We’ve all had that sinking feeling after a long weekend or holiday: opening our inbox to find projects that haven’t yet moved forward but haven’t been scrapped either. They sit in limbo, quietly draining time and reducing productivity.
These are what we call ‘Zombie Projects’, and they are becoming a real productivity problem for UK businesses. Our recent research found that 41% of UK workers usually carry projects over from one year into the next, and 90% of respondents surveyed globally say they’ve caused problems.
AI Evangelist at Atlassian.
They are also damaging employee experience, morale and wellbeing, with a third (33%) of UK workers feeling stressed and overwhelmed by these projects, and 28% saying they lead to team burnout.
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In today’s fast-paced and demanding work environment, this type of ongoing project becomes an operational nightmare, especially against a backdrop where UK productivity declined last quarter.
Luckily, AI can help by surfacing information and analysing which projects are inactive or no longer needed, and support teams to make decisions around which projects to see through and which to retire.
A lack of clear ownership keeps Zombie Projects alive
Zombie Projects continue for a common reason; many workers are unclear about who has the authority to end a project, or when it is acceptable to do so. This creates a decision gap, and work continues by default.
Most team structures are designed to deliver projects, not to abruptly close them. Without a clearly assigned leader or decision maker, it’s hard to find the moment when a project should end, so progress slows, and teams don’t see any meaningful outcomes, but activity doesn’t fully stop. Modern work patterns, where an employee can have multiple tabs open at the same time, amplify this, as it’s far easier to leave tasks open than to actively close them.
Psychological factors also reinforce the fear of shutting down a project, and 30% of UK employees fear being perceived negatively if they make the decision to retire a project.
Set clear parameters, and apply AI
So, getting a handle on Zombie Projects needs to start with defining ownership, putting in place clear statuses, and documenting everything in a shared system, so teams can understand where projects are starting to grind to a halt. This could include defining how projects are labelled as ‘complete’ or ‘ongoing’, or sharing regular updates tied to outcomes that have been agreed by the whole team.
This is where AI can then be applied to help manage and triage projects effectively. In fact, half of the workers in our recent survey felt that having a dedicated AI agent for Zombie Projects would allow them to decide which projects are deemed the highest priority, and what isn’t essential work.
An AI tool can help to monitor project activity against agreed parameters and highlight where work is drifting off track or slowing down. AI helps increase visibility, reduce ambiguity, and support clearer decision-making. It can continuously surface stalled work, flag misalignment, and rank tasks by impact so individual workers and teams can be clear on how to get a project back off the ground or take a call to close it.
This can also reduce the manual burden on employees, as instead of manually assessing documents and trying to determine which ones matter most, AI can quickly summarize the most important projects or actions in a snapshot: work that’s powering progress, work that’s consuming capacity without clear objectives, and work that hasn’t advanced.
Ultimately, AI doesn’t create more time, but it can expose where time is being wasted, especially within dormant work, and help make informed decisions on when to put a Zombie Project to rest.
Ending the zombie project gap, once and for all
Projects turn into Zombie Projects when teams don’t feel clear on who is taking ownership of decisions, and when the information needed to make those decisions is hard to find and understand. Applying AI to projects can make it clearer and easier to see where things are falling off track and make informed decisions on how to progress or retire projects.
The value of AI in this context is not automation alone, but better decisions. Intelligent, integrated AI tools can surface the context and insight needed to distinguish between initiatives worth reviving and those that should be retired. This shifts the conversation from emotional or stakeholder-driven considerations to evidence based prioritization.
Working in this way is good for productivity, but it will also reduce stress and burnout among teams, and free up time to work on the projects that really matter – not the ones that are just weighing teams down.
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