AI won’t replace the PMO, but it will reshape it, creating what we call Amplified Impact. As AI changes how projects are delivered, strong governance, sound judgement and alignment on value are more important than ever.
Key Insights
- AI amplifies existing practices
- Admin automation frees value
- PMO oversight remains critical
Right now, there’s a lot of discussion in project management offices (PMOs) across Australia about AI and its impact on project delivery — some of it useful, much of it overhyped.
Over the past few months, we’ve been working closely with senior project professionals, sponsors and delivery teams in the Quay Consulting network to explore where AI is showing up, what it’s actually helping with and where the risks are starting to appear.
At Quay, we are on our own journey with AI. Like many of our clients, we are experimenting with where it creates value and where it needs more guardrails. What we’re seeing is that AI doesn’t replace project expertise — it amplifies its impact. In skilled hands, it accelerates delivery and governance, helping teams focus on what matters. But when delivery structures are weak or governance is lacking, AI has the opposite effect: it magnifies inefficiencies and masks risks, usually by giving false confidence to teams that don’t know what good looks like.
At Quay, we think of this as Amplified Impact — the tendency for AI to scale whatever systems and habits are already in place, for better or worse.
Where AI is being used in project delivery (and what it’s good at)
For better or for worse, AI is already making its way into project delivery, but not always in ways that are highly visible at first glance. In many teams, it is being used behind-the-scenes to support some of the more mundane administrative tasks, such as:
- Writing schedules
- Summarising meetings
- Drafting risk registers
- Generating status reports
Most of this is happening through free tools like ChatGPT, or using embedded features within platforms like Smartsheet or Microsoft Copilot.
The purpose of project delivery is to create value, and governance exists to guide and protect that value. What often gets in the way is the sheer volume of administration, which adds overhead without creating outcomes. When applied well, AI reduces that burden and shifts the focus back to value-creating activities. Administration may not be the only application for AI in delivery, but it is a logical place to start given the lower risk to outcomes.
When used well, AI tools can strip hours out of routine admin and free teams to focus on delivery. The danger is when a polished output is mistaken for real progress. A schedule or report may look convincing, but without expert input it can miss the details that matter most — leaving decision-makers with the impression of substance when there is little behind it.
Therefore, given their proximity to outcomes, delivery and governance activities are best impacted by expertise. AI isn’t the problem here, it’s using those tools in the absence of experience and judgement.
When AI accelerates the wrong things in the PMO
False confidence has always been one of the biggest risks in project delivery, and AI can amplify it. It is easy to be persuaded by the echo chamber of detailed pages and polished reports that look convincing but do not reflect reality.
At Quay, we’ve supported clients on projects where the problem was not a lack of data or analysis — there was plenty of both. The real issue was that the detail masked weak thinking. AI can accelerate this tendency by producing more material, faster, without the necessary controls or critical reflection. The result is reports that read well but mislead, or schedules that appear complete but are not grounded in the actual delivery context. What matters most is not the quantity of detail but the quality of analysis.
AI will inevitably influence decision-making in PMOs, from shaping initiatives to how they are run. The risk is that its accessibility encourages more business-led or BAU projects, giving leaders the sense they can take on more. Without governance maturity, that extra load often leads to more risk, not less.
This is particularly common in decentralised or business unit-owned projects, where delivery is happening outside the centralised PMO. Teams are trying to do more with less, and AI can make that feel possible — even when the fundamentals aren’t in place. We explored this trend in more depth in our recent article on decentralised delivery and BAU project risk.
As one senior project leader we spoke to said: “You can now generate a project report that looks great, but if you don’t know what good looks like, you won’t realise it’s garbage.”
In other words: AI doesn’t fix broken practice. It accelerates it.
We explored more insights like this in our recent conversation with senior project professionals on the emerging role of AI in delivery.
The AI governance gap (and why the PMO still matters)
This is why the role of the PMO is still just as critical (if not more so). In environments where AI is being adopted without clear oversight, the greatest risk isn’t slow progress — it’s moving too fast in the wrong direction. The danger comes when tools are used to accelerate delivery before the fundamentals are in place: clear scope, real risks, quality inputs and alignment on value.
An effective PMO doesn’t need to control every detail, but it does need to set the conditions for success. That means fit-for-purpose governance, visible decision rights, clarity on what “good” looks like and the ability to intervene when projects go off track. (While this article focuses on the PMO, the reality is that AI adoption is inherently cross-functional. Delivery, technology, risk and finance all play a role in ensuring new tools are used safely and strategically.)
It also means helping teams stay aligned on why the work matters, not just whether it’s progressing. In our recent piece on reframing delivery through the lens of value, we explored why traditional metrics like time, cost and scope are no longer enough to guide strategic project decisions. Value is what gives delivery its direction, and AI can’t prioritise what your people haven’t defined.
AI might streamline processes, but it can’t replace judgment. And it won’t catch what a mature PMO is designed to see early (before it becomes a costly recovery effort). That exposure extends beyond delivery risk and into organisational risk, particularly in functions like finance where trust in AI remains low and change readiness is still evolving.
What good looks like in an AI-aware PMO
While the role of AI in project delivery is still evolving, we’re starting to see clear signals of what good looks like. These traits are emerging in PMOs that are using AI safely and effectively:
- A clear definition of value to guide decision-making
- Lightweight governance that supports (not slows) delivery
- Practitioners who understand both project context and the tools they’re using
- Consistent data practices and quality inputs
- A culture of enquiry — where the priority is asking better questions, not generating faster answers
Getting this right is going to be a journey, but the signs of maturity are already starting to emerge.
What comes next?
We’re still in the early stages of understanding how AI will reshape the PMO. However, one thing is already clear: it’s not about replacing delivery expertise; it’s about amplifying its impact.
If you’re experimenting with AI, navigating a move to BAU delivery, or just want to sense-check whether your governance is still fit for purpose, we’re up for a conversation. Let’s brainstorm it together.
Quay Consulting is a professional services business specialising in the project landscape, transforming strategy into fit-for-purpose delivery. Meet our team or reach out to have a discussion today.
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