Do you want to know how to integrate AI into an app? You need to take the following steps:
1. Assemble an expert team to plan the project to integrate artificial intelligence into your web and mobile apps
Web or mobile app development with the requirement of integrating AI can be hard. Enhancing existing apps by adding AI modules can be complex too. You need to plan well to succeed.
Form an experienced team to plan the project. An experienced project manager (PM) should lead this team. This team needs a software architect and business analyst (BA).
The PM should plan the project. You need a PM with a thorough knowledge of the following:
- Project management frameworks;
- Important project management methodologies;
- PM tools;
- Project management best practices.
2. Review examples of AI-powered mobile apps and web apps
You might think of Uber or Google Maps when looking for examples of apps using AI. These aren’t the only ones though. Many other apps use AI to great effect.
The following are examples of AI-powered mobile apps:
- Google Assistant;
- Amazon Alexa;
- Swiftkey Keyboard;
- Data Bot;
- Siftr Magic.
You can check out the following web apps using AI systems successfully:
- Interior AI;
- DALL-E 2;
- Murf AI;
- Adobe Podcast’s Enhance Speech.
Analyze how these AI apps utilize AI and machine learning. Several popular AI apps also use speech recognition technology, image recognition technology, deep learning, etc.
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3. Assess how integrating AI and machine learning (ML) can help your app users
In a highly machine-driven world, integrating artificial intelligence including machine learning, natural language processing, etc. can help users. No wonder the global artificial intelligence market is growing rapidly!
How do you want to use artificial intelligence in your app? AI can do much, e.g.:
- Analyze user behavior to provide personalized recommendations;
- Responding to user requests and customer support tickets with the help of AI chatbots;
- Assess behavior patterns of users to detect potentially fraudulent transactions;
- Improve user engagement by providing virtual assistants powered by AI to users;
- Use AI algorithms for data analysis to assist data scientists;
- Analyze human speech, voice notes, images, videos, biometric data, etc. to derive insights required for national security;
- Enhance app analytics with the help of important AI capabilities like deep machine learning and advanced analytical mechanisms;
- Identify central objects among different visual objects using image recognition technology;
- Build advanced backup software using AI and machine learning models;
- Identify human speech for law enforcement and criminal investigations.
The above isn’t an exhaustive list, but you get the idea. Choose a suitable use case for AI.
4. Finalize business requirements for integrating AI into your app
Your team should now finalize the project requirements. The BA should interview business stakeholders and gather requirements. After analyzing the requirements, the BA should document them.
The architect should define the NFRs like performance, scalability, etc. You need a thorough requirements review and management process for this project. The PM should implement such a process.
The project should define the scope. We assume you will integrate AI into your web and mobile apps.
5. Select the right approach for implementing AI in your app
Firstly, use one of the famous AI-based platforms for integrating AI into your apps. Top AI development platforms like Microsoft Azure AI Platform, Google Cloud AI Platform, and BigML have considerable cloud capabilities.
You can focus on software development instead of IT infrastructure management if you use one of these platforms. Data storage, data management, and data integration are key factors when developing an AI solution.
You also need considerable computing resources while building AI solutions. AI development platforms can help significantly. Hire app developers with AI and machine learning experience and familiarity with these platforms.
Secondly, you should design a robust solution for the app’s security. Plan to use security tools and solutions like multi-factor authentication (MFA), encryption, etc.
Finally, plan to develop APIs (Application Programming Interfaces) for the proposed AI-powered features or services. You can then scale your app development processes seamlessly.
6. Select a technology stack
You are integrating AI into digital solutions that serve existing users. Obviously, you should continue with the current tech stack for your mobile and web apps.
We recommend you use Python for developing the proposed AI modules. This open-source programming language has excellent libraries.
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You can use these libraries to implement key AI capabilities like deep machine learning processes. Python makes it easy to implement several other important AI capabilities, e.g.:
- Machine learning (ML);
- Image recognition;
- Speech-to-text and text-to-speech;
- Neural networks;
- Natural language processing (NLP).
Typical developers in an AI development company will often think of using Python in AI and machine learning projects.
