Generative AI for Prospecting and Lead Generation

See exactly how this course's AI prospecting skills build on each other, from ideal customer profile through to a ready-to-use pre-call brief.

What you'll learn:

• Understand how the course sections connect into one repeatable AI prospecting workflow

• Identify which sections to prioritise based on your current role and biggest bottleneck

• Locate the templates, exercises, and capstone project you'll use throughout the course

Master exactly where generative AI adds real value in the prospecting process, and where it doesn't, before you build a single workflow.

What you'll learn:

• Identify the specific prospecting tasks generative AI genuinely improves

• Distinguish AI-suited work from tasks that still need human judgment

• Explain how AI changes the sequence and speed of a typical prospecting process

Build a complete stage-by-stage map of the AI-assisted prospecting funnel, from first research pass to booked meeting.

What you'll learn:

• Break the prospecting funnel into distinct, AI-assisted stages

• Apply the right AI task to each funnel stage instead of one generic prompt

• Create your own funnel map to reference throughout the rest of the course

Understand the three biggest risks of AI-assisted prospecting- hallucinated facts, stale data, and privacy exposure- before they cost you a deal.

What you'll learn:

• Identify common hallucination patterns in AI-generated prospect research

• Recognise when AI output relies on outdated or unreliable data

• Apply basic safeguards to protect prospect and company data in AI tools

Use generative AI to define a sharper ideal customer profile than a spreadsheet exercise ever could, grounded in real firmographic and behavioural signals.

What you'll learn:

• Define an ideal customer profile using firmographic and behavioural criteria

• Use AI prompts to stress-test and refine a draft ICP

• Identify the data sources that make an AI-built ICP reliable

Build buyer personas AI can actually use, grounded in real stakeholder priorities instead of generic job-title assumptions.

What you'll learn:

• Create buyer personas that reflect genuine priorities, not stereotypes

• Structure persona details so generative AI can apply them consistently

• Validate a persona against real deal and conversation evidence

Capture your hard-won sales knowledge as reusable AI context, so every prompt benefits from what you already know works.

What you'll learn:

• Identify the sales knowledge worth capturing as reusable AI context

• Structure product, objection, and win-loss knowledge for AI reuse

• Build a starter knowledge base you'll reference throughout the course

Write a prospecting prompt brief detailed enough that AI stops guessing and starts producing usable, on-target research.

What you'll learn:

• Structure a prompt brief with the context AI needs to perform well

• Combine ICP, persona, and knowledge-base inputs into one usable brief

• Test and iterate a prompt brief against real research output

Use targeted AI research queries to surface high-potential accounts faster than manual list-building ever could.

What you'll learn:

• Write AI research queries that surface accounts matching your ICP

• Filter AI-generated account lists for genuine fit versus surface matches

• Build a repeatable process for sourcing new account candidates

Build a full company, market, and strategy picture of any target account using AI-assisted research, in a fraction of the usual time.

What you'll learn:

• Research a target account's business model, market position, and strategy

• Combine multiple AI queries into one coherent account picture

• Identify which account details actually change how you approach outreach

Map an account's full buying committee with AI, so you stop pitching one contact and start engaging the whole room.

What you'll learn:

• Identify likely stakeholders and roles within a buying committee

• Use AI to map reporting lines and probable influence within an account

• Prioritise which stakeholders to engage first based on the mapped structure

Use AI to catch buying signals and trigger events as soon as they surface, instead of finding out weeks too late.

What you'll learn:

• Identify common buying signals and trigger events worth tracking

• Set up AI-assisted monitoring for relevant account changes

• Turn a detected trigger event into a timely, relevant outreach angle

Build a simple verification habit that catches AI research errors before they reach a prospect and cost you credibility.

What you'll learn:

• Apply a quick checklist for verifying AI-generated account research

• Identify the highest-risk types of claims to double-check manually

• Build a verification habit that fits into a real prospecting workflow

Learn what genuinely useful AI lead enrichment looks like, versus a data dump that just makes your CRM messier.

