Written by Lidia Vijga
Looking for that once-in-a-lifetime opportunity to create the next big thing with AI? That moment is now. We’re currently living through a revolution. It’s not exaggeration; it’s reality. Just a few years ago, AI was mostly hype. And now? It’s everywhere. The tipping point came with GPT-3.5 and 4. These models blew past expectations, impressing even the most skeptical experts.
In this article, I want to share how to evaluate and pick an AI idea that’s worth pursuing. What to look for, what to avoid, and most importantly, where to start and how to think bigger.
The Evolution of AI Technology
What’s fascinating is how quickly things are changing. In 2017, the “Attention is All You Need” paper laid the groundwork for modern language models. Fast forward to today, and we’re seeing multimodal AI that can generate text, images, and even video. It’s mind-boggling.
Key players in the AI industry
The AI field is a mix of tech giants and scrappy startups. OpenAI, Google, and Microsoft are the heavyweights. They’re pushing the boundaries with massive models and seemingly endless resources.
But don’t count out the underdogs. Startups are innovating at incredible speeds. They’re finding niches and solving specific problems that the big players overlook. And let’s not forget the open-source community. They’re democratizing AI, making powerful tools accessible to all.
The difference between general AI and specialized AI applications
Here’s where it gets interesting for us founders. General AI, like ChatGPT, is impressive. It can handle a wide range of tasks. But specialized AI? That’s where are the real opportunities.
Specialized AI focuses on specific domains or tasks. It’s like the difference between a jack-of-all-trades and a master craftsman. General AI might be able to do a bit of everything, but specialized AI excels in its niche.
Take sales, for example. A general AI might help draft emails. But a specialized AI could analyze years of sales data, understand industry-specific jargon, and provide tailored strategies for closing deals. That’s the kind of value that customers will pay for.
The key is to find that sweet spot. Where can AI solve a specific, painful problem? It might not be as flashy as general AI, but it’ll be far more valuable to your target market.
The next big thing often starts small and focused. Don’t be afraid to dive deep into a niche and follow the money. That’s where you’ll find your billion-dollar idea.
How to Identify Promising AI Startup Ideas
Want to know a secret? The best AI startup ideas are often found in the most mundane places.
Look for boring but essential tasks
Boring tasks are goldmines. Why? Because they’re essential, yet overlooked. Everyone’s chasing the next shiny thing. But real value? It’s in the grunt work.
Think of automation for government contract searches and RFPs.
There are still individuals out there spending all their days refreshing government websites. Searching for contracts. Submitting proposals. Mind-numbing work, right?
This is a perfect use case for LLMs. Think about it. Repetitive tasks. Information processing. It’s what AI excels at.
There is actually a startup that has implemented an AI in this specific niche. The founders already saw this opportunity. They built a tool to automate the process. Boom! Instant traction. Why? Because they solved a real problem.
Here’s the thing about everyday mundane problems: they’re everywhere. Every industry has them.
AI can transform these tasks. It’s not just about saving time. It’s about unlocking potential. Freeing up humans to do what they do best: think creatively, strategize, innovate.
At DeckLinks, we’re always looking for these opportunities. Where can AI streamline our processes? How can it make our users’ lives easier?
The next big thing might not look exciting at first glance. It might be buried in spreadsheets or hiding somewhere in back-office operations. But if it solves a real pain point? That’s where you should start digging for it.
So, my advice? Embrace the boring. Look for those tasks that make people groan and whine. That’s where you’ll find your golden AI startup idea.
Focus on specific industries or use cases
Let’s get real. The AI gold rush is on, and everyone’s trying to strike it rich. But the real winners are those who dig deep into specific industries and build a laser-focused solution that solves real problems.
Healthcare
Healthcare is ripe for AI disruption. Think about it. Mountains of data. Life-or-death decisions. Overworked staff.
AI could revolutionize diagnostics. Streamline patient care. Accelerate drug discovery.
But you can’t just walk in with a generic AI solution. You need to understand the nuances. The regulations. The workflows.
One startup I admire is focusing solely on using AI to interpret medical images faster and more accurately. Or optimizing hospital staffing to reduce burnout.
