In April 2023, I had my first real experience launching an AI business opportunity. At the time, I was part of a software services company. It was a small team where I worked directly with the owner, an exceptional programmer who loved experimentation. During a brainstorming session one day, he suggested building an AI product that could generate passive revenue for us.
At that point, there was a lot of hype around ChatGPT. Everyone was posting about the best prompts and different uses of the tool. But as we looked closer, we found a glaring gap: ChatGPT struggled with generating personalized content.
So, we decided to create a tool that could scan individuals’ Twitter (now X) profiles and generate content tailored to the individual. When we launched, we simply shared the link on X, hoping a few dozen users might try it out.
What happened next exceeded our wildest expectations. Within just 36 hours, over 150,000 people had used the tool. It went absolutely viral! This became my first-hand experience of how it was to be an AI entrepreneur. In this article, I’ll dig into the steps you need to take to become an AI entrepreneur. I’ll also share my experience. Let’s dive in!
Table of Contents
- How to Become an AI Entrepreneur
- Potential Areas for AI Entrepreneurs to Target in 2025
- Empowering Aspiring AI Entrepreneurs
How to Become an AI Entrepreneur
Step 1: Find the problem statement.
The foundation of any successful business lies in solving a meaningful problem. To thrive as an AI entrepreneur, focus on identifying real-world challenges and crafting innovative solutions to address them.
Here’s how my team identified a problem statement and found a product to build around it.
Marketers know that generating personalized content is very costly. The process requires intense computational resources. The data often involves millions of tokens. So the biggest need we found was to reduce the cost.
So, we tried to crack this problem. Our programming team built a context engine using Large Language Models (LLM). We hypothesized that LLMs should have the data necessary to produce personalized outputs (more on this in the steps below).
I get it — pinpointing the right problem to solve can be tough. You also have to avoid creating technology for technology’s sake. The idea is to target industries where AI can deliver significant value, such as healthcare, education, or retail.
To help spark your creativity, here are some AI business ideas that can inspire you and help you find unaddressed needs.
Step 2: Turn the problem into a business opportunity.
Once you have identified your challenge, do thorough research. Understand the nuances, how the problem impacts your audience, and what solutions are already available. This will give you a solid foundation for identifying gaps or inefficiencies that AI will address more effectively.
Remember, as an AI entrepreneur, your ultimate goal is to build an economically viable solution that delivers tangible benefits to your customers.
In the case of our experiment, the challenge was the cost. LLM models require constant training and high capital. We didn’t have that sort of money, but we didn’t want to give up either.
We put our thinking caps on and devised a way to test our theory. Instead of training the tool to pick up billions of data points, we restricted it to pick the data from the user’s X profile only. So essentially, users’ tweets became our building blocks.
Step 3: Make use of cutting-edge AI tools.
I think it’s smart to utilize existing AI tools and platforms in the market to build your own. As an AI entrepreneur, you can improve your tool development journey by leveraging platforms like PyTorch and TensorFlow.
Use Microsoft Azure, HubSpot, Google Cloud, and AWS for speeding up deployment, scaling growth, and unlocking actionable insights.
To build our AI personalization tool, our CTO, Saad Mughal, combined the following:
- ChatGPT.
- Google NLP.
- Elasticsearch.
That was back in early 2023. Fast forward to today, the landscape has evolved even further. Now, you have a wealth of AI tools at your disposal.
As computer scientist Fei-Fei Li aptly puts it, “Artificial intelligence is not a substitute for human intelligence; it is a tool to amplify human creativity and ingenuity.” In other words, make use of these tools to push the boundaries of creativity.
Step 4: Build a strong foundation in AI.
Before you start building products yourself, I recommend spending some time building a strong foundation in AI fundamentals. As an AI entrepreneur, you should have an in-depth understanding of algorithms, data, and models.
Here’s one of my biggest takeaways from our experiment: In order to build more impactful and data-driven prototypes, AI entrepreneurs must have an understanding of data science.
Ideally, you should also know the following:
- Supervised & unsupervised algorithms.
- Structured and unstructured data.
- Machine learning models.
- Ensemble learning.
- Deep learning models.
Step 5: Build a Minimum Viable Product (MVP).
Before developing a complete solution, it is necessary to test your idea. That’s where an MVP comes in. I believe there’s no such thing as a perfectly polished product at the start. The real progress comes from building something, putting it out there, and continuously refining it over time.
In the case of our MVP, the tool was trained to replicate the patterns, language, and tonality of users. We added a humorous element to churn out users’ style of typing into fun raps, bios, or answers making it look like the users wrote it themselves. This functionality of the tool became our unique selling point (USP) and users started outputting personalized content.
I learned that the key to success depends on engaging users. In our case, the tool helped users discover insights about “themselves” — this contributed to its rapid adoption. In fact, within 24 hours, we reached over half a million impressions.
We started getting up to 50,000 user requests per second. I would say that this is a rather unique case. That’s not something that usually happens when you test MVPs. We had to increase our server bandwidth. We found that our users even understood the issue.
A key lesson to take away: Listen to your customers. We did that by using our load-balancing capability. The speed with which we scaled the server contributed to the exponential growth of the tool. And, users appreciated it!
The tool also gained significant attention organically, with several news outlets covering the story of how we developed it.
Our product wasn’t monetized initially. However, we started receiving emails inquiring about how to purchase the product and even RFPs from other organizations to build AI products using the same technology. That was our cue to refine our MVP and transition away from offering free access.
