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STAGE 1 OF 5

Foundations

Before you can use AI effectively in B2B marketing, you need to understand what it actually does, how to communicate with it, what it costs in rupees, and how the buyers you are selling to differ depending on which market you are in. That is what this stage covers.

STAGE OUTCOME
You can use any LLM confidently for marketing tasks, write prompts that work first time, and know exactly what to change when you are writing for a Boston VP versus a London procurement lead versus a Singapore CTO.

What this stage covers

The AI foundations every B2B marketing team in India needs are covered in this stage — from understanding how language models work to writing prompts that produce useful output and reading buyer signals by market. According to McKinsey’s State of AI research, 72% of organisations now use AI in at least one business function, making foundational literacy a baseline requirement. Once you complete this stage, move to Stage 2: Skills Lab to apply these foundations across content, demand gen, PMM, and RevOps.

Most AI adoption in marketing fails at the foundation. Marketers pick up a tool, try it for a few tasks, find it produces generic output, and conclude AI is not ready. The problem is not the tool. It is the lack of a mental model for how these systems work and how to communicate with them effectively.

This stage builds that foundation. It also covers something that no comparable resource addresses: the fact that the buyers you are selling to in North America, Europe, and APAC are meaningfully different from each other, and that your AI output needs to reflect that. A prompt that works for a US enterprise sale will not work unchanged for a UK mid-market buyer or a Singapore technology decision-maker.

YOU WILL LEARN TO
Explain what a large language model actually does, without the hype
Write prompts that produce usable output on the first attempt
Choose the right AI tool for your budget and workflow at INR pricing
Adapt your AI output for NA, European, and APAC buyer expectations
Spot when AI is wrong and know how to correct it without starting over
Build a basic prompt library you can reuse across campaigns

The four guides in this stage

Work through them in order. Each builds on the last.

1.1
Live
How AI models work
What large language models actually do, why they hallucinate, what to trust and what to verify, and the difference between reasoning models and generative models. Written for marketers, not engineers.
8 min read Read →
1.2
Live
Prompting 101
The structure of a prompt that works. How to set context, assign a persona, specify format, and iterate without starting over. Includes 15 copy-paste templates for common B2B marketing tasks.
10 min read Read →
1.3
Live
The AI literacy quiz
Five questions that tell you where you actually are with AI in marketing, not where you think you are. Get a score and a personalised reading path across the full curriculum.
1.4
Live
Buyer context by market
How decision committees, buying cycles, communication tone, and trust signals differ across North America, Europe, and APAC—and how to adapt AI outputs for each.
12 min read Read →

Why foundations matter more for India-based B2B marketers

The AI tools most B2B marketers are using were built primarily on English-language data with a heavy US weighting. This means the default output, without deliberate prompting, tends to sound American. The tone, the examples, the framing, the references, all of it defaults to a US context.

For an India-based marketer selling into London or Singapore or Frankfurt, this is a problem. A cold outreach email that reads like it was written in San Francisco will not land the same way with a UK procurement lead who values understatement and process, or a Singapore CTO who is evaluating three other vendors and wants you to get to the point.

Getting the foundation right, specifically understanding how to brief AI with the right buyer context from the start, is what separates output that converts from output that sounds generic. That is what the buyer context guide in this stage is built to fix.

“The AI tools most marketers use default to a US context. Understanding how to override that default is a foundational skill, not an advanced one.”
COMMON MISTAKES THIS STAGE FIXES
Using AI like a search engine
Giving it a question instead of a brief. Output is shallow because the input is shallow.
One prompt, one attempt
Not iterating. The first output is a draft, not a deliverable.
Generic prompts for all markets
The same prompt for a US and a UK audience produces the same output. That is not personalisation.
Trusting everything it produces
AI hallucinates facts, statistics, and company details. Verification is non-negotiable.

After Foundations: Stage 2

2
Skills lab
Function-by-function AI skills: B2B content, demand generation, product marketing, and revenue ops. Once you have the foundation in place, this is where you build the skills to run each marketing function with AI as the operating layer.
Go to Stage 2 →

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