Since the dawn of modern artificial intelligence, AI has slowly crept into almost every industry. From supply chain management to accounting, it has streamlined numerous processes and automated countless tasks. One major industry AI has also infiltrated is software development.
As AI has spread into software development, it has brought with it many new opportunities and challenges that developers must navigate. Below, we will examine the benefits and drawbacks of how AI is reshaping the coding landscape and redefining the craft of programming.
Coding Enhancements
Many of the changes that AI is bringing to the coding landscape are positive. They are enabling developers to code more quickly, reduce development cycle times, and produce more innovative technologies.
Entry to Coding
Among the most significant positive changes ushered in is the reduction in technical ability required to code. Because AI can, for the most part, do the primary coding for you, many people with little to no experience in coding have entered the market and have begun to learn coding with AI assistance.
While this comes with challenges, such as some software now being entirely developed by AI with little input from a human other than prompts, it has made the industry more accessible to those wanting to become developers.
Automation
Another incredible tool that AI has brought to programming is its ability to automate. From simple checks and script tests to more advanced regular procedures, AI can automatically do routine tasks in the background.
With these tasks handled by AI, developers are free to focus on more essential tasks or on further brainstorming for their software. For full-stack developers who run both front and back-end development, the time gained through using AI can be particularly beneficial.
Debugging
Debugging code is one of the primary tasks that AI can automate to save developers hours. With its ability to analyze millions of lines of code quickly, AI can find errors in code and suggest solutions in a fraction of the time it would take even a skilled developer.
Beyond simply finding material errors during the debugging process, AI can also provide suggestions to tidy up the code and make it more streamlined and functional. In some cases, it can also be used to “self-heal,” which allows applications and code to adapt based on input or failures.
Accelerated Prototyping
Because AI can quickly write extensive code based on a relatively simple natural language input, developers using AI to write boilerplate code or even more customized programs are able to generate working prototypes more quickly and efficiently.
This allows programs and new ideas to be tested more quickly and allows the viability of projects to be determined. Faster prototypes also lead to faster development cycles, with software being launch-ready more quickly.
AIDD and Implementation
Beyond using AI as a tool, AI-Driven Development is gaining traction in the industry, with the continuous dialogue between AI coding bots and developers resulting in complete applications. In many cases, the development and implementation of new code are both handled by AI through instruction in natural language by developers.
Growing Low-Code
The final advantage of AI in coding is the new generation of applications developed by AI that use low-code or no-code logic. These apps, which have minimal hard-coding, instead use custom components and logic to function.
More advanced apps are also being generated with low-code by using advanced logic functions in the backend paired with automated workflows that guide the app’s processes. This is leading to smaller, more streamlined apps that can run on both thin clients and high-performance computers.
AI-Driven Challenges
Despite the many benefits that AI has brought to coding, the enhanced coding opportunities have also introduced unique challenges that need to be carefully navigated to protect developers and the industry as a whole.
Loss of Creative and Critical Thinking
Chief among these challenges is the loss of creative and critical thinking on behalf of developers. As coders rely more on AI to handle debugging and even brainstorming, there is a concern that those responsible for coding the next generation of software may become over-reliant on AI.
This will occur if developers begin relying on AI to devise creative functions and features of their apps and then rely on the same AI to implement and overcome challenges related to them. When doing this, developers may avoid handling any of the code themselves.
Should this occur, software and applications may all begin to show the same underlying code as they will all come from the same or similar sources. In addition, this could lead to a future “black box,” a problem where a developer does not understand the code that AI has generated and, therefore, can offer little to no support for an app or program they have released.
Vulnerable or Incorrect Code
Aside from developer skill degradation, another major concern is the vulnerability and accuracy of code developed by AI. While artificial intelligence may know all the best security practices, it may not know how best to implement them. As such, AI-generated code may be prone to security vulnerabilities and weaknesses.
Incorrect code may also be a side effect of over-reliance on AI. Despite knowing how to code, AI can sometimes lack the attentiveness and logic of a human coder, leading to errors in its code that would otherwise be absent. This incorrect code could hinder the effectiveness of a program and cause more problems when trying to debug it.
The Spread of AI
The advantages (and challenges) of AI have not stopped its spread into new and existing software developments. This spread has not only entered the tools developers use, but also the front-end platforms consumers use.
Developer Back-End
Behind the scenes, AI is being implemented as a tool alongside traditional programming utilities, including major developer programs like Microsoft Visual Studio and even on platforms like GitHub.
Consumer Front-End
On the front-end side, AI is helping personalize information and services. Whether it’s on streaming services such as Netflix, where it is used to recommend shows based on viewing history, or on gambling platforms that offer slots in Canada, which use AI to recommend the best places to find online entertainment, AI is helping us find what we want more efficiently and accurately.
Conclusion
With continuous advancement in how AI can handle complex tasks and generate code, there appears to be no slowing of its spread deeper into software development. However, using it to take advantage of its superior benefits should be weighed carefully against the challenges it brings, and over-reliance on AI should be avoided.