AI application is a hot topic of discussion. These days artificial intelligence-based applications are booming. People are frequently using apps like Siri, ELSA, Cortana that can provide ease and, most importantly, save time. Considering humans’ needs, mobile app development companies focus on developing more such applications that satisfy their clients’ needs.
Admitting so much hype surrounds AI apps, let’s see – how to develop an AI application? Or what are the necessary steps for creating a successful AI application? What is an AI application development platform? What is the future of AI? Today, we will discuss these common questions that are catching the eyes of various people. But before switching to answer these questions, I want to take you to the statistics of AI apps:
- The AI technology market is going to rise fast in the coming years. It will reach 126 billion $ by 2025.
Source: Statista
2. The AI deployment in different sectors is tremendously increasing from 25% to 37% between the 2018-2020 years (Gartner Survey).
3. IDC anticipates 75 percent of business plan apps will use AI by 2021 (Source- em360tech).
Highlights of Contents
7 Step For AI-Driven Application Development- Implement To Have Successful Application
Step 1. A Successful AI App Starts With Great Ideas
For starting an app, you don’t need to climb a long tree; you simply need good and unique ideas. After having an idea in your mind, sketch it down on plain paper. This will help you in getting a realistic visual of your app.
While designing the sketch for your AI apps, be clear with some of the points like:
- What features will it have?
- Who will your targeted audience- will it be kids or adults?
- How will your app perform?
These are the simple assignments you can make easily. You won’t need any special tools to sketch your ideas. Only two simple tools are enough, i.e., pen and paper. Use these tools for sketching. After sketching, keep those papers safely because that is what your app will get launched in the future.
Step 2: Perform Business Analysis Concerning AI Technology
Secondly, go for the business analysis of AI Technology. Why so?
Let me explain.
When you’re performing this step, you get insight into:
- What’s new in AI?
- How is it influencing the IT sectors?
- Whether you have selected the right technology for your next project?
- What features or functionality of AI can enhance your project?
- Is integrating AI in a project can engage the audience?
- What are the core requirements and objectives of the business?
- What makes AI necessary for this project?
- How will AI help meet those needs?
- What is needed to succeed and avoid failure?
Not only these, but analytics will also help you in finding customer behavior towards AI technology. These collective data will help you in creating the perfect application.
Most of the web application development companies are hiring business specialists who can help in gathering such information. Although we have seen what business analysis is essential?
So, hire business specialists who can help you gather this information in a more accessible way—the gathering of information aids in enhancing customer satisfaction.
How?
Because Artificial Intelligence helps to determine customer behavior and allows companies to drive insights to improve users’ engagement in the app, it enables users to find exact information in the mobile app and enhance satisfaction.
You should focus on all questions quoted in the above paragraphs. This way, you are near to meet the objectives and needs of your AI projects. Follow this second step to evaluate the current situation of your business and understand the cognitive requirement.
Once you are done with business analysis, your next step is to assume how to use AI to meet the objective or goal.
Step 3: Do the data Analysis of an AI application that is already present in the market.
This stage is all about acquiring information about the different AI-based applications already present in the market.
Carry this step to know:
- What features satisfy which requirements of customers?
- What is the standard of present applications?
Analysis of present data is vital to understand the uses of AI applications that are already out there. Once you know what the people mostly like features, you can try adding them to your projects. However, don’t just try to add it because it is popular, firstly see whether those features are needed for your projects.
One of the interesting AI applications that are famous among people is Amazon’s Echo. This application is a case of how Artificial Intelligence implements an interpretation of human language into engaging activities.
This gadget performs after acknowledging our words and plays out a broad scope of assignments on your order. It can accomplish something beyond just playing music for you. You can even use these gadgets to control other devices or gadgets at your home. Use it for booking taxis, ask the Echo to call your friend, place an order to your favorite restaurant, check the climate conditions, etc.
Similarly, you have to discover what features you want to include in your project. Accessing such programs’ data helps you meet the business goals set up during the AI-centered business analysis.
The AI data analysis is also essential because it will guide how to use it in your AI project. So, before you begin employing this information for AI-driven application development, set up a couple of research on it.
- When you’re playing out this research, you will know whether you have the quality information.
