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An Exhaustive Guide to AI App Developmentby@Smruti_26
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An Exhaustive Guide to AI App Development

by Smruti HingnikarMay 18th, 2017
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By now, we all have at least once heard about the technology called <a href="https://hackernoon.com/tagged/artificial-intelligence" target="_blank">artificial intelligence</a> or AI. In a layman’s language it is a process of linking the system with human intelligence so that it can perform the assigned tasks automatically, based on the customer’s preference and choice.

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By now, we all have at least once heard about the technology called artificial intelligence or AI. In a layman’s language it is a process of linking the system with human intelligence so that it can perform the assigned tasks automatically, based on the customer’s preference and choice.

Xavier Amatriain, VP of engineering at Quora, in his interview with Arkenea explained AI as: “Artificial intelligence is this idea of building machines or building systems which basically are able to think and have intelligence for themselves.”

While almost every app development company is trying their best to successfully inculcate AI in their tech product, there are some major points to consider when it comes to its implementation.

I researched about artificial intelligence and it’s development process, with which, here are some tips to remember during the product development life-cycle for AI apps so that it solves the customer’s problem in the easiest and the most convenient way.

1. Research in-depth about the process before going for the development

AI has a long way to go in terms of user reach and technology advancement, both. Since there is such a vast variety of topics to work on and improve upon, serving everything in just one product is not possible. One needs to reach into the depth of the subject and come up with something which handles the crucial problems of the users with efficiency and reliability.

AI is no doubt a vast ocean to be explored. So, once you find the problem to solve, it is also important to do an extensive research before starting to develop it. A well researched problem will surely help in finding the apt solution.

While talking about chatbots, Vladimir Getselevich, CTO and founder at Robinlabs says, “I will answer from my years of experience in developing conversational personal assistants and chat-bots. The only way is to go in-depth in more limited but still useful vertical domains.”

2. Make sure you develop a relevant product

It is very important that you build a product that users can trust. Since AI is comparatively new for the users, it become a bit of a task to make them trust the product. For this, it is very necessary to develop a relevant app. As published in HBR, it is important that you show the benefits of your app to the users so much so that they would just not only fall in love with it, but also trust it enough to start using it regularly to solve their issues.

AI is an opportunity of innumerable advancement and discoveries. Any product which is useful today will surely be 10x better tomorrow once more research is done about it in future. You just need to focus on user’s feedback and looking for the demands they are making according to their problems.

While creating an AI app, always keep a few things in mind as said by Shivon A. Zilis, Partner at Bloomberg Beta, Advisor at OpenAI, “It is useful today. The best part about MI apps is that if they are useful today they will get even better over time, assuming the developers have put thought into creating the right user feedback loops to enhance the dataset over time.”

3. Identify the pain points where you are supposed to put efforts

It can be very intimidating to take up the entire problem at once and start working on it. But it will always be a far wiser choice to pick up a subset from the problem and work towards solving it.

Along with this, you have to figure out that one thing you can excel at and relentlessly work on it for the betterment to provide a good customer service. A strategy in which you do develop an AI app just for the sake of it will never work.

Dr. Rob McInerney, founder and CEO at Intelligent Layer has explained, “The greatest advice I can give to entrepreneurs looking to build AI into their app is to follow the 80/20 rule and understand how to manage uncertainty.”

There is no doubt in it that around 80% of the effects come from 20% of the causes. So if we are successful at grabbing that pain point which is causing most of the problems, you can surely attract more users towards your product.

4. Always proceed by keeping human benefits in mind

It is very natural to think about making a product or an app which would give you a good revenue. But that is where most of the apps fail. Always look from the user point of view. Observe keenly and identifywhere the shoe is pinching. This is the best way to make your app successful. There is no point in showing the problem to the user which doesn’t even exist for them in the first place.

Solving the problem which people face in their day-to-day life is more attractive to them. They might not be concerned about something which bothers them once in while.

Jack C. Crawford, founder & CEO at Datalog.ai says, “When developing an advanced technology product for human use, it’s best to start with the challenges that people face every day. Understanding daily “jobs” is the first place I look for opportunities where AI can make a difference.”

5. AI should be blended smoothly in your product

Apps like Google maps, Amazon, Netflix which are used by a lot of people on a regular basis have mastered the incorporation of artificial intelligence with such beauty that the customers do not even realize it.

Raj Singh, co-founder & CEO at Tempo.ai, also has quoted, “The best apps leveraging AI do it in a way such that tech isn’t in your face but blended into the experience.”

Many experts believe that AI should be designed such that it should not show the algorithm or its engineering. The customer is just interested in the result. Also, the product will only be appreciated for its ease of use and not the complexity.