You need to choose the right database solutions. Consider using MySQL or PostgreSQL, both of which are popular open-source SQL databases.
Do you need to use a NoSQL database? Use MongoDB or Apache Cassandra. Both of them are highly popular open-source NoSQL databases.
We recommend you use the REST (Representational State Transfer) standard for API development. You can easily find developers that know how to develop RESTful APIs.
7. Plan the project to integrate AI into your app
The project planning activities should cover all the key aspects, e.g.:
- The technical environment of the project;
- Plans to use suitable software development methodologies like agile;
- Task planning;
- Identifying dependencies between tasks;
- Scheduling the project, identifying milestones, and planning iterations;
- Managing risks and issues;
- Estimation, budgeting, and cost management;
- Quality management;
- Human resource management;
- Communications management.
8. Hire a software development team
Hire capable people for the following roles:
- AI developers with Python skills;
- UI (user interface) designers;
- Web developers;
- Mobile developers;
- DevOps engineers.
You need to take the following steps:
A. Select an appropriate hiring platform
Should you hire freelancers for this project? We don’t recommend this approach. Integrating AI into an app can be a complex project. Developers need to keep various aspects in mind, e.g., machine memory, preparing training sample data, data modeling, etc.
Freelancers work part-time on a project. You might not get the required bandwidth from them. Managing freelancers can be hard, and freelance platforms don’t offer any project management support. You need to find replacement developers if freelancers leave your project mid-way.
We recommend you hire programmers from trustworthy AI, web, and mobile app development companies like DevTeam.Space. Our developers work full-time on your project. They have relevant expertise. Our developers are experienced, and we train them in our AI-powered agile processes.
We offer project management support. You need a reputed partner like us for a complex project.
B. Interview candidates
Having chosen a hiring platform, you have posted your job ad. You now need to interview the applicants. Use our interview questions, e.g.:
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Evaluate the relevant experience of developers by asking questions about their past projects, and avoid asking only theoretical questions. You can explain your project requirements. Ask candidates how they would approach this project.
C. Onboard the new team members
The PM needs to ensure an effective onboarding of new developers. The architect needs to explain the project requirements and technical solutions. You should share the relevant documents with the new team members.
The PM should grant the required access. New team members should be introduced to your existing team. The PM should discuss the roles and responsibilities.
Subsequently, the architect should explain the work approval project. The PM should describe the project schedule and set up a communication process.
9. Code, test, and deploy the enhanced apps
The software development team should do the following:
- Design the changes required in the user interface (UI) of the web and mobile apps.
- Gather vast data sets including training sample data.
- Prepare data for use in the AI/ML development project.
- Implement the information security solution formulated earlier.
- Implement the relevant AI and ML algorithms.
- Develop the relevant AI modules.
- Test the new AI system.
- Deploy the new AI system and train it.
- Develop APIs as needed.
- Integrate the AI modules into your web and mobile apps.
The architect needs to guide the team, whereas, the PM should manage the project.
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Integrating artificial intelligence into web and mobile apps can take a lot of effort. When you integrate AI into an app, you work with cutting-edge technologies like speech recognition, audio or video recognition, etc. You should hire competent developers for Incorporating AI into applications. Needless to say, your team also needs web and mobile application developers.
DevTeam.Space can offer the web, mobile, and AI app developers that you need. We train our skilled, motivated, and experienced developers in our AI-powered agile process.
Do you want to know how DevTeam.Space can help you to implement AI in your apps? Fill out the DevTeam.Space product specification form and a dedicated account manager will reach out to you.
DevTeam.Space developers have extensive experience in developing AI-powered web and mobile applications. Our developers have the relevant expertise. They are motivated, furthermore, they are trained in our world-class development processes.
DevTeam.Space programmers have good knowledge of popular AI use cases as well as emerging ones. E.g., our developers know about AI-based automated reasoning, AI-powered dynamic call scripts, and AI-powered streaming services. They have considerable AI app development expertise.
DevTeam.Space can provide much more than just developers experienced in AI technology. Our focus on quality management ensures that you get supportable and maintainable code. You also get complementary support from a dedicated tech account manager when hiring our AI developers.