Diego Lo Giudice, Vice President and Principal Analyst and Mike Gualtieri, Vice President and Principal Analyst
There’s fewer timelier topics for business and technology leaders right now than the impact of AI on the enterprise, and those leaders heading up software development teams are no exception. In this episode, Vice Presidents and Principal Analysts Diego Lo Giudice and Mike Gualtieri provide their unique insights on how AI is already impacting the developer’s role and what the future will bring.
The episode starts with an explanation of what TuringBots are (AI systems to support software developers during various stages of development), Forrester’s history in researching the topic, and where the name came from (a nod to computer science pioneer Alan Turing).
From there, the conversation turns to the benefits and advantages of TuringBots. As Gualtieri points out, there are trillions of dollars spent every year on software development around the world, and Forrester predicts that in 2023, TuringBots will write 10% of worldwide code and tests. So these “tiny little percentages” of productivity improvements translate to huge savings for organizations. But they aren’t without risks, and the discussion goes on to cover developer concerns around security licensing issues.
Lo Giudice then walks through some of the use cases for TuringBots across the software development lifecycle, from coding to testing to security. According to Forrester data, 30% of developers use AI and machine learning in the testing phase of development. Taking it a click deeper, Lo Giudice describes how AI tools such as GitHub Copilot or Tabnine are, or will be, embedded in integrated development environments (IDEs); chat-based generative AI like ChatGPT, however, likely won’t function within an IDE.
Developer sentiment around AI in software development is mixed. While some developers have trust issues and fear being “replaced” by AI, Lo Giudice points out that most orgs are using AI to automate more manual work in the cycle, leaving developers more time to focus on the creative and fulfilling aspects of their jobs, which increases job satisfaction and retention.
The episode closes with some next steps for organizations looking to deploy TuringBots in their software development organization, as well as guidance on which use cases are the most mature and which are still in the experimentation phase.
To hear more on this topic, be sure to check out the webinar Risk Or Reward? Generative AI’s Impact On The Software Development Lifecycle.
- AI Insights
- APIs & API management
- Application Development & Delivery
- Architecture & Technology Strategy
- CIO insights
- development & operations (DevOps)
- Emerging Technology
- Generative AI
- low-code platforms
- natural language processing (NLP)
- Responsible AI
- robotic process automation (RPA)
- text analytics