Finance
Money talks, and in finance, AI is becoming the new language.
From fraud detection to algorithmic trading, the opportunities are endless. But again, specificity is key.
I’ve seen startups succeed by tackling specific challenges. Like using AI for credit risk assessment. They’re not trying to boil the ocean. They’re solving one problem exceptionally well.
Legal
The legal industry might seem old-school, but it’s begging for AI innovation.
Contract analysis. Legal research. Predictive case outcomes. These are goldmines waiting to be tapped.
Here’s the bottom line: pick an industry. Dive deep. Understand its unique challenges. Then build an AI solution that speaks directly to those needs.
This is not about being everything to everyone. It’s about being indispensable to someone.
Reimagine existing software with AI capabilities
Here’s a thought that keeps me up at night: what if we could rebuild every piece of software from the ground up with AI? It’s not just a pipe dream. It’s happening right now.
The key is to look at existing software with fresh eyes. Don’t just slap an AI chatbot on top and call it a day. That’s lazy thinking. Instead, reimagine the entire user experience.
Let’s talk about CRMs. They’re the lifeblood of sales teams. But most of them? They’re glorified databases. Useful, sure. But revolutionary? Hardly.
Now, imagine a CRM powered by AI. It doesn’t just store data. It analyzes it. Predicts it. Acts on it.
Let’s just look into the future for a second here. You log in on Monday morning. The AI has already prioritized your leads based on the likelihood of closing. It’s drafting personalized follow-up emails for each prospect. It’s even suggesting the best time to make your calls.
But it doesn’t stop there. This AI-powered CRM is learning from every interaction. It’s identifying patterns in successful deals. It’s coaching you on your sales technique in real-time.
This isn’t science fiction. It’s the near future of sales software. And it’s just one example of how AI can transform existing tools.
The opportunities are endless. Project management software that predicts bottlenecks before they happen. Design tools that generate mockups based on a simple text description. Accounting software that not only tracks expenses but also provides strategic financial advice.
Here’s my advice: look at the software you use every day. What frustrates you about it? What manual tasks do you wish it could do for you? That’s your starting point for an AI-powered reimagining.
And again, the goal isn’t to replace humans. It’s to augment them. To free them up to do what they do best: think creatively, build relationships, and make strategic decisions.
The future belongs to those who can blend the best of human intelligence with the power of AI. So, don’t just build another app. Reimagine an entire category of software.
Explore AI applications beyond chatbots
Let’s face it: chatbots are so 2022. Don’t get me wrong, they’re useful. But if you’re only thinking about chatbots, you’re missing the bigger picture.
Voice AI agents
Voice is the new frontier. It’s natural, it’s hands-free, and it’s incredibly powerful.
Voice AI agents are always on, never take breaks, and can handle multiple calls simultaneously. It’s not just about cost-saving. It’s about scaling customer service in ways that were previously impossible for small businesses.
These aren’t just glorified answering machines. They’re intelligent agents that can understand context, ask follow-up questions, and even detect emotion in a caller’s voice.
Multimodal AI systems
Multimodal AI can process and generate different types of data – text, images, audio, video – all at once. It’s like giving AI a full set of human senses.
I recently saw a demo of a multimodal AI system for e-commerce. It could take a photo of a room, understand the style and color scheme, and then recommend furniture pieces that would fit perfectly. All in real-time.
Think about the applications. In healthcare, it could analyze patient symptoms across multiple data types – medical history, x-rays, and even the patient’s voice during a consultation. In education, it could create personalized learning materials that combine text, images, and videos based on a student’s learning style.
Here’s my advice: don’t limit yourself to text-based AI. Look for opportunities where combining multiple data types could solve complex problems in innovative ways.
The future of AI isn’t just about smarter algorithms. It’s about creating more human-like interactions and insights. So think big, think multimodal, and you might just stumble upon the next big thing in AI.
Avoiding AI Startup Pitfalls
Beware of “tarpit” ideas. Let me tell you about a trap I’ve seen many founders fall into. It’s called the “tarpit” idea. Sounds intriguing, right? Well, it’s not as fun as it sounds.