What you'll learn:

• Distinguish useful enrichment fields from noise

• Explain how enrichment should change what you do next with a lead

• Set standards for what "enriched" means for your own pipeline

Turn raw, scattered lead data into usable sales intelligence with AI, so every field earns its place in your outreach.

What you'll learn:

• Convert raw firmographic and contact data into sales-ready intelligence

• Use AI to summarise enrichment findings into a usable snapshot

• Prioritise which enrichment insights matter most for outreach

Structure-enriched lead records so AI can score and route them automatically, not just describe them in a paragraph.

What you'll learn:

• Structure enrichment fields for downstream scoring and routing

• Standardise a lead record format AI can apply consistently

• Test an enriched record against the scoring model you'll build later

Catch research gaps in a lead record before you reach out, so your first message never gives away that you didn't do the homework.

What you'll learn:

• Identify missing or low-confidence fields in an enriched lead record

• Use AI to flag research gaps before outreach begins

• Decide when a gap is worth filling versus safe to work around

Understand the real difference between personalisation and relevance- the reason most AI-written outreach still gets ignored.

What you'll learn:

• Distinguish surface-level personalisation from genuine relevance

• Explain why name-and-company mail merge outreach underperforms

• Identify the relevance signals that actually drive replies

Break down the anatomy of a prospecting message that actually gets replies, line by line, before you write a single one with AI.

What you'll learn:

• Identify the core components of a high-response prospecting message

• Explain how each component should be adapted per prospect

• Apply an anatomy checklist to messages before sending

Write personalised cold emails with generative AI that read as if they came from a person who did the research, because they did.

What you'll learn:

• Draft a cold email using AI and prospect-specific research inputs

• Apply the message anatomy from the previous lesson to a real draft

• Revise AI-generated email drafts for tone and specificity

Create AI-assisted social outreach and connection messages built for LinkedIn's shorter, more casual format, not repurposed email.

What you'll learn:

• Adapt AI-generated messaging for social and connection-request formats

• Apply platform-appropriate length and tone to AI drafts

• Sequence a connection message with a natural outreach follow-up

Generate AI call openers and voicemail scripts that sound natural on the phone, not like a script read aloud.

What you'll learn:

• Draft call openers grounded in prospect and account research

• Write voicemail scripts short enough to actually get listened to

• Adapt an AI-generated script for a natural spoken delivery

Adapt the same AI outreach for executive, technical, and financial buyers, each reading for something completely different.

What you'll learn:

• Identify what executive, technical, and financial buyers each prioritise

• Rewrite one outreach message for three distinct buyer types

• Adjust tone, length, and proof points based on buyer role

Edit AI-generated outreach until it sounds like you wrote it, not like it came off an assembly line.

What you'll learn:

• Identify common tells of unedited AI-generated writing

• Apply a personal editing pass to remove generic AI phrasing

• Build a repeatable edit checklist for future AI drafts

Apply proven sales qualification frameworks with AI assistance, so qualification stops depending on gut feel alone.

What you'll learn:

• Apply an established qualification framework (such as BANT or MEDDIC) with AI support

• Use AI to surface qualification answers from existing research

• Identify qualification gaps a framework reveals early

Design an AI lead-scoring model that reflects your best-fit criteria, not a generic points system.

What you'll learn:

• Define scoring criteria based on your ICP and qualification framework

• Assign weighted values to firmographic and behavioural signals

• Build a working lead-scoring model with AI assistance

Automatically classify and route leads by priority, so your best opportunities never sit behind the wrong ones.

What you'll learn:

• Apply your scoring model to classify leads by priority tier

• Design simple routing rules based on lead classification

• Test classification logic against a sample batch of leads

Qualify inbound replies at a glance, sorting genuine interest from objections and opt-outs with AI-assisted triage.

