Transforming the way software engineers work by integrating generative AI


The emerging tide of generative AI is supercharging the way software is made and managed. As a new wave of software development dawns on the horizon, an increasingly competitive environment will necessitate engineers to think fast about how best to integrate this new technology in order to stay ahead of the curve. In this blog, we’ll delve into four key areas software engineering teams need to look to prioritize when it comes to AI. 

  • Small shifts, big benefits: The best way to get started is to embrace the change in stride. By identifying certain, everyday tasks where AI shines (such as facilitating bug fixes, testing, and documentation), software engineers can steadily spend less time on menial, rote activities, and shift their focus onto more meaningful work. The results are immediately noticeable – 88% of developers using generative AI tool Copilot reported feeling more productive at work. 
  • Accessibility matters: Getting everyone on the team up to speed on new technologies and know-how is necessary to maximizing the productivity of a team collectively – and ensuring no one gets left behind. Dealing with knowledge silos remains as one of the biggest persisting problems for software engineers, with 70% running into a knowledge silo once a week. As the pace of work accelerates through the use of generative AI tools, this problem will only be exacerbated if everyone isn’t progressing at the same pace of progress. 
  • Speed is key: Now’s the best time to experiment with and discover where best generative AI fits into the development process of each team is essential – it’s the dawn of a new era where most teams haven’t figured things out yet. However, generative AI is an incredibly fast-moving piece of technology, and capabilities are only set to make leaps and bounds within the coming years. Teams that set the foundation for functional use of generative AI will be able to adapt and adopt new benefits quickly – while those that don't will be struggling to play catch up while the competition rushes forward. 
  • Keep security top of mind: However, it’s critical to ensure that teams are properly trained and educated when it comes to applying sensitive enterprise information to generative AI. Already, 11% of all information being input into ChatGPT is confidential. Teams need to think carefully about which sort of solutions they use and integrate when it comes to integrating AI and LLMs into the workplace. 

As businesses explore further how best to incorporate generative AI into their everyday work, it's crucial for software engineering teams to start now if they don’t want to fall behind. With the pace of production set to accelerate, furthering product innovation and maintaining the competitive advantage will rely heavily on a team's capability to quickly seize the opportunities that generative AI provides now and in the future. 

Generative AI isn’t the only priority that software engineers need to keep in mind, however. Everything from the way teams are tackling the talent gap to integrating new tools to maximize coding time and efficiency is set to change the way software is developed and engineering teams collaborate. Get the complete picture by downloading our latest whitepaper on trends shaping the future of software engineering.

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