Why you should integrate AI into your dev processes sooner rather than later

As artificial intelligence moves in to transform industries as diverse as banking and art, leaders of companies in every field must ask themselves: how can AI potentially improve my team? In software development, the potential applications of AI are so significant that they are poised to usher in a massive transformation in how dev teams work, saving developers time, reducing errors, and improving decision-making. Integrating AI is not a matter of if, but when. And there’s no better time than the present.

Software development’s human problem

There is no getting around it: Human beings are fallible. In the world of coding and software development, the human capacity for error is the reason behind things like code review, quality assurance, testing, and, of course, lots of bugs. In short, a lot of manpower goes into trying to anticipate, correct, and manage the human error factor.

But what if you could avoid it in the first place? 

Indeed, artificial intelligence is a tool that has been and will continue to be used to help augment what humans can do, reducing errors, improving efficiency, and boosting speed. With its powerfully transformative nature, embracing AI for coding is absolutely essential.

Benefits of AI for developers

AI has the potential to offer a variety of significant benefits to developer teams, including:

• Increasing scale and speed – By automating a number of processes, AI can help increase deployment frequency while decreasing lead time for changes and time to restore.
• Error management – Not only can AI be used to find existing errors, but it can also proactively predict future errors and even correct them.
• Freeing up developers’ time for more important tasks – In handing over certain repetitive tasks to AI, developers are able to concentrate on more complex and challenging problems.
• Making strategic decisions – Humans can spend forever debating different products and features, but AI trained to make decisions based on data analytics can help make smarter choices with much less debate, eliminating human bias in the process.

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Types of AI worth knowing about

AI has an infinite number of potential applications. These are the ones forecasted to most disrupt the way development is done in the next few years. 

Code completion

Similarly to how Google can predict the search you’re going to make based on your first few keywords, code completion tools can finish lines and entire functions of code as developers are writing them. With tools like Tabnine, developers can accept a prediction or keep typing to get more alternatives adapted to the code context. As you can imagine, this can save a tremendous amount of time, skyrocketing developers’ efficiency. 

Personal assistants

AI code assistants are quickly increasing in popularity, with features that can assist a developer in non-coding tasks such as managing pull requests. By helping to automate and optimize the more boring and repetitive coding-related tasks that developers are required to do (such as debugging and testing), these tools save significant time for developers, allowing them to maintain focus on the technical side of their job rather than the task management minutiae. 

AI art engines

AI art engines, such as DALL·E 2 and Midjourney, are revolutionizing the way that graphics and art are created, allowing users to create images with natural language prompts. By breaking down the barriers to creating art, these AI art engines are ushering in a new era for visual creativity.

Potential concerns about implementing AI

Just because software development is a technical field doesn’t mean that the industry is having an easier time accepting the coming AI revolution than others. Indeed, there are still many concerns regarding the implementation of AI for developer teams. 

Replacing people

One of the greatest fears surrounding AI in all industries is the fear that it is going to replace human employees. But AI tools aren’t created to compete with human programmers; they’re created to help them and enhance their abilities. Because while training AI to completely replace humans isn’t necessarily impossible, it is highly impractical, and not on the horizon anytime soon.

Reducing creativity

Another common concern regarding AI automation is the fear that machines simply aren’t capable of producing the same level of creativity and innovation that human programmers can offer. But AI tools aren’t trying to do so. Instead, they work to free up programmers’ time and resources so that they can focus even more on the complex, creative work at which they are best.

Code permissiveness

The code that AI algorithms were trained on was written by somebody. Responsible AI algorithm development requires taking care to ensure that all code used has been appropriately licensed. In fact, some code completion platforms may be facing potential lawsuits for possibly infringing on the licensing agreements of certain software. Others, like Tabnine’s AI models, are only trained on repositories with permissive open-source licenses. In addition, Tabnine’s models are never trained on their users’ code. 

AI isn’t the future – it’s the present

AI is well on its way to becoming a central part of the development workflow that we can no longer imagine living without. It isn’t supplemental; it’s essential, and it is only going to become more necessary with time. In order to set your development team up for success, make their jobs more efficient and effective, and attract and retain top developer talent, you must embrace and integrate AI into your workflows. Not later – now.

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