AI Expert Roadmap

The complete map.

Knowledge → capability → evidence → experience → impact → leadership → expertise.

  1. Foundations+

    Understand how AI works and how organisations use it.

    • AI fundamentals
    • Machine learning fundamentals
    • Generative AI
    • LLMs
  2. AI Practitioner+

    Move from using AI to applying it through workflows, automation, agents and practical solutions.

    • Advanced prompting
    • Workflow automation
    • AI agents & tool use
    • Retrieval (RAG) basics
  3. Specialisation+

    Choose a professional direction and develop deeper expertise.

    • The roadmap branches here
    • Choose based on strengths
    • Paths can combine
    ◆ AI Engineer

    Build and deploy AI systems.

    ◆ Data Scientist

    Use data and machine learning to solve complex problems.

    ◆ AI Product

    Design products and experiences powered by AI.

    ◆ AI Strategy

    Help organisations identify where and how to implement AI.

    ◆ AI Governance

    Make AI responsible, secure and compliant.

    ◆ AI + Domain

    Combine AI with an existing professional speciality.

  4. Build+

    Turn knowledge into projects, systems and a professional portfolio.

    • RAG application
    • Production-grade agent
    • AI product prototype
    • AI strategy or governance assessment
  5. Professional+

    Apply AI to real problems and demonstrate measurable impact.

    • Owning AI outcomes
    • Leading delivery teams
    • Reporting impact to leadership
  6. Leadership+

    Move from individual AI capability to organisational transformation, architecture, governance and adoption.

    • Identify enterprise AI opportunities
    • Build AI roadmaps
    • Lead AI transformation programmes
    • Evaluate AI investments
    • Manage AI risk
    • Create AI governance frameworks
    • Lead cross-functional AI teams
    • Drive adoption
    • Measure business impact
  7. AI Expert+

    Combine technical knowledge, business understanding, experience and leadership.

    • Knowledge
    • Implementation
    • Business impact
    • Governance
    • Leadership
AI Career Guide

From AI curious
to AI expert.

A practical roadmap for understanding AI, choosing your path, building real capabilities and progressing from beginner to AI professional.

Explore the RoadmapFind Your AI Path
  1. Foundations→
  2. AI Practitioner→
  3. Specialisation→
  4. Build→
  5. Professional→
  6. Leadership→
  7. AI Expert
01The landscape

AI is not
one career.

There is no single path to becoming an AI professional.

AI is transforming engineering, product, strategy, marketing, design, data, cybersecurity, finance and almost every other professional field.

You don't necessarily need to become an AI engineer. You need to understand where AI fits into your strengths.

02Seven stages

The roadmap.

Seven stages from first principles to recognised expertise. Open any stage to see exactly what it takes.
03Where the roadmap branches

Choose
your path.

After Foundations and Practitioner, the roadmap branches. Each path is a different way to create value with AI.
04The loop

What actually makes
an AI professional?

  1. 01

    Learn

    Build a real mental model of how AI works.

  2. 02

    Certify

    Validate knowledge with a relevant credential.

  3. 03

    Build

    Make things. Small, then ambitious.

  4. 04

    Apply

    Use AI on problems that matter to someone.

  5. 05

    Measure

    Prove impact with numbers, not adjectives.

  6. 06

    Specialise

    Go deep where your strengths compound.

  7. 07

    Lead

    Help others adopt AI responsibly.

  8. 08

    Teach

    Share knowledge and develop others.

Certifications demonstrate knowledge.

Projects demonstrate capability.

Experience demonstrate impact.

Leadership demonstrate expertise.

05Certification intelligence

The certification
layer.

Certifications structure learning and signal knowledge. Choose deliberately — then build, apply and measure.

Certification database

46 credentials · 15 providers · 6 career paths

AI moves fast. This roadmap evolves with it.

Content reviewed: October 2026
Provider verification status shown per credential

46 of 46 credentials

CORE: recommended for the path · OPTIONAL: stack-dependent · ADVANCED: experienced professionals · SPECIALIST: ecosystem-specific. Priorities and experience levels are roadmap guidance, not provider entry requirements.

Certifications are a signal.
Experience is the proof.

A credential can demonstrate knowledge. It cannot prove you can solve a real business problem. The goal is knowledge + projects + experience + impact + leadership.

06Evidence

Build your
AI portfolio.

Employers don't hire certificates. They hire evidence. Each project should tell a complete story — from problem to business impact.
07Your advantage

Your domain is
your advantage.

You don't have to start over.

Years of experience in your field are not a detour — they are context AI-only specialists don't have. Combine the two and you become rare.

Marketing + AI
SEO + AI
UX + AI
Finance + AI
HR + AI
Law + AI
Healthcare + AI
Operations + AI
Cybersecurity + AI
Product + AI
Marketing + AI
SEO + AI
UX + AI
Finance + AI
HR + AI
Law + AI
Healthcare + AI
Operations + AI
Cybersecurity + AI
Product + AI
Example evolution — from digital strategy to AI transformation
  1. Digital Strategy↓
  2. SEO↓
  3. AEO↓
  4. GEO↓
  5. AI Search↓
  6. AI Strategy↓
  7. AI Transformation
09Definition

What does "AI expert"
actually mean?

Not a stack of certificates. Expertise is the combination of five capabilities, proven over time.
01

Know

Understand AI technology.

02

Build

Create AI solutions.

03

Apply

Solve real problems.

04

Govern

Understand risk and responsibility.

05

Lead

Create strategy and drive adoption.

The formula

Knowledge+Implementation+Business impact+Governance+Leadership=AI Expert

Your AI career
starts with a
direction.

  • Understand the landscape.
  • Choose your path.
  • Build the skills.
  • Create the evidence.
  • Start moving.
Start the RoadmapExplore Career Paths