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AI Set to Transform Way Application Development Projects Are Managed

The race is now on to infuse project management applications with generative artificial intelligence (AI) capabilities that promise to reduce the level of friction that now all too often occurs between developers and the project managers tasked with making sure application development and delivery deadlines are met.

Atlassian, for example, is extend the large language models (LLMs) that OpenAI created to provide summaries of software development projects managed using its Jira software. Based on an Atlassian Intelligence capability the company is infusing into all its cloud applications, the AI capabilities also make it possible to launch queries via a natural language interface and surface relationships and dependencies that exist between projects.

Elsewhere, ClickUp has added templates and collaboration tools to make it easier to invoke prompts that invoke generative AI platforms such as ChatGPT from within its namesake software-as-a-service (SaaS) application for project management.

The templates make it simpler to, for example, produce summaries of project timelines in addition to automatically generating a whiteboard listing tasks that need to be finished to complete a project.

Finally, Microsoft has promised to create Copilots for every application it provides, including Microsoft Project.

There’s no doubt additional LLMs will be created for project management applications that will further transform the relationship between project managers and the DevOps teams they support. Historically, project managers have been dependent on member of DevOps teams to provide updates. That requirement often forced project managers to constantly issue reminder to DevOps teams to update the status of any given project. DevOps teams often resent having to manually reenter data that already exists within the applications they already employ. Machine learning algorithms coupled with LLMs should make it possible to automatically update any application that exposes an application programming interface (API). The days when project managers needed to nag members of a DevOps team for status updates are now all but over.

It’s now only a matter of time before generative AI is applied across the entire software development lifecycle (SDLC). There will be as much irrational exuberance as there is fear and loathing of AI but DevOps teams that have always been committed to ruthless automation will naturally be at the forefront. The immediate challenge is assessing what functions will be automated and the impact those changes will have on the way DevOps teams are currently structured. Ultimately, the goal is to eliminate as many DevOps bottlenecks as possible at a time when despite previous investments in automation manual tasks continue to bog down workflows.

Less clear is the degree to which generative AI will impact DevOps. Some argue most of the software engineering process is about to become automated, while others suggest there will always be a need for a human to be in the loop of any process automated using AI models. The one thing that is certain is the pace at which applications are built and deployed is about to be greatly accelerated.
In fact, that accelerated pace of innovation is likely to create additional project management challenges as the number of applications being simultaneously developed steadily increases. AI, in fact, might reduce the total cost of building and deploying applications to a point that is, for all intents and purposes, negligible.

It’s not likely AI will replace the need for project managers any time soon. Arguably, it will be just the opposite as it becomes easier to launch multiple application development initiatives using developers that may not require as much coding expertise. The challenge, of course, will be making sure none of those application development initiatives are redundant to one another as they continue to multiply across the enterprise.

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