The operations manager of a growing construction firm spends most of Monday doing the same thing she does every week: chasing site managers for updates, copying figures into a spreadsheet, building a status report for the directors and turning meeting notes into action lists. By the time the report is finished, some of it is already out of date. The actual problems on site, a delayed delivery, a subcontractor dispute, a client changing their mind, get her attention only on Tuesday.
She isn’t unusual. In many businesses, the people responsible for projects spend a large share of their time gathering and reporting information rather than solving problems, making decisions or looking after relationships.
This is exactly where AI and automation are starting to change project management. They are taking over much of the administrative load, freeing the people who run projects for the judgement and leadership that projects depend on.
One Like insight: AI is good at tracking projects. People are still needed to lead them.
What the forecasts and surveys say
In 2019, the research firm Gartner made a bold prediction: by 2030, 80% of the work of today’s project management discipline would be eliminated as AI took on traditional functions such as data collection, tracking and reporting. Gartner stressed that this didn’t mean project managers would disappear; rather, the routine parts of the job would be automated, and the role would shift towards leadership, problem-solving and managing people and change.
More recent survey data shows adoption is real but still early. The Project Management Institute’s 2023 Annual Global Survey on Project Management found that about 21% of respondents were using AI in their project work. The top three uses were reporting (34%), decision support (33%) and communication (26%). And 82% of senior leaders said AI would have at least some impact on how projects are run in their organisation over the next five years. PMI also noted that relatively few project professionals had practical experience with AI.
Forecasts like Gartner’s are predictions, not findings, and the 80% figure refers to today’s tasks, not to jobs. Survey figures date quickly in a field moving this fast, and adoption has very likely grown since 2023. But the direction is consistent: AI is taking over the information-gathering side of projects, while the human side becomes more important.
Using AI and automation in projects now
Small businesses don’t need specialist enterprise software to benefit. Many everyday tools already include useful features.
Automate status updates. Project boards and task tools can automatically flag overdue tasks, send reminders and produce progress summaries, so nobody spends Monday compiling them by hand.
Turn meetings into actions. AI note-takers and assistants can summarise meetings and draft action lists with owners and dates. A person should check them before they’re shared, as explored in AI Sounds Sure of Itself.
Draft plans and reports faster. AI can produce a first draft of a project plan, risk list or client update from your notes. Treat it as a starting point that you refine with your own knowledge.
Spot risks earlier. Some tools can highlight tasks that are slipping or resources that are overloaded. Even simple automated alerts, such as “no update in five days”, catch problems sooner.
Keep the human work human. Stakeholder relationships, negotiating changes, motivating a team and making trade-offs remain firmly people’s work. As explored in From Chaos to Clarity, shared understanding is built through conversation, not dashboards.
Before automating, simplify. As we explored in Fix the Process Before You Automate It, automating a messy project process just produces mess faster.
[Infographic placement] How project work is shifting. Two columns. Increasingly automated: data collection, status tracking, reporting, reminders, meeting notes, first drafts. Increasingly human: leadership, stakeholder relationships, judgement and trade-offs, problem-solving, change management. Beneath: Gartner (2019): 80% of today’s PM work could be eliminated by 2030. PMI (2023): top AI uses are reporting (34%), decision support (33%) and communication (26%).
Getting started
Track where your project time actually goes for one week. Note how many hours go on gathering updates, writing reports, chasing people and taking notes, and how many on solving problems, making decisions and talking to clients. Then pick the single most time-consuming administrative task and try automating it with a tool you already have: automatic reminders, an AI meeting summary or an automated weekly status report. Measure the hours saved, and decide deliberately how to use them.
A few questions can help:
- How much of our project time is spent gathering and reporting information?
- Which repetitive project tasks could our existing tools automate?
- Who checks AI-generated plans, notes and reports before they’re used?
- What would we do with the time saved, and how will we protect it?
Which brings us back to the construction firm’s operations manager and her Monday of chasing and copying. Automated status updates and an AI summary of site reports could hand her a draft report by Monday morning. That would free the rest of her day for the delayed delivery, the subcontractor dispute and the client who’s changed their mind: the work where her experience makes the real difference.
Sources
- Gartner, “Gartner Says 80 Percent of Today’s Project Management Tasks Will Be Eliminated by 2030 as Artificial Intelligence Takes Over”, press release, 20 March 2019, as reported by MacTech.
- Project Management Institute, “Demand Increases for Project Professionals with AI Skills, Yet PMI Research Finds Only 18% Have Practical Experience”, 26 September 2023, reporting the 2023 PMI Annual Global Survey on Project Management. The 21% usage figure is from secondary reporting; confirm against PMI’s source.
