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How Artificial Intelligence transforms Application Development in 2019
Artificial Intelligence (AI) has defined a new paradigm of application development. In a world of great customer experience, technologies like Artificial Intelligence, Machine Learning (ML), Deep Learning, etc, are seen to be the frontiers driving innovation and customer satisfaction. The self-learning capability of AI applications has made it an all-time favorite among its users worldwide.
So, how strongly does AI benefit and spearhead application development in 2019?
5 Ways AI transforms Application Development
1. Accurate Project Estimates & Plans
Application development is a game of expertise and experience. App development projects can often go overboard monetarily in the absence of proper planning and estimation. It is here AI becomes a savior as the technology uses its previously gathered insights to present precise estimates for each application development project. Based on previous user stories, feature developments, change requests, etc, AI uses evidence to power its intelligence. The cost and time estimates suggested would be significantly more accurate than manual figures.
2. Smart Programming Assistants
Any new application development project needs time and effort. Reading the documentation and fixing bugs are two unavoidable yet mandatory actions in application development processes. Developers lose a good portion of their allotted time in such reading and trial and error activities. Intelligent programming assistants speed up development processes by coming up with recommendations and code examples or preventing common code mistakes. An example is Kite that uses ML to provide useful code completions for Python.
3. Rapid Prototype Development
Converting business solutions into robust technology solutions require months of planning and effort. Once the project kickstarts, there will be various moments of trial and errors that consume a good deal of time. AI shortens the whole process by automating common code lines and reducing repeated code lines. The predefined libraries of AI and Deep Learning act as the elixirs to rapid prototype development.
4. Improved Data Security
The amount of data exchange in an application is continuous and unlimited. There will be personal or other types of confidential data being transferred in the network that needs to be monitored and safeguarded. Any threat to cybersecurity can be proven disastrous for the users involved. In some cases, there might be delays in notifying any data breaches. With AI in implementation, data security monitory becomes easier and faster. There won’t be any unnoticed suspicious activities happening in the network.
5. Automated Testing and Debugging
Once an application has been developed, testing is the next crucial step in the process. As said earlier, the project teams lose a major portion of their time identifying the bugs and fixing them. AI can easily help both the testing and development teams in creating possible test case scenarios based on the previous data. It can also predict the outcome of testing without actually running the tests and prioritize bugs based on the criticality of the issues.
Business intelligence applications powered using AI and Machine Learning (ML) are widely in demand all over the globe. In other words, we have seen people quoting that AI has given traditional software a boost. It has helped to eliminate the technical barriers in understanding users.
Earlier, there was a notion of AI being expensive and hence, not quite affordable to the small and medium-sized businesses. But, we have come a long way after that. Today, AI can be incorporated into any business process irrespective of their budget and business size. If you have a good technology solutions partner experienced in application development, your business can undoubtedly reap the benefits out of AI and ML without leaving a hole in your pocket.