Step 6: Keep ethical considerations in mind.
This step is essential and often overlooked. From what I’ve observed, the rise of AI has always been intertwined with discussions about ethics.
Adhering to all relevant regulations and laws can be one of the most challenging aspects of developing an AI product. It is, nevertheless, a crucial step to ensure the product’s success and sustainability in the long run.
I suggest keeping the following things in mind:
- Data. Use diverse sets of data. This means that your product is not biased and is providing the most accurate representation of reality.
- Algorithms. It is necessary to create transparent algorithms. This way users can understand why a particular action is being taken or a decision is being made.
- Regulations. Be up-to-date with changing AI regulations. For instance, if you’re based in Europe or looking to expand in the region, keeping a close eye on the E.U.’s AI Act is important.
To put it simply, take the necessary steps to make sure the AI product doesn’t pose any inappropriate risks.
Step 7: Start marketing the product yourself.
As the entrepreneur behind the product, you are in the best position to tell its story. Use LinkedIn to share updates, product demos, and success stories. In fact, many founders have started building in public. I personally feel that X is a great place for doing that.
Authenticity matters — people want to hear directly from you. If possible, share case studies showing how your AI tool solves real problems.
Join relevant online communities like Reddit or industry-specific forums where your target audience hangs out. Offer value by answering questions and sharing your tool when appropriate.
If your solution is good enough, people will reach out to you themselves. The key here is to make the products beneficial for users.
The importance of partnering with influencers, other entrepreneurs, and organizations in the AI space to cross-promote cannot be overstated. In fact, it’s so important that it deserves its own dedicated step.
Step 8: Connect yourself with others in the industry.
From my experience, I highly recommend connecting with industry leaders. Keep an eye out for ongoing AI trends. Subscribe to popular AI platforms and publications. Participate in AI forums to expand your network.
What truly made a difference for me — and something I feel incredibly fortunate about — was being surrounded by brilliant minds.
Although I moved on from the company that created the personalized tool, I still keep in touch with the CEO, Hammad Khan. During one of our conversations, he shared how he had been collaborating with a law firm that had identified a major bottleneck: the time-consuming task of reading through lengthy documents and paperwork, which slows down the entire documentation process.
Once he recognized this challenge, he knew exactly what needed to be done. With his technical expertise, he developed an AI tool designed to automate the mundane document work for lawyers.
So, building a strong network of experts will give you insights into existing ideas in the industry. Remember, the idea is to provide a much-needed solution to a critical issue in any field. By addressing the pain point, you’re on the right track to attracting clients in the industry.
Step 9: Secure the right resources/funding.
This step comes last for a reason. Seeking venture capital or angel investors should not be your initial goal. This should be a means to scale your business after you’ve validated your product and successfully marketed it to users.
If you have followed all the steps above, you may have already secured clients to sustain your business or attracted experts in the tech and AI space who are willing to invest in your product.
Even if not, another alternative worth exploring is government funding or grants tailored for AI entrepreneurs. If applicable, your region may even have accelerator programs designed to support your growth.
It is also important to communicate the value of your product — a basic salesman rule that applies to entrepreneurs as well. If you want to sell your product, you should be well-versed in convincing people why they/their company needs it.
It’s equally important to clearly communicate to investors what sets your AI product apart and why it will attract users or buyers. In our case, our USP was solving the challenge of handling large, costly datasets by developing a cost-effective approach to processing and storing data.
Potential Areas for AI Entrepreneurs to Target in 2025
In my opinion, here are several areas that present opportunities for AI entrepreneurs to explore in 2025:
- Legal. You could build a digital lawyer to give insights on where a particular case would go. You can also build a product that streamlines contract analysis and legal research.
- Healthcare. Digital doctors are already being developed using AI to give second opinions based on reports and a patient’s medical history. Other target areas include health monitoring and addressing inefficiencies in AI-powered telemedicine platforms.
- Sustainability and Environmental AI. AI tools can help optimize energy consumption, use existing resources efficiently, and scale sustainable farming practices.
- Financial research. There’s already a lot of work being done using AI to offer predictive analytics, automated trading systems, and fraud detection. Building a financial research assistant with instant access to your numbers is an area where a smarter financial product could be built — for both consumers and businesses.
- Retail and Ecommerce. Opportunities still exist in areas like personalized recommendations. For instance, an ecommerce store can tailor its marketing material and product offerings based on individual customer profiles.
As technology evolves, one thing is certain for aspiring AI entrepreneurs: The opportunities available today are unparalleled compared to the past, with far fewer technical barriers to overcome than ever before.
According to the CEO of DeepMind, Silvio Savarese, “I’ve long believed that AI won’t just enhance the way we live, but transform it fundamentally. AI is placing tools of unprecedented power, flexibility, and even personalization into everyone’s hands, requiring little more than natural language to operate.”
Empowering Aspiring AI Entrepreneurs
It is safe to say that aspiring entrepreneurs in this industry will turn out to be successful if they can balance responsibility and innovation.
Remember, innovation doesn’t always require groundbreaking ideas.
In fact, the most successful businesses are built by enhancing and optimizing existing processes rather than reinventing the wheel. By offering solutions that truly make a difference, you’ll ensure your business stands out and drives impact.
2025 is the perfect time to dive into the world of AI entrepreneurship and capitalize on the growing demand for AI-driven products and services.