- Whether the information is sufficient for application development with AI.or, you need to research it more.
This way, you find out what quality control measure that will assist you in your project. Even it will help in taking a discussion if to continue with the project or to discontinue it.
Step 4. Now you’re ready to implement AI in application development.
After having the business analysis and data analysis of AI technology, you can start preparing your project.
Just extend your preparation as per the information you acquire in the above stages. Put your planning accordingly to the necessities of your project. Figure out all your key components and put them as a whole.
Make sure your AI project must have the option to address the necessities of the business. In this manner, the information should be arranged, cleaned, and marked; however, it should be appropriately designed and well planned.
More significantly, if your designs are compelling and precise, you can accomplish a great business result. So keep on upgrading your information regarding AI technology to make your application design more attractive.
When you’re underlying this technology gives more emphasis on the designing part. This will set up a base for your progress of the project in the future.
Whenever you plan to launch an application, you should be with the first and most important thing, i.e., customers’ expectations. If you are clear with it, you get a chance to center around what is most important?
If there are sufficient elements to continue with AI usage. It is necessary to pick the correct AI design, which will drive the execution innovation stack, approach, and AI model determination.
Step 5: Machine Learning Data Model Development
This stage hopes to build up the significant cycles that help make the ML information model for your AI-based project.
The vital components of this stage are:
- Selecting the algorithm for the project.
- The theories and hypothesis for the project.
- Test design creation.
- Development lifecycle.
- Distribution of tasks for the development of the model.
Some significant contemplations for ML information model improvement include:
- The way to deal with and use of techniques.
- Enhancement of hyperparameter or model tuning
- The methodology for preparing and scaling model
- The methodology for a re-preparing model
- The expansion of a pre-prepared model
- Managed, solo, and fortification methodologies recognizable proof.
Concentrating on every point will permit you to make a suitable ML information model for your AI-based application.
Step 6. Employ AI Model Testing
As the name proposes, this stage includes the testing of the AI model that has been created. In AI model testing, the primary thing to know is if the learning happens for the prepared model. An apparatus that can be utilized for the conclusion is expectations to absorb information.
When testing results are accessible, the model ought to be explored for exactness and execution to coordinate the business KPIs. If the model doesn’t meet the measures, it needs to experience another cycle to accomplish an improved result.
At last, this stage will deliver an ML/AI model that is prepared for operationalization.
Also Read: How AI & Machine Learning Impacting Our Lives: 5 Best Examples
Step 7. Selection of Appropriate Deployment Platform.
Once you are done with the testing phase, continue your mobile application or web application development process. Integrate the ML model to the different components of the application to make it reliable and flexible.
After developing the app, your next stage is to select an appropriate platform for its deployment.
Make sure your platform is well verified and configured. The application should be appropriately integrated with other sets of applications. The last stage of the development is deploying the application in the right place and monitoring the plan.
Conclusion
We have outlined the processes for the AI application development in 7 steps. Implement all these steps to get success in your AI projects. These steps will help you in resolving the issues that you might face during your project.
Not only that, it will keep you far away from any type of misleads and failures. These steps are already tested on various projects. It proves the successful delivery for its clients of different sizes and industries.
The market of AI technology shows a ton of opportunity for startups, SMEs out there. Although, this technology is in its beginning stages. Considering all things, creating an AI app quickly and soon, it is an enormous chance that AI could proceed to do complex functions. So, accelerate your AI application development cycle as per the above instructions and make it more robust against mishaps.
Frequently Asked Questions (FAQs)
Q1: In which industries AI application development is worth making?
Ans- AI-based application development is ruling almost all industries like:
- AI in Healthcare
- AI in Finance
- AI in Education
- AI in the Automotive Industry.
- AI in Data Security.
Q2: How do I develop an AI application?
Ans– Developing an AI application is not as challenging as launching a rocket. However, there are a few steps you need to follow:
- Recognize the problem.
- Arrange the data.
- Pick the algorithms.
- Equip the algorithms.
- Pick a remarkable programming language.
- Operate on a selected platform
- Monitor the progress of the plan
Q3: How is artificial intelligence implemented in mobile app development?
Ans: Try to integrate algorithms that can efficiently study patterns of human behavior. Implementing this process will help you in developing AI-based applications.
