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Generative AI is rapidly changing the way projects are planned and executed. Teams can now produce documentation, analyze scenarios, and coordinate work faster than ever. Yet this level of efficiency is introducing new risks of poor data quality, weak governance, and over-reliance on automated insights.

In every industry, including cloud infrastructure, security, marketing technology, and data services, leaders are assessing both sides of this transformation. Organizations including OpenMetal, Securitas, Adzviser, Kanerika, and Inspire11 are experimenting with generative AI to improve project workflows, even as they struggle with the operational and cultural adjustments it requires.

Faster Plans, Messier Reality

One of the most visible shifts is the automation of preparation work that once consumed hours of project managers’ time. Generative AI tools can now draft user stories, acceptance criteria, project roadmaps, and training plans in minutes. 

Teams are also using AI to test and validate planning assumptions before execution begins. At OpenMetal, a company focused on cloud infrastructure, AI is increasingly used to analyze planning options and align product development with customer needs.

Jamie Tischart, CTO responsible for product strategy at OpenMetal.io, sees the biggest opportunity in reframing how teams approach problems.

“I think the biggest thing is to not limit the usage… if you go and turn that on its head and instead say, how can AI help solve this problem, you can become a lot more efficient in how you build everything.”

The Double-Edged Sword of Speed

Faster planning can also accelerate poor decisions. Generative AI can quickly simulate schedules, dependencies, and operational scenarios, but that speed may reduce opportunities for experiential learning and human judgment. Security services provider Securitas has explored AI tools across its programs, including internal systems such as “SecuritasGPT” and initiatives that train employees to experiment responsibly with AI.

Ahlilah Longmire, Sr. Brand Communications & PR Officer at Securitas North America, says governance and prompt precision remain critical.

“The amount of prompts you have to play with to get the right level of definition of what you’re trying to execute is quite fascinating to me, right? Like, especially for what I do, I never want to lose the Securitas brand tone or things that are just proprietary to us, but how many prompts it takes me to get it the way that I need it is like, you know, you spend 15–20 minutes just trying to get the prompts right to really, you know, for your work to really be accurate and consistent.”

Data-Driven Campaigns and Budgets

Marketing teams are also integrating AI into project management by replacing manual spreadsheet analysis with natural-language insights. Campaign performance, budget allocation, and reporting cycles are increasingly handled with AI-assisted tools.  

Zeyuan “Goo” Gu, founder and CEO of Adzviser, advises teams to maintain a balanced approach.

“Always treat AI as a new hire and then you should be the grand master of whichever AI tool you’re using… Take it as recommendations, but take it with a grain of salt.”

From Task Tracking to Strategic Oversight

Another shift is happening in execution. Agentic systems are beginning to automate routine project tasks such as status tracking, standups, and dependency monitoring.

Bhupendra Chopra, Co-Founder and Chief Revenue Officer at Kanerika Inc., points to the company’s Jarvis agent as an example of automation expanding inside project environments.

“It is the human issue or the personnel issues that AI can’t control. Otherwise, from the project management perspective. AI is doing a great job… Like our Jarvis agent is stabilizing; it has taken 50% and is likely to reach 80% project management. So the PM organization will scale higher with AI; my expectation within the next 12 months or so, absolutely.”

An Underused Capability

Despite the rapid growth of AI tools, adoption remains uneven. Many enterprise project managers still rely on traditional methods, even when AI features are available in their software platforms.

Laura Sundberg, Chief Marketing Officer at Inspire11, says the gap often reflects experience levels rather than technical limitations.

“I think AI is still very unmet… I think AI is still very underutilized in project management… there’s a lot of very seasoned project management professionals… where I think we’re seeing it much more underutilized in a slower adoption rate than other areas where AI is being applied.”

Designing AI-Augmented Project Teams

Industries are beginning to realize that generative AI works best as a collaborator, not a replacement. Teams use it to accelerate preparation, analysis, and coordination, while human leaders remain responsible for setting priorities, making trade-offs, and making strategic decisions.

Organizations are stepping up to exemplify this change, showing how generative AI is neither improving nor complicating project management. Instead, it is fundamentally changing how the work gets done.