What you'll learn:

• Classify inbound replies into interest, objection, and opt-out categories

• Use AI to draft an appropriate first response per reply type

• Route qualified replies into the correct next-step workflow

Spot bias and false precision hiding in an AI lead-scoring model before it quietly deprioritises your best accounts.

What you'll learn:

• Identify common sources of bias in AI-assisted scoring models

• Recognise false precision in confidently stated AI scores

• Apply a review process to audit a scoring model periodically

Draw a clear line between what's safe to automate in prospecting and what still needs a human before you build a single sequence.

What you'll learn:

• Categorise prospecting tasks by automation suitability

• Identify red flags that signal a task needs human oversight

• Set your own automation boundaries before building sequences

Design a multi-touch AI outreach sequence that builds naturally across channels instead of repeating the same pitch five times.

What you'll learn:

• Structure a multi-touch sequence across email, social, and phone

• Vary message angle and value across sequence touches

• Set timing and spacing for a sequence that feels natural, not spammy

Create AI follow-up messages that reference what actually happened last time, instead of a generic "just checking in."

What you'll learn:

• Feed prior-touch context into an AI follow-up prompt

• Draft follow-ups that reference specific prior interactions

• Avoid generic "just following up" phrasing in AI drafts

Connect your AI prospecting workflow to your CRM and sales-engagement stack, so nothing lives in a disconnected side document.

What you'll learn:

• Map where AI outputs need to land in your existing tech stack

• Identify practical connection points between AI tools and your CRM

• Design a workflow that keeps AI output and CRM records in sync

Put guardrails around AI-driven outreach automation so a sequence never fires the wrong message at the wrong moment.

What you'll learn:

• Identify failure modes that make automated outreach harmful

• Set up guardrails and stop conditions for automated sequences

• Test an automated sequence for edge cases before it goes live

Build an intelligent AI pre-call brief that pulls every relevant fact into one page, so you walk into calls actually prepared.

What you'll learn:

• Structure a pre-call brief combining account, contact, and signal research

• Use AI to summarise scattered research into one usable brief

• Customise a brief template for repeat use across accounts

Generate discovery questions tailored to each stakeholder's role with AI, instead of asking every buyer the same generic list.

What you'll learn:

• Draft discovery questions tailored to a specific stakeholder role

• Use account and persona research to sharpen question relevance

• Prioritise the discovery questions most likely to surface real needs

Prepare for likely objections before the call even starts, using AI to draft responses grounded in the account you're actually calling.

What you'll learn:

• Anticipate likely objections based on account and persona research

• Draft objection responses with AI before a call happens

• Practice delivering AI-drafted objection responses naturally

Turn every piece of AI research into one ready-to-use call plan, so preparation stops being scattered across five documents.

What you'll learn:

• Combine brief, discovery questions, and objection prep into one call plan

• Structure a call plan for quick reference during a live conversation

• Adapt a call plan template for different meeting types

Understand what appropriate data use actually looks like in AI-assisted prospecting, before privacy becomes a problem instead of a policy.

What you'll learn:

• Identify what data is and isn't appropriate to feed into AI tools

• Explain basic privacy principles relevant to prospecting data

• Apply data-handling habits that reduce privacy risk

Apply the three pillars of responsible AI outreach: consent, honesty, and clean opt-outs, without slowing your workflow down.

What you'll learn:

• Apply consent-conscious practices to AI-assisted outreach

• Avoid deceptive or misleading claims in AI-generated messages

• Build a clean, respectful opt-out process into every sequence

Build a human-in-the-loop process that keeps a person accountable for every AI-assisted step, without adding unnecessary friction.

What you'll learn:

• Identify the checkpoints where human review adds the most value

• Design a lightweight human-in-the-loop review process

• Balance oversight with the speed benefits AI provides

Turn everything from this section into one AI sales governance checklist your whole team can actually follow.

What you'll learn:

• Consolidate privacy, consent, and oversight practices into one checklist

• Adapt a governance checklist to your team's specific tools and process

• Establish a review cadence for keeping the checklist current