A tarpit idea is like a shiny object that lures you in. It looks promising from afar. But once you’re in, you’re stuck. It’s quicksand for startups.
I’ve seen it happen. A friend of mine got excited about building an “AI co-pilot” for businesses. Sounds great, doesn’t it? Everyone wants an AI assistant. He got lots of interest, even some early customers.
But here’s the catch: nobody knew how to use it effectively. It was too general. Too unfocused. In the end, it solved no real problems.
So, how do you spot a tarpit before you’re knee-deep in trouble? Here’s what I’ve learned:
First, be wary of ideas that sound too good to be true. If it seems like it could solve everything for everyone, it probably solves nothing for no one.
Second, look for specific, tangible problems. That focus will keeps you out of the tarpit.
Third, talk to real users. Not just people who say they’re interested, but people who will actually use and pay for your solution. If they can’t articulate exactly how it’ll help them, you might be heading for a tarpit.
Finally, be honest with yourself. Are you excited about the technology, or the problem you’re solving? If it’s just the tech, watch out. That’s tarpit territory.
Trust me, the view from solid ground is much better than the one from the bottom of a tarpit. Choose your AI battles wisely.
Evaluating the Long-term Potential of an AI Startup Idea
Let’s talk about the future. Not just next year, but five, or ten years down the line.
Assessing scalability and market size
Here’s the thing about AI startups: they can scale fast. Really fast. But only if you’re targeting the right market.
I’ve seen founders get excited about niche problems. That’s great for starting out. But ask yourself: can this grow? Is the market big enough?
Look at the numbers. Really dive into them. And don’t be afraid to think big. If your AI solution works for one industry, could it work for others? That’s where true scalability lies.
Considering defensibility against larger AI companies
Let’s face it: the big tech giants are in the AI game. And they’ve got deep pockets. So how do you compete?
The key is to be irreplaceable.
Here’s my advice: go deep into a vertical. Understand the nuances that the big players miss. Build relationships. Gather data that no one else has.
Remember: big companies move slow. They can’t specialize in everything. That’s your advantage. Use it.
Potential for creating an ecosystem
Now, this is where things get exciting. Don’t just think about building a product. Think about building an ecosystem.
I recently met a founder who started with an AI tool for legal document analysis. And now, they’re building an entire ecosystem for law firms. Document analysis, case prediction, and client management – all powered by AI.
That’s the dream. To become the go-to platform in your industry. It’s not easy, but it’s where the real value lies.
Think about it: could your AI solution be the foundation for other tools? Could developers build on top of it? Could it become the ‘operating system’ for your industry?
Here’s the bottom line: building a successful AI startup isn’t just about having cool tech. It’s about creating long-term value. It’s about becoming indispensable to your customers.
So, as you evaluate your AI startup idea, don’t just think about the now. Think about the future. Can it scale? Can it defend against the big players? Can it become an essential ecosystem?
Answer these questions honestly, and you’ll be well on your way to building not just a startup, but a lasting, impactful company.
Final Thoughts
We’ve covered a lot of ground, haven’t we? Let’s wrap this up.
Choosing the right AI startup idea isn’t easy. But it’s not rocket science either. Remember: look for the boring but essential tasks. Focus on specific industries. Reimagine existing software. And don’t get stuck in the chatbot trap.
Here’s the thing: the best AI ideas aren’t about the coolest tech. They’re about solving real problems.
So, ask yourself: what problem am I really solving? Who’s life am I making better? If you can answer those questions, you’re on the right track.
As I mentioned already we’re living through a revolution. The opportunities in AI are massive. They’re transformative. And they’re happening right now.
Don’t wait for the perfect idea. Don’t wait for someone else to build it. The time to act is now.
Will it be easy? No. Will there be challenges? Absolutely. But that’s what makes it exciting.
So, go out there. Explore. Experiment. Fail fast and learn faster. The next big AI breakthrough could be yours.
Every giant tech company started with a simple idea and a lot of hard work. And your AI startup could be next.
