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AI-powered follow ups: How to automate responses without sounding like a bot

Manual follow ups don’t scale. Support teams get busy and responses fall through the cracks. Meanwhile, transactional and timed messages lack context and sound robotic.

Here’s how to do follow ups at scale without reducing quality — i.e. here’s how to set up an AI agent that can handle your follow ups while personalizing, adapting, and taking real action.

How to set up AI-powered follow ups

Step 1: Identify where AI follow ups are needed

Start by finding the biggest gaps in your follow-up process:

  • Where do customers usually go silent?

  • What questions take too long for support to answer?

  • Which follow ups are frequent and repetitive? feel repetitive for your team?

Common use cases:

  • Sales: AI agent reaches out to leads who abandoned checkout.

  • Support: AI agent checks in after a ticket is closed.

  • Onboarding: AI agent guides users who didn’t finish setup.

Step 2: Build your AI agent

Now, it's time to actually get your AI up and running. This means choosing the right AI tool and setting it up to handle follow ups effectively.

How to do it:

  • Choose an AI platform: Pick a pre-built tool (like Jotform AI Agents, HubSpot) or build your own with frameworks like OpenAI or Dialogflow.

  • Decide its role: Will it follow up on leads? Help new users? Answer questions? Be clear.

  • Create initial response templates: Start with a few basic responses AI can use before fine-tuning with real conversations.

Step 3: Train AI on real conversations

AI is only as good as what it learns. If you train it on rigid, scripted responses, it will sound like a bot.

How to do it:

  • Use past support emails and chat logs to train AI agents on real user questions.

  • Upload FAQs and help docs but teach AI agents to summarize naturally.

  • Set clear rules on when AI agents should hand off to a human.

Step 4: Connect AI to your CRM for personalized follow ups

A good follow up feels personalized, not automated. To make this happen, AI agents need access to genuine user data.

How to do this:

  • Connect the AI agent to CRM systems so it knows customer names, past interactions, and purchase history.

  • Enable dynamic response generation (e.g., “Hey [First Name], your order #[12345] has been shipped.”).

  • Review and test the AI agent’s responses to real customer queries to ensure that the responses sound natural.

Step 5: Automate follow ups across multiple channels

Everyone has their preferred way to stay in touch, so a single follow-up method just doesn't cut it. AI agents can help reach people in places that feel convenient and easy for each person.

Where AI agents can send follow-ups:

  • Email: For those detailed updates

  • Live chat: For instant help

  • Texts(SMS): For those snappy confirmations

  • WhatsApp: For a more personal touch

  • Phone calls (AI voice agent): When a direct response is the best option.

Step 6: Monitor AI performance and fine-tune

Even the best AI agents need improvement over time

How to track AI success:

  • Monitor response rates: Are people replying to AI agent follow ups?

  • Check resolution times: Are AI agents actually solving problems faster?

  • Review conversation logs: Fix any awkward or incorrect responses.

AI agent follow ups should evolve based on real customer interactions.

How to not sound robotic

A great AI-powered follow-up should feel like it was written by a human — quick, spot-on, and actually helpful.

Here’s how to make that happen:

1. Keep it personal

Automation fails because it often feels too generic. AI agents should be able to reference real customer details so responses don’t feel mass-produced

What doesn’t work: "Hello, valued customer! We wanted to check in."

What works: “Hey Sarah, I noticed you started to set up your account but you never completed it. Need help?"

How to do this:

  • Integrate the AI agent with your CRM data so it knows customer names and past interactions and history.

  • Let AI pull previous conversations so customers never have to repeat themselves.

  • Train the AI agent on support logs with real humans so responses feel natural

2. Adjust the tone based on customer sentiment

A one-size-fits-all tone doesn’t work. Your AI agent should recognize emotions and adjust accordingly.

What doesn’t work: "Your refund is being processed."

What works: "I totally get how frustrating that wait can be. It’s being processed, but let me see if I can find out when it’ll hit your bank account."

How to do this:

  • Turn on sentiment analysis in your AI tool or use a service like Google Cloud to detect emotions.

  • Adjust responses based on tone and urgency.

  • Add empathy statements before giving answers.

3. Make AI follow ups actionable, not just conversational

A follow up shouldn’t just be a check in. It should either instantly resolve the issue or drive the conversation forward.

What works:

Customer: “What’s the status of my refund?

AI: (Find refund ID → Check status → Send real-time update.)

Customer (frantically): "I need to reschedule my appointment."AI: (Finds time slots available → Proposes new times → Confirms booking.)

How to do this:

  • Allow the AI agent to connect with your support and order management systems so that it pulls real-time data.

  • Turn on automation in your AI tool (look for "Workflows" or "Triggers" in your settings) to let it update orders, reschedule meetings, and assign tasks. If your tool doesn’t have this, connect it to other apps using Zapier or APIs.

  • Let AI trigger human handoffs when an issue is too complex.

There you have it. If you're interested in giving it a try, check out Jotform's AI Agent.

on April 25, 2025
  1. 1

    Nowadays it's easy to get AI to write your emails, in your own tone. What brings real value is the integration, so people don't have to copy-paste the context and emails. That's what my new chrome extension FastQuill does, check it out!

  2. 3

    Is this post written by ai?

    1. 2

      Thought the exact same lol

    2. 1

      some of the comments do sound like AI...

  3. 2

    Love the focus on personalization. So many AI follow-up systems miss the mark by feeling canned. Have you found a sweet spot between automation and sounding genuinely human?

