@jin.henry.dev2AI & Full Stack Engineer, Independent
AI Challenge: How Do We Turn AI Potential into Real Business Value?
AI is evolving faster than ever, but many businesses are still struggling with one important question:
How can we turn AI technology into practical solutions that solve real business problems and generate measurable value?
For example:
- How can small businesses use AI to reduce operational costs and improve productivity?
- What are the biggest challenges in integrating AI into existing business workflows?
- Is the biggest barrier to AI adoption the technology itself, or the lack of people with the right skills and experience?
- How can independent developers and small businesses collaborate to bring AI-powered products to market?
I'd love to hear different perspectives from people working in this space.
I'm also open to exploring potential business ideas and exchanging skills with other founders, developers, and small business owners who are interested in AI, technology, and entrepreneurship.
What's the biggest AI-related challenge you see businesses facing today, and how would you solve it?
Let's discuss! 🤝
Introductions
Comments5
From what I see with small businesses, the barrier usually isn't the technology. It's that nobody has looked at how the work actually flows. Owners ask for "AI", but what they need first is to see where leads get stuck and where time leaks. Once that's on one screen, the right automation is usually obvious, and small. Start with the most annoying task, run it alongside the manual way until the team trusts it, then move to the next one.
I completely agree. AI delivers the most value when it solves a clearly identified business problem rather than being implemented just for the sake of using new technology.
Starting with one repetitive, time-consuming task and proving its value is a practical way to build trust and achieve measurable results.
I think there's also a great opportunity for developers and small business owners to collaborate, identify these workflow bottlenecks, and build simple AI solutions that make a real difference.
In your experience, which business process offers the best starting point for AI automation?
Honestly, the first step isn't a process, it's people. I sit with the owner and the team and ask how the work really runs. Then lead tracking: is anyone measuring where leads come from and how fast they get an answer? Often nobody is. Then the CRM: usually everything is already written there, just not in a way anyone can use, so I have Claude read through it and pull out next steps, callback times, what's missing. Only after that come automations and integrations, and by then it's clear which ones are worth building.
In GTM specifically, the barrier is rarely the model. It's that nobody mapped where a lead actually sits for hours before a human touches it.
5 comments
From what I see with small businesses, the barrier usually isn't the technology. It's that nobody has looked at how the work actually flows. Owners ask for "AI", but what they need first is to see where leads get stuck and where time leaks. Once that's on one screen, the right automation is usually obvious, and small. Start with the most annoying task, run it alongside the manual way until the team trusts it, then move to the next one.
I completely agree. AI delivers the most value when it solves a clearly identified business problem rather than being implemented just for the sake of using new technology.
Starting with one repetitive, time-consuming task and proving its value is a practical way to build trust and achieve measurable results.
I think there's also a great opportunity for developers and small business owners to collaborate, identify these workflow bottlenecks, and build simple AI solutions that make a real difference.
In your experience, which business process offers the best starting point for AI automation?
Honestly, the first step isn't a process, it's people. I sit with the owner and the team and ask how the work really runs. Then lead tracking: is anyone measuring where leads come from and how fast they get an answer? Often nobody is. Then the CRM: usually everything is already written there, just not in a way anyone can use, so I have Claude read through it and pull out next steps, callback times, what's missing. Only after that come automations and integrations, and by then it's clear which ones are worth building.
I completely agree with this approach. Understanding how people actually work and identifying operational gaps should come before introducing any AI solution. Otherwise, automation can simply make an inefficient process run faster without solving the underlying problem. I particularly like your point about making existing CRM data actionable. There's significant potential for AI to turn business information into useful insights, prioritized tasks, and timely follow-ups. By the way, I'm also interested in exploring AI training platforms such as Handshake AI and Mercor as opportunities to leverage technical skills and generate additional income. Have you had any experience working with these platforms, or explored similar opportunities?
In GTM specifically, the barrier is rarely the model. It's that nobody mapped where a lead actually sits for hours before a human touches it.