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AI-assisted software development: How AI adoption can benefit development teams

Learn the benefits of AI-assisted software development and how your team can embrace AI adoption to make the most out of these tools.

Feb 23, 2024 • 10 Minute Read

Image of a robot coding to illustrate AI assisted software development
  • Software Development
  • Developer Experience
  • Software Delivery Process
  • Team Development

It’s no secret that AI is on the rise, with 81% of executives saying they’ve already adopted or plan to adopt AI tools and technologies within their organizations. But as AI becomes more prominent in the workplace, many developers worry that the skills they’ve developed to become successful in their roles will soon become obsolete.

At Pluralsight, we call this AI skill threat. The truth is that AI needs human intelligence; it can’t work alone. AI won’t replace developers but can be an invaluable tool to help increase their performance, productivity, and quality of work. 

So how do we work on decreasing AI skill threat so developers and leaders can have confidence in AI-assisted software development? 

Below, we’ll give a rundown of the power of AI in software development, how it can benefit teams, and how Pluralsight Flow can give your team confidence when adopting AI.

What is AI-assisted software development?

If you’re reading this, you likely already know what AI is and how it can benefit organizations. In a nutshell, this technology is used to streamline processes across various industries by executing and automating repetitive tasks, eliminating the burden of repeating the same stuff over and over. 

When it comes to AI-assisted software development, teams can integrate AI into their processes to improve productivity, efficiency, and the overall quality of their software products. AI uses natural language processing and machine learning algorithms to recognize code patterns and suggest improvements to streamline different stages of the development process. 

As the name suggests, AI-assisted software development is meant to assist developers, not take their jobs. Think of AI as a developer's trusty sidekick—someone who understands programming and can offer suggestions on how to improve the process and product. 

As Pluralsight’s CEO Aaron Skonnard explains it:

Benefits of using AI for software development

With the above in mind, AI can be that sidekick development teams need. Here are just a few of the many benefits of utilizing AI in software development

  • Increases productivity: Automating repetitive tasks can expedite project timelines and increase productivity, giving developers time to focus on projects that require human problem-solving, critical thinking, and creativity skills. 
  • Improves accuracy: AI code generation tools can detect flaws and bugs in coding that may get overlooked, leading to improved accuracy and decreased human error. 
  • Promotes collaboration: AI-driven tools can help explain complex code and offer valuable suggestions to development teams. In turn, this knowledge can facilitate better communication and encourage collaboration among teams.
  • Boosts accessibility: AI-assisted software development can also make developer roles more accessible to those with little to no coding skills and provide clear coding documentation that’s easy for non-technical stakeholders to understand.

How to use AI for software development: 5 use cases

As we mentioned, AI won't replace developers but instead acts as a tool to streamline different aspects of the software development lifecycle. Let’s dive into some key ways organizations can use AI technology to streamline the development process. 

1. Code generation

AI has become increasingly better at automated code writing and uses AI algorithms and machine learning to generate or modify code based on certain parameters. 

Using prompt engineering, developers input a prompt, and AI code tools can reference their database of programming language and code patterns to output lines of code. This automation helps developers become more efficient, expedites project lifecycles, and gives developers more time to focus on complex work.

2. Bug detection

As we mentioned earlier, AI is like a developer's trusty sidekick, and having that second pair of eyes can help spot potential errors or vulnerabilities in code at a way faster rate than humans. AI can use past data to identify commonalities in code errors, make suggestions on how to improve the code and help developers prioritize bugs based on their severity and impact.  

Automating code review and detecting these mistakes early on in the project lifecycle ultimately helps reduce timeline bottlenecks and decrease the number of issues for end users. As these AI tools receive more data, they continue to learn and adapt to coding practices, leading to fewer errors in future projects.

3. Code analysis

In addition to detecting bugs, AI can also provide valuable suggestions on how to improve the quality of the code. A new or complex codebase can sometimes be difficult for developers to understand. Using machine learning and natural language processing, AI can break down suggestions on the code’s functionality in a way that’s easy to digest. These insights help developers improve their coding skills and complete tasks more efficiently. 

4. Testing and quality assurance

AI can also automate code testing, which 54% of developers say they currently utilize in their development process. Testing and quality assurance are crucial to ensure development teams deliver quality products to customers, and AI can help uncover test scenarios your team may not have thought of before. 

With the help of AI, development teams can see how their product performs in different conditions to ensure it runs smoothly—even in tricky scenarios. This type of automation can predict software flaws early on so developers can quickly resolve issues to improve the quality of the software and ultimately help prevent future technical debt.

5. Advanced planning

AI plays a valuable role in code generation, bug detection, code review, and code testing, helping teams improve efficiency and speed up delivery times without sacrificing quality. 

Making all of these improvements within the development process and utilizing a product like Flow can give you a higher-level view of your organization. Flow gives you a glimpse into how AI is being utilized to make IT planning and resource allocation more predictable over the long term.

How Pluralsight Flow can help your team gain AI confidence

After you’ve integrated AI technology into your development process, how can you ensure it’s actually helping your team? That’s where Flow comes in. Flow is designed to provide actionable insights into your team's work and can help gauge the impact of AI in your organization. 

Our research has found that although organizations are implementing AI technologies into their workflows, most leaders are unaware of their team's AI skills and don’t have a proper upskilling strategy. 

Here are just a few of the ways Flow can help your organization bridge the AI skill gap and effectively leverage AI technology:  

  • Identify the effectiveness of AI: You can use Flow to test how AI is used within your team and your problem domain, allowing you to get a glimpse into the tool’s effectiveness. In what areas are developers using automation the most, and in what areas of the lifecycle are they reluctant to use the tools? By visualizing the effectiveness of AI tools, leaders can use the data to analyze and improve the development process, leading to more efficient workflows for their teams. 

  • Assess cycle time: Flow gives you visibility into cycle times, allowing you to see how much time your team spends on certain tasks, where they’re experiencing bottlenecks, and areas where automation can help improve processes. This data can help cut cycle times so your team can deliver confidently, ultimately improving team health, productivity, and employee retention. 

  • Analyze deployment frequency: Get a glimpse into how testing automation impacts your team's deployment frequency and leverage the change failure rate to identify areas where more automation testing is needed. This will ensure your team is delivering high-quality, reliable products at a faster rate. 

  • Identify training and upskilling opportunities: Because AI can pinpoint bottlenecks in the development process, it's often easier to measure areas where your team needs additional AI training and upskilling. By upskilling your current talent, you can show your team you’re invested in their growth, mitigate job security worries, and generate a long-term AI strategy that generates a positive ROI.   
  • Mitigate AI skill threat: With the help of our Generative AI Adoption Toolkit, you can assess the current landscape of your organization’s AI use and utilize the resources to guide you through AI implementation so your team feels confident using AI-assisted development tools. In turn, this will help your team become more resilient as they shift towards using AI-assisted software development

Embracing the future of AI-assisted software development

AI technology continues to evolve, making it essential for teams to prioritize learning strategies to harness the power of AI. 

While you can use Flow to measure how AI adoption impacts your team, if you feel your team needs additional training to bridge the AI skill gap, Pluralsight Skills can help. Whether you’re looking to brush up on existing skills or train on new advancements in AI, we have a wide range of AI courses designed for all skill levels. 

Schedule a demo today to learn how Flow can ensure your team reaps the benefits of AI-assisted software development.

Flow Transformation Team

Flow T.

Our engineering transformation experts are here to help you and your team embrace The Flow transformation process by establishing a foundation, demonstrating impact, and strategically growing your team in the most effective and efficient way possible.

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