6. Adopt a human-centred approach

The complexity during the development of the app should not reflect on the final outcome of the of the product. The user has nothing to do with how difficult it was to build a product. They will only look at the convenience which your app offers in solving their problem.

Gianluca Maruzzella, co-founder & CEO at Indigo AI explains his working as: “We at Indigo AI strongly believe that AI-powered chat-bots will change customer experiences forever, delivering wow moments that were not quite possible before. But this change — enabled by AI — will be possible only if we will design adopting a human-centred approach.”

It is also important that not just the development but the designing part of the product is dealt with utmost care. This is so because the user will use your app only once. And if they do not find it easy to navigate and use, there are high chances that they will uninstall it and never use it again. So, encash the first chance itself to rope in your users, by giving them the best design and navigation experience.

7. Do not overlook user experience

Though one should not over do the designing part so much that you fit in all the features in the same page or same app. But it is necessary to keep in mind the feel and comfort your which app is giving to your customer. For a product to succeed, it is must to provide with top-notch user experience.

8. Do not make an app for the tasks which are already easy enough to do

Sometimes, while developing a product or conceiving an idea we tend to move towards a concept where we feel it’s easy to develop. But real struggle is to figure out that exact direction which will give the hint of the real idea worth working upon.

Users look for the solution to the problem which they are not able to solve by themselves. Making an app which solves the easy problem will not excite or attract the users. They want something solid to stick to.

Manuel Ebert, Founding Partner at summer.ai says, “The real power of AI is augmenting and enabling humans, like an intellectual steam shovel. A great AI app will not just help users do something faster, but enable them to do something they couldn’t do before.”

8. Do not get distracted by early traction

While developing an AI product, It’s easy to get distracted, especially if you have some early customers or potential partners demanding for the similar features. But, make sure your product survives and succeeds in the long run as well. You may get a good traction initially through free and paid promotions, mouth publicity or through your already existing users. But if your product doesn’t fulfil the expected result, after a short while you may lose all the traffic.

9. The best AI app should empower its users

The user should feel in control of the app. The main motive of the app should be to reduce human effort and work on its own, intelligently. The success of any tech product lies in empowering its users. You need to make sure to implement some intelligent calculation in such a way that user would have to do a very minimal work as possible.

It is also necessary that an app should communicate with its user using natural language. More the user would be able to connect with it, more regularly they will tend to use it.

As Dennis R. Mortensen, CEO and founder at x.ai says, “The best AI products make the user more capable. And the very best AI completes a task start to finish for the user; the user should have to do as little work as possible to make it happen. These are truly autonomous intelligent agents.”

10. Make your customer is your ultimate focus

You need to understand how the user and app are going to interact with each other. Make that interaction worthwhile and smooth. Also, may it be any kind of entrepreneurship, customer should be the first and the foremost priority. The communication between your AI and user should be strong enough to make them believe in it. Since AI is comparatively new to use, the reliability and authenticity of the product is always in question. So, it becomes essential to deliver something which is designed by focusing customers and their needs.

Trevor Jackins, marketing specialist at NeoSpeech stated, “You can have the smartest, most brilliant AI app in the world, but if it’s unable to effectively communicate information to the user or the user has trouble interacting with the app, then it is worthless.”

11. Create a wow moment in your product for your customers

The user should at once fall in love with the simplicity of the product. The ease of use should come naturally. A user would not want to spend time in understanding the complications in the app. If they do not connect with the app, they will definitely not use it.

If your app in anyway is similar to other products then you need to have an edge over all of them, so that the user would prefer you over other apps.

Nathan Benaich, Investor in tech companies Playfair Capital says, “A truly great application powered by AI will deliver that wow moment, the magical feeling of accomplishing something that wasn’t quite possible before, right out of the box. For example, SwiftKey, which predicts the words you’ll type next.”

12. Do not underestimate the power of regressive testing

However awesome your product may be, but you cannot leave a scope for bugs and errors. It is of the utmost necessity that you put your product to test repeatedly - over and over again. Because once you launch it in the market then it gets exposed to all your current and targeted audiences.

If it is not possible to launch all the features in one go, then you can always launch the most important and the attractive one first, to rope your customers, and then with the passage of time you can update the other features. Do not mess up the product by including all features at once and making it live without proper testing.

Mark Stephen Meadows, founder at Botanic.io, in his expert roundup has very clearly illustrated his thought process while developing an AI app. “Iterative builds are a must here and expect that your bot is something you continually improve, refine, expand, and improve. Learn from your mistakes. Improve your libraries, tighten integration, float responses higher up the flow so that people know what they can do when. All those decisions come from testing.”