How to Use AI for Cold Email Writing in 2025 (ChatGPT + Claude Guide)

Everyone is using AI to write cold emails now. ChatGPT, Claude, Jasper—pick your poison.

And here's the problem: recipients can tell. They're getting dozens of obviously AI-written emails every day, and they're ignoring all of them.

But AI isn't the problem. Bad prompts and lazy implementation are the problem.

I've sent over 5 million cold emails, and I use AI for probably 60% of my copy now. But I use it strategically, not as a shortcut. The emails that work don't sound like AI wrote them—even though AI did.

Here's how to actually use AI for cold email without sounding like every other generic outreach message flooding inboxes in 2025.

The Problem With AI-Generated Cold Emails

Let's start with what's broken. If you've ever received an AI-written cold email, you know exactly what I'm talking about:

• Opening with "I hope this email finds you well"
• Way too formal and corporate sounding
• Generic value propositions that could apply to anyone
• Awkward transitions between paragraphs
• Overuse of buzzwords ("leverage," "synergy," "cutting-edge")
• Ending with "I'd love to hop on a quick call"

These aren't AI problems—they're prompt problems. The AI is giving you exactly what you asked for. You just asked for the wrong thing.

The Right Way to Use AI for Cold Email

AI should be a collaborator, not a replacement. Here's my framework:

Step 1: You Do the Research

AI can't research your prospect. You need to understand:

• Their actual pain points (not assumed ones)
• Their company's recent activity
• Their role and responsibilities
• What they care about right now

AI can help synthesize this information, but you need to feed it real data.

Step 2: You Write the Strategy

Before touching AI, define:

• The hook (why should they care?)
• The insight (what do you know that they don't?)
• The ask (what specific action do you want?)
• The tone (professional? casual? direct?)

Step 3: AI Helps With Execution

Now you can use AI to:

• Generate multiple variations quickly
• Improve clarity and flow
• Test different angles
• Shorten or expand sections

Step 4: You Edit Heavily

Never send AI output raw. Always:

• Remove obvious AI patterns
• Add your personality
• Verify accuracy
• Make it conversational

Prompts That Actually Work

The difference between good and bad AI cold emails comes down to your prompts. Here are my go-to templates:

Prompt 1: The Context-Heavy Approach

Prompt 2: The Angle Testing Approach

Prompt 3: The Improvement Approach

ChatGPT vs Claude vs Other AI Tools

I've tested all the major AI writing tools for cold email. Here's my honest take:

ChatGPT (GPT-4)

Best for: Quick drafts and variations

Pros: Fast, understands context well, good for ideation

Cons: Can be wordy, sometimes too formal, requires heavy editing

When I use it: First draft generation, testing multiple angles

Claude (Sonnet/Opus)

Best for: More nuanced, human-sounding copy

Pros: Better at conversational tone, less formulaic, stronger editing

Cons: Sometimes too cautious, can over-explain

When I use it: High-value campaigns, improving existing drafts

Jasper/Copy.ai/Writesonic

Best for: Templates and frameworks

Pros: Built-in templates, good for beginners

Cons: Very generic output, obvious patterns, limited customization

When I use it: Rarely. The specialized tools aren't better than ChatGPT with good prompts.

Real Examples: Before and After AI

Example 1: Generic AI vs Good AI

What Changed:

• Started with specific observation (hiring SDRs)
• Named the actual problem (infrastructure pressure)
• Gave concrete proof (97% deliverability)
• Shared insight (rotating domains, warm-up)
• Simple ask (audit)

Example 2: Using AI for Subject Lines

Subject lines are perfect for AI testing because you can generate 20+ options in seconds.

This gives you real options to A/B test, not just slight variations.

Advanced AI Techniques

Technique 1: Persona Emulation

Train AI to write in a specific voice by showing examples.

Technique 2: Objection Handling

Use AI to anticipate and address objections preemptively.

Technique 3: Research Synthesis

Feed AI prospect research and have it extract the relevant hooks.

The Biggest AI Mistakes to Avoid

Mistake 1: Using AI for Personalization at Scale

AI is terrible at fake personalization. "I saw you recently posted about [topic]" when it's clearly templated? Recipients see through it immediately.

Better approach: Use AI for the structure and core message. Do real personalization manually for high-value prospects, or don't personalize at all (honest generic beats fake personal).

Mistake 2: Not Testing AI Output

AI makes stuff up. It will confidently state facts about companies that aren't true. Always verify anything specific.

Mistake 3: Over-Relying on AI Edits

If you ask AI to "make this better" 5 times in a row, you'll end up with bloated, over-optimized copy that sounds like a marketing brochure. Know when to stop.

Mistake 4: Ignoring Your Own Voice

The best emails sound like they're from a human, not a company. AI defaults to corporate voice. You need to inject personality back in.

My Current AI Workflow

Here's exactly how I use AI for cold email campaigns now:

For New Campaigns (High Value)

1. Research the target (30 minutes, manual)
2. Write strategy brief (10 minutes, manual)
3. Generate 5 angles with AI (5 minutes, ChatGPT)
4. Pick best angle, refine with AI (5 minutes, Claude)
5. Heavy manual editing (10 minutes, me)
6. Test with real prospects (ongoing)

For Volume Campaigns (Scaled)

1. Create master template (manually, once)
2. Use AI for variations (different industries/roles)
3. Batch edit for tone (remove AI patterns)
4. A/B test versions (ongoing)

For Follow-Ups

1. Write first email manually
2. Use AI to generate follow-up sequence (different angles)
3. Edit for brevity (follow-ups should be shorter)

Tools That Integrate AI with Cold Email Platforms

Some cold email platforms now have built-in AI features:

Instantly.ai AI Features

Built-in AI personalization variables, subject line suggestions. Useful but generic—I still prefer custom prompts.

Lemlist AI

AI-powered icebreakers, image generation. Creative but time-consuming to set up properly.

Apollo AI Features

AI-generated first lines based on prospect data. Hit or miss quality—always edit before using.

The Future of AI in Cold Email

Where is this all heading? Here's what I predict for 2025-2026:

What's Coming

• Better personalization at scale: AI will get better at synthesizing prospect data
• Voice-based AI: Dictate your strategy, AI writes the email
• Real-time optimization: AI adjusts campaigns based on early results
• Multi-channel coordination: AI manages email + LinkedIn + calls cohesively

What Won't Change

• Strategy still matters most: AI can't fix bad targeting
• Human editing required: AI output will still need refinement
• Recipients get smarter: They'll keep recognizing AI patterns
• Authenticity wins: The more AI is used, the more real human touch stands out

When NOT to Use AI

AI isn't always the answer. Skip AI when:

• Targeting 10-20 dream clients: Write manually, it's worth the time
• Following up on a conversation: Reference specific details only you know
• Responding to replies: Real replies deserve real responses
• You're learning cold email: Write manually first to understand what works
• The email needs deep expertise: AI doesn't know your industry like you do

Final Thoughts

AI is a tool, not a strategy. It can write faster than you, generate more variations, and help you test ideas quickly.

But it can't:

• Understand your prospect's real situation
• Know what makes your offer unique
• Recognize when to break the rules
• Add the human touch that makes emails memorable

Use AI to amplify your skills, not replace them. The best cold emailers in 2025 will be the ones who master AI as a collaborator while keeping the human element that makes emails work.

Start with good strategy. Use AI for execution. Edit heavily. Test relentlessly.

That's the formula.