Whether you’ve tried ChatGPT once or use automated tools daily, it’s hard to miss AI’s monumental growth. According to Grand View research, the global artificial intelligence market is expected to grow 37.3% from 2023 to 2030. And of all fields, AI in software development will see some of the most investment.

There’s no denying that AI has a place in the future of software engineering, so getting ahead of artificial intelligence adoption is crucial for tech leaders to stay competitive. To help refine your AI strategy, we’ll highlight opportunities and considerations for implementing AI in software development.

Table of contents:

Will AI replace software engineers?

Opportunities and risks of AI code

How to use AI in software development

How to mitigate the risks of AI in software development

How tech leaders should proceed with AI

Track and measure your AI initiatives with Pluralsight Flow

Will AI replace software engineers?
AI won’t replace software developers anytime soon. Even with customization, specific use cases, and wishful thinking, AI has too many limitations. That said, AI will change how software engineers work—70% of developers report AI coding tools give them an advantage in completing tasks and improve their productivity.

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As Corey Coto, SVP of product development at Pluralsight, explains:

 AI won’t replace all software developers and engineers. AI will help developers accomplish more by freeing them up to work on higher-level problems. Companies that invest in increased automation to chain tools and AI together will amplify the impact human developers make. 
How will AI impact the developer experience?
Software development AI will change the ways teams design, develop, document, deliver, and debug software. Developers could also use AI as a mediator when collaborating with teammates, stakeholders, and customers. Specifically, AI can speed up feature additions, bug fixes, and support requests. 

These changes stem from a few key sources: 

Developers will switch from design to platform thinking. In the past, developers built code for outcome-oriented design. Now, AI developers will focus on how platforms function in goal-oriented design. 

AI will help draft user stories, acceptance criteria, and requirements. developers will pass this information to business analysts to ensure it aligns with their overall strategy. 

AI will assist with basic UI design and leave more complex interactive design elements to human teams. After AI lays the groundwork for pages and flows, designers create a UI that helps users navigate through them. 

AI will deliver true continuous delivery. Agile teams can use AI to write high volumes of code and draft PRs for teams to review. With AI assistance, developers can increase their overall rate of delivery to make it feel more continuous. 

Testing will become a higher priority. As AI produces more code, teams need to build the architecture that tests it from every angle. Test architects will assess end-to-end functionality and create new regression tests if issues emerge.

Opportunities and risks of AI code
Automation poses growth opportunities and risks to your operations. We'll explain the pros and cons to help you understand its full impact. 

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What generative AI can do
While using AI in software development won’t improve every process, prompt engineers can play to its strengths. Prompt engineers design inputs to get the desired output from AI. Prompt engineering can help teams handle work like: 

Rote, repeated tasks: AI can complete routine tasks with well-defined steps. While this work is important, leaving it to AI frees up developers to focus on more complex problems AI can’t handle.

First drafts of code: Software engineer AI gets the first draft off the ground quickly. When developers aren’t sure where to start or have trouble entering a flow state, AI-generated code gives a great place to start. 

Small updates to existing code: AI perfectly suits small edits and code refreshes. You can use AI tools to find bugs, improve prewritten programs, and make adjustments based on specific criteria.

Reduce cycle times: AI offers tight feedback loops and the ability to analyze business roadmaps. By tracking performance across projects, AI can improve predictions and find the optimal path to completing tasks. 

What you need developers for
Despite AI’s strengths, human developers outpace it in many processes. So, you still need a team of human developers for:

Complex coding requirements: Some projects ask developers to juggle multiple requirements. While AI can respond to prompt engineering, it struggles to manage complex criteria while keeping the big picture aligned with expectations. 

Contextual outputs and organizational knowledge: AI can’t predict your organizational preferences, so AI-generated programs may not align with your security and performance requirements. Software developers need specific prompting or edits to align the code with strategic initiatives. 

Broader strategic approaches: AI works best within a narrowly defined scope. It can create programs that fulfill specific tasks but can’t align its output with wider strategic approaches. You need a human dev to stylistically and functionally align all your software.

Autonomous action: AI requires inputs to get outputs. The current crop of AI is generative, so it creates text from prompts and predicts what should come next based on the vector weights.

As AI and its benefits continue to grow, the onus is on engineering leaders to keep up with emerging trends to make the most out of the technology. For example, LangChains is an open-source framework that allows developers to chain together multiple large language models and perform more advanced actions. 

To help train your team on new software dev skills, try Pluralsight Skills. Our platform offers over 7,000 courses to help your teams upskill and reskill to stay competitive in today's changing dev landscape.

How to use AI in software development
Knowing when and how to use AI is crucial to getting the most out of the available tools. We’ll cover the best opportunities to use AI for software development in the years to come.