration

AI Product and Decision Systems Architect

Designs AI products and decision systems that embed intelligence into enterprise workflows. Focus areas include AI product lifecycle, copilots, workflow automation, and human-AI interaction.

Enterprise AI Orchestration and Systems Integration Expert

Experienced AI engineering leader focused on orchestrating production-grade AI solutions from proof of concept to enterprise-scale adoption, with targeted delivery support where required.

Teams are assembled based on the needs of each engagement, ensuring the right expertise across strategy, platforms, and domain. Leadership and orchestration remain centrally managed by the founding principal, giving you senior-level attention throughout.

Our Model

Why a Practitioner-Led Practice?

The person who advises you should be the same person who has built what you're trying to build.

The principal stays on the work

The founding principal leads every engagement from first conversation to outcomes. You won't meet a senior partner at the pitch and then be handed to a team learning your industry on the job.

Expertise shaped by building, not advising

Our recommendations come from founding and scaling enterprise AI functions inside major energy organisations, not from frameworks assembled by research teams.

Teams sized to your problem, not our bench

We assemble the right specialists from a curated senior network. No underutilised consultants, no inflated teams, no juniors billing time while they learn.

Accountability for outcomes, not activity

Engagements are scoped around measurable results. We have no incentive to extend timelines, expand scope, or keep teams on-site longer than the work requires.

Speed without layers

Decisions happen in the room, not in a committee three levels removed. When something needs to change, it happens the same day.

Domain fluency from day one

Energy and industrial AI is all we do. There is no ramp-up period where we learn your operations, your data landscape, or your terminology. We arrive ready to work.

Not because large firms lack talent, but because this work demands someone who has done it before, stays accountable, and has no structural reason to overcomplicate the path.

From the Field

Where This Experience Comes From

Before Zanor AI, our founder initiated and led AI programmes inside a major national energy company, from proof of concept through to production scale and value realisation. These are two examples of that work.

AI-driven petrophysics workflow across wells and fields

Upstream: AI-Driven Petrophysics at Scale

The challenge: Petrophysical interpretation across a growing asset portfolio was manual and expert-dependent. Behind-casing opportunities and thin-bed reservoirs were being missed — not for lack of data, but because human workflows couldn't cover the volume at the speed investment decisions required.

What we built: An in-house AI platform for automated well log interpretation that surfaced opportunities manual analysis had missed. Started with dozens of wells in one field; scaled to thousands of wells across dozens of fields.

What it proved: AI earns its place in upstream when it scales beyond a single field and changes how the organisation makes decisions, not when it produces a promising pilot.

AI-First principle: Value-Linked Execution, every capability tied to resource monetisation, not experimentation.

AI optimisation of national gas transmission operations

Midstream: Optimising a National Gas Transmission Network

The challenge: A national gas transmission network — thousands of kilometres, supplying power plants, petrochemicals, and industry. Fuel gas consumption was a major cost and carbon driver, but optimisation still relied on engineering judgement and static models.

What we built: An AI-driven system integrating real-time operational data with physics-based pipeline models to continuously optimise fuel gas consumption. Gave control room operators live decision support — reducing costs and lowering emissions.

What it proved: Midstream optimisation at national scale demands AI that respects physical constraints, pressure, flow, compressor dynamics. The system worked because it combined physics with AI, not one or the other.

AI-First principle: Hybrid Intelligence by Design, domain engineering combined with machine learning to create intelligence grounded in real-world physics.

These programmes didn't start as innovation projects. They started as operational problems, and the AI had to earn its place by delivering measurable value in production, not in a lab.

Why Zanor AI

Proven Track Record

Evidence from hands-on leadership and delivery at enterprise scale in global energy and industrial settings.

23+ years in energy & AI

Hands-on leadership in oil and gas digital transformation and enterprise AI, spanning assets, operations, and executive strategy.

Measurable operational value

Large-scale enterprise AI programmes with hundreds of millions in measurable operational value delivered for clients.

Enterprise AI build-out

AI and data functions built and scaled from scratch across major enterprises and high-growth startup environments alike.

Industrial-scale delivery

Programmes deployed across hundreds of assets and operating sites in complex industrial environments worldwide.

Awards & publications

Two national awards for AI in energy; 30+ publications; conference advisor, committee roles, and peer review internationally.

Curated specialist network

100+ years of combined energy AI expertise on strategy, analytics, platforms, and transformation, from subsurface through to enterprise automation.

This is the experience behind every engagement we lead and the standard we hold ourselves to.

Ready to Work With Us?

If you would like to learn more about how we work or discuss an engagement, we would be glad to hear from you.

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About Zanor AI