Zenhub Blog > AI > AI in project management: Developer attitudes towards AI use cases Zenhub Blog > AI > AI in project management: Developer attitudes towards AI use cases AI AI in project management: Developer attitudes towards AI use cases Kristen Kerr September 18, 2023 | 4 min read Table of Contents Artificial Intelligence (AI) is seeping into nearly every industry, and project management is no exception. For project managers, engineering leads, CTOs, and anyone who may be evaluating AI tools, staying on top of how devs are using this tech, their attitudes towards it, and whether it’s helping or hindering productivity is critical. To get some better insight into this, we recently conducted a small survey of 38 software team members to better understand attitudes and perspectives toward AI project management. Because sharing is caring, we’re publishing some of our findings in this blog to help everyone better understand the prevalence of AI in project management for software teams, how it’s being used, and whether it’s beneficial or not. *For more information on the survey respondents, please visit the appendix at the end of this blog. Are developers using AI? An overwhelming 71% of respondents are actively exploring AI tools for their professional tasks (this includes non-project management tools), illustrating a profound interest in AI within the development community. It shouldn’t be surprising that the already tech-savvy love leveraging the latest tech, no? The prevalence of AI in software development is important to note – for tech leaders, the exploration of AI tools comes with concerns and considerations. For larger companies, AI security regulations may be top-of-mind. For others, it’s worth considering how the rise of AI use is impacting the overall quality of their code – a concern a few GitHub Copilot reviewers told us a while back. If productivity and quality are a concern for you in the age of AI, check out this blog on measuring AI’s impact on performance. What aspects of project management would you most like to see improved or taken over by AI? It seems that software developers find “planning, estimation, and prioritization” the most exciting applications of AI in project management. This makes a lot of sense, considering these are often some of the most tedious and mundane aspects of managing projects. With that in mind, “backlog refinement” came in a close second place. If you’re a project manager, these stats may be important to take note of when considering what AI project management tools would be most useful for your team. What benefits are developers hoping to receive from AI for project management? The #1 benefit developers hope to get from project management AI is the reduction of busywork. No one loves mindless work. And, if anyone loves a challenge, it’s developers. So, it makes sense that devs love the idea of spending more time solving complex coding problems and innovating rather than doing work that doesn’t meet their level of expertise. So, what does this mean for tech leaders? Well, it could mean happier developers. According to our 2022 Developer Happiness Report, developers who spend less time with busywork were overall more satisfied with their jobs. In other words, investing in automation tools that enable devs to spend more time on problem-solving is not just a productivity investment. It’s a people investment. Additional findings: In addition to what’s presented in the graph above, some other comments developers made were that they were “looking to increase productivity,” “get insights into process improvements,” and get “better retrospective views of past projects.” All very valid potential use cases for AI. What are developers’ biggest concerns around using AI? The expectation from AI is to primarily reduce busywork and improve data accuracy. However, doubts about data accuracy and security and privacy concerns loom large. These concerns highlight the need for AI systems to offer comprehensive insights into the data they use. While there is enthusiasm for what AI can bring to the table, respondents made clear that AI systems must strike a balance between providing value and maintaining security, privacy, and data integrity. The survey paints a promising picture of the future of AI in project management as long as these systems can successfully address emerging concerns. Check out our blog on the most common AI user challenges for more info on what users are looking out for when using AI tools. Conclusion The integration of AI in project management is not a far-off concept but a present reality with immense potential. Developers, almost more than any other group, have shown a keen interest in embracing AI technologies, particularly for tackling mundane tasks and refining processes. However, this enthusiasm is tempered by legitimate concerns about data accuracy and privacy. The challenge for AI providers is to build systems that can deliver value while also ensuring data integrity, security, and privacy. If these concerns are aptly addressed, we stand at the brink of a revolution in project management, with AI leading the way towards enhanced productivity and efficiency. *Appendix: respondent profiles Respondents’ Departments The participants represented a wide array of departments, with the engineering department being the most prevalent. A significant proportion of respondents also hailed from academic environments, demonstrating an active interest in AI across specialized fields. Most Respondents Embrace Agile When it comes to software development methodologies, Agile reigns supreme, with 58% of participants reporting that Agile methodologies make their teams more efficient. Adding to this, 73% actively value and implement these methodologies. Share this article New Work smarter, not harder. With Zenhub AI Simplified agile processes. Faster task management. All powered by AI. Learn more
Project Management Why projects fail: The dangers of inaccurate project data Kristen Kerr August 23, 2024 | 5 min read Project Management The Best Scrum Software in 2024 Guest August 15, 2024 | 5 min read AI How to use AI for project management: 4 of the best use cases Kristen Kerr July 24, 2024 | 3 min read Project Management Will AI help or hurt data integrity? Both. Here’s why Kristen Kerr July 17, 2024 | 5 min read Hone your skills with a bi-weekly email course. Subscribe to Zenhub’s newsletter. Email Return to top
Project Management The Best Scrum Software in 2024 Guest August 15, 2024 | 5 min read AI How to use AI for project management: 4 of the best use cases Kristen Kerr July 24, 2024 | 3 min read Project Management Will AI help or hurt data integrity? Both. Here’s why Kristen Kerr July 17, 2024 | 5 min read Hone your skills with a bi-weekly email course. Subscribe to Zenhub’s newsletter. Email Return to top
AI How to use AI for project management: 4 of the best use cases Kristen Kerr July 24, 2024 | 3 min read Project Management Will AI help or hurt data integrity? Both. Here’s why Kristen Kerr July 17, 2024 | 5 min read
Project Management Will AI help or hurt data integrity? Both. Here’s why Kristen Kerr July 17, 2024 | 5 min read