The impacts of AI are mostly viewed through the lens of improving business processes, but AI is poised to have long-term impacts on engineering too. Not only can AI make it easier for engineers to bring their ideas to life, but it can also remove the burden of manual toil that keeps them from focusing on more business-critical issues. The growing integration of AI into engineering workflows will drive both engineering efficiencies and business advantages as teams continue to unlock valuable use cases.

Here are three ways AI will bring long-lasting change to engineering practices.

AI will accelerate prototype building and idea validation

For teams assessing their current architectures and gauging where they want to be in the next few years, AI can help identify the changes they would need to make and the prototypes they would need to build. An engineer may compile bullet points to map out their thought process, which can then serve as the initial AI prompt to assist in building out the plan. The feedback generated from the AI prompts can enable teams to make decisions faster and get into the proof-of-concept stage at an accelerated pace.

AI can also help engineers become more efficient by directing them where to begin research. For example, when building a chat UI, AI can identify various factors the engineer needs to think through, such as performance and network considerations, and create a list of recommended actions. As a result, teams can get a head start on their projects and ultimately get to solutions faster.

AI will increase the importance and quality of documentation

It’s important to remember that AI tools need direction, and they’re only as good as the data they’re trained on. If the AI doesn’t have good input, it can’t create good output.

The industry will move toward stronger documentation practices because of how AI works. In order for the AI to perform as desired, organizations need proper, up-to-date documentation to prevent the AI from making incorrect assumptions. Well-formed prompts that are focused on an outcome, and that give the AI easier ways to discover the documentation, make a significant difference in performance because these prompts can give the AI stronger context and direction to work with.

Plus, AI can be leveraged to ensure that technical documentation is kept up-to-date and relevant. Similar to prototyping, engineers can automate the initial stages of documentation to help reduce the amount of time they spend on it. The engineer can then use their expertise to review and refine the AI-produced documentation, further guiding the AI toward the correct results.

AI will increase the focus on compliance

Compliance remains an ongoing challenge for organizations as they navigate data and privacy regulations around the world, including GDPR and SOC 2. Maintaining compliance is crucial to avoiding costly fines and penalties from regulatory bodies, but also to protect the organization from potential reputational damage. AI use exposes a new liability as organizations are now challenged with managing the data it can access.

As organizations feed sensitive company and customer data into their AI tools, they need to ensure that the data stays within these systems. Teams need to maintain visibility into how accessible the AI data is internally, as well as what other tools may be exposed to it. Additionally, strong guardrails and security permissions must be established to prevent any unauthorized access or use of customer data. While every organization is eager to deploy AI, they need to be vigilant around the level of data access they grant these tools.

The future of engineering

The ongoing integration of AI will transform the ways engineers work. They can kick off their projects faster and offload their more boring and tedious tasks, freeing them to focus on the higher-impact issues that require human expertise. Between speeding up prototype building and increasing productivity, engineers will be empowered to find more ways to leverage AI as they continue to guide their organizations toward innovation. 

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