Learning path
Adopt AI in your organization
Learn the language and how AI works first, then check your readiness, run one measured pilot and understand the two big building blocks.
- Length
- 6 articles · about 46 min
- Level
- Beginner
- Before you start
- None. Written for non-technical readers, starting with the vocabulary.
Best for: Leaders and small teams deciding where to start
By the end
What you will be able to do
- Speak the same AI vocabulary as your team, your vendors and your leaders
- Explain in plain words how AI learns from data, and name its main branches
- Match a business problem to the right branch of AI
- Score your organisation’s readiness across data, people, process and risk
- Choose one task, set a baseline and run a 30-day pilot
- Understand what RAG assistants and AI agents can and cannot do
- Decide, with evidence, whether to continue, change or stop
The path
Read in this order
Concept · Beginner · 10 min read
AI basics: the essential terminology, in plain language
Sixty terms you will hear in every AI meeting, explained simply, so that you can ask better questions and spot buzzwords.
You will learn
- Shared vocabulary is the cheapest way to avoid expensive misunderstandings with vendors, teams and leaders.
- AI is the broad field, machine learning is one way of building it, and generative AI and language models are the part most people now meet.
Start here →
Concept · Beginner · 10 min read
How does AI work, and what are the branches of AI?
A plain-language map of how modern AI learns from data, and the main branches, from machine learning and language to vision, robotics and agents.
You will learn
- Most modern AI is a pattern-finding system: it learns from many examples, then applies what it learned to new cases.
- AI is a family of fields, not one technology: machine learning, language, vision, speech, robotics, planning and more.
Read →
Guide · Beginner · 6 min read
AI readiness checklist for your organization
Twelve questions across data, people, process and risk, with a simple way to score yourself and decide what to do first.
You will learn
- Most stalled AI projects fail on data access, ownership and change management, not on technology.
- Score yourself honestly: a gap you can see is a gap you can fix.
Read →
Guide · Beginner · 6 min read
Your first AI pilot: pick one task and measure it for 30 days
A practical plan for small teams: choose one repeated task, set a baseline, try a tool for a month and decide with evidence.
You will learn
- Start with one painful, repeated task, not a grand AI strategy.
- Record the time or cost per task before you begin, or you will have nothing to compare.
Read →
Concept · Beginner · 7 min read
RAG explained: how AI answers from your own documents
Retrieval-augmented generation in plain language: how it works, why it reduces made-up answers, and where it can still fail.
You will learn
- RAG retrieves relevant passages first, then asks the language model to answer using only those passages.
- Good retrieval matters more than a bigger model, so most of the work is in how documents are prepared and searched.
Read →
Concept · Intermediate · 7 min read
AI agents explained: from answering to acting
What makes an AI agent different from a chatbot, how agents are built, and how to keep them safe and useful.
You will learn
- An agent plans and carries out multi-step tasks using tools. A chatbot only replies.
- Autonomy is a dial, not a switch: start with suggestions, then approvals, then limited actions.
Read →
When you finish
Where to go next
Next path
RAG: from idea to a trusted assistant
Understand how it works, split documents well, build a pipeline and prove it answers correctly.
5 articles · 37 min
Next path
GeoAI: from zero to your first map
Learn the basics, work with free imagery and finish with a land cover map you tested honestly.
7 articles · 63 min
Start a project
Want this applied to your own project?
Learning is the first step. If you would rather have a working system, book a discovery call and we will scope it with you.