  4. 2

    Interesting approach to balancing automation with personalization. The emphasis on CRM integration for context-aware follow-ups seems particularly useful - it addresses the 'uncanny valley' problem many AI responses have.

    The sentiment analysis component is smart, though in practice I've found it requires very clean training data to avoid misinterpretations. How are you handling edge cases where tone detection might misfire?

  5. 1

    In the future, this bot will be talking to other bots... We're not too far off from this.

  6. 1

    Hey Aytekin, this is super cool. Your landing page is clear but I think a few small tweaks could boost signups. I’m a beginner copywriter and I’m practicing by helping startups for free in exchange for testimonials. Want me to give you a few suggestions?

    1. 1

      Hey Altaf! care to review my homepage and see what you think? Happy to write a testimonial for it! www.signalboard.dev

      1. 1

        Thanks for checking out my post, @Sherwell! I took a look at your homepage and have a few copy ideas that might boost engagement. Want me to send over a mini audit?

      2. 1

        Hi Sherwell, Thanks so much for reaching out!
        I messaged you personally on Instagram.
        Check it out!

  7. 1

    Manual follow-ups waste time. Most AI still feels clunky and scripted. What actually helps is letting it do something, not just reply. Connect it to real data, let it take action, and it becomes more than just support. It's follow-through. The point isn't just automation. It's making it actually useful.

  8. 1

    Loved this write-up, Aytekin! I’m building Afterburn Global Tek — a CloudOps/DevOps strike team for AI startups scaling fast under pressure. We’ve seen firsthand how powerful AI agents can be, but also how easy it is for teams to drown in tooling without clear execution strategy.

    The secret? Let AI do the grunt work — but put a human in the pilot seat who knows when to hit the throttle.

    Appreciate your tactical breakdown. If anyone here is dealing with growth-stage infra chaos, happy to connect or trade notes!

    — Will Duncan

  9. 1

    This is one of the clearest and most actionable breakdowns I’ve seen on scaling follow-ups with AI — especially love how it blends tech with empathy. The point about training AI on real conversations to avoid that “robotic tone” really hit home. Too many businesses treat automation like a one-size-fits-all fix, but this shows that nuance, tone, and timing matter just as much as efficiency.

    Also appreciated the emphasis on actionable follow-ups. It’s not just about checking in — it’s about actually doing something useful for the customer in that moment. That’s where AI shines when used right.

    Curious to hear your thoughts on maintaining that human-AI balance as teams scale — how do you prevent over-automation from creeping in?

  10. 1

    This is such a smart way to scale follow-ups without sacrificing quality! I love how you emphasized personalization—AI can definitely feel robotic without that human touch. I can see this being a huge time-saver for support teams, especially when it comes to handling repetitive tasks or keeping leads engaged.

    The idea of using sentiment analysis to adjust the tone based on customer emotions is particularly interesting. It’s something I think will set AI-powered follow-ups apart from traditional automation.

    Looking forward to seeing more tools like this. I’m definitely going to give it a try! Thanks for sharing the step-by-step guide.

  11. 1

    It's interesting that AI agents still follow drip campaign approach. Why didn't you link out to where we can try this btw?

  12. 1

    Great insights! This approach seems like a practical way to enhance follow-ups while keeping them personalized and efficient. Thanks for sharing.

  13. 1

    Very cool! My mind needs this.

  14. 1

    🔥 Super insightful post, Aytekin!

    This is one of the most practical and well-structured guides I’ve seen on scaling follow-ups with AI. Personalization at scale is such a challenge—especially in onboarding and support—and your step-by-step approach really breaks it down clearly.

    I'm currently building an AI-powered image detection app (ImgDetect) that helps users identify fake or AI-generated images. As a solo founder, I’ve been thinking about how to improve user onboarding and engagement without overwhelming myself. The idea of using an AI agent for contextual follow-ups is very appealing.

    Quick question:
    For indie makers at an early stage, do you recommend starting with pre-built tools like Jotform AI Agent or going with a custom solution using OpenAI APIs from the beginning?

    Thanks again for sharing—super valuable insights!

  15. 1

    Really helpful breakdown! I like how you explained making AI follow-ups feel more personal instead of robotic — that’s where a lot of businesses mess up.
    Have you noticed if certain channels (like email vs. SMS) work better for getting people to actually reply?

  16. 1

    i like dat! very useful article

  17. 1

    Thanks for sharing this information. If it passes Turing's test... please let us know :D

  18. 1

    This article captures the real challenges of scaling follow-ups without sounding robotic.
    I like how it focuses on personalization, sentiment analysis, and actionable responses — not just conversation.
    It’s a great blueprint for building a truly human-centered AI follow-up system.

  19. 1

    Great insights, the world needs this type of automation!

  20. 1

    This is exactly what today’s businesses need — genuine, human-sounding automation! It’s refreshing to see AI being used thoughtfully rather than just blasting robotic replies. Personalization at scale is the future, and this article nails how to balance efficiency with authenticity

  21. 1

    Wishing you success with your project! Have you thought about crowdfunding as a way to secure funding and build your audience?

  22. 1

    A.I is evolving day by day

  23. 1

    Great insight to have AI follow up in omni-channel.

    We saw a lot of freelance post asking for AI automation (like using N8N) for this purpose. We are not sure what is the business value, like save 6 hours per week.

    BTW, we help customers deliver AI phone agents. If you need, just ping offline.

  24. 1

    Thanks Aytekin, this was really helpful

  25. 1

    This is what I take away: AI can enhance outreach, but keeping the human touch is everything

    1. 2

      Indeed, the human touch is something that cannot be quantified—at least not yet.

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