AI mobile app development (according to Topflight Apps’ experience) carries challenges often not associated with developing traditional IT products for many reasons:
1. AI products are probabilistic, not deterministic, because the market is emerging, and many ifs exist.
2. Data access is still prohibitive; sales can be inherently slow, and determining market direction may be a lot of trouble.
3. It’s hard to determine potential buyers’ AI fluency during artificial intelligence application development, especially when deploying a product in an untapped market.
But even with these limitations, the smart move is to niche down your AI product or service offering. Even in the traditional IT market, developing a product that offers all-around functions to multiple industries is a farce. A startup’s core marketing task is to find the market a product is most useful and dig into the market. But it can be more challenging than it sounds. First, marketers must access enough data to find what customers are best satisfied and repetitive and what niche is best served with an AI product.
For example, a chatbot that can help in the retail finance industry in the US may not be well suited for the retail finance industry in the United Kingdom. Laws and regulations like the GDPR, market language, and functionality requirements of the US market differ from the UK market, even though both markets are in the finance industry. A chatbot that sends repetitive messages in the finance industry may not be viable in eCommerce. The finance industry alone can be broken into different businesses within which a chatbot can exist. And within each business, we have different languages and customer needs. A chatbot learning the nuances of the finance industry may confuse itself when introduced to the nuances of eCommerce.
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ChatGPT, for example, isn’t an AI for all industries. It is an AI created to help content creators develop the perfect or near-perfect copy or written content for different niches. ChatGPT learns language itself, but it is inherently niched, and we suppose that the creators will continue to tweak its functionality to ensure that it serves specific markets the best. Imagine ChatGPT extending to include the healthcare environment. Imagine the challenges if the creators want to make an AI app for Android for patient-doctor communication. Imagine the unimaginable and robust infrastructure it will need to be able to function as a repetitive customer support bot for patients looking to book or consult medical professionals!
With AI, context is extremely important because not only are you creating a technology that helps people through certain tasks, you are creating a technology that is supposed to learn the nuances of the industry it operates. Conflicting data can result in reduced performance.
Three Things to Consider When Deciding a Niche for Your AI App Development
Marketing that Resonates
In artificial intelligence app development and every other industry, marketing that resonates differs in principle from marketing that appeals. Even if you hire the best videographers and create a 30-second advertisement that moves your audience to tears, they will wipe their tears and still not buy your product if it does not resonate with their needs. In recent times, people have placed emotions over resonation when developing marketing plans. An emotional marketing campaign can make people buy what they do not need; however, you will not be able to convert a buyer into a repetitive buyer. This is also the reason why some companies spend horrendous money on marketing while others seem always to have the market in their palms.
When your AI product resonates with a prospect, the prospect will most likely buy the product and renew a subscription or product whenever necessary. According to a Harvard Business Review publication, a marketer’s dream is to find an underserved or untapped customer segment and create a product or service offering for the segment.
Niche Your Product
When people consider leviathan companies like Google, they assume that their products offer multiple services. However, Google is, first and foremost, a search engine. Facebook is a social media company. These companies, by extension, offer many other services, but their products are inherently niched and tailor-made to help people in unique ways. Your AI mobile application must solve unique problems.
Focus on Your Niche
Again, focus on your niche and develop your product’s brand image from an intrinsic point. If Discover adopts your AI mobile app, it becomes easier to pitch to other companies like America Express because you have niched the product within the credit card industry and can build momentum.
Conclusion
AI application development is probabilistic, not deterministic, and while experts feel like AI can really take off, there is still an enormous chance for failure. As a startup, your belief in the market should surpass your belief in the product. When you follow the market, you know when to start and when to stop in your AI app development.
