In a previous blog, we explored the leadership gap in AI adoption; the missing strategies, ownership, and clarity slowing progress before it begins. But strategy isn’t the only hurdle.

For many organisations, the real blockers are messy, overlapping, and deeply human: fear, confusion, misalignment, and a general sense of “we’re not ready yet.”

In our latest survey of 864 professionals across Australia and New Zealand, we asked what’s standing in the way of progress. The answers paint a clear picture: while the potential of AI is huge, the practical challenges are still very real.

Strategy gaps continue to stall progress

When asked about the biggest obstacles their organisation faces in keeping up with AI:

• 41.0% said “no strategy”
• 40.6% said “unclear goals”
• 34.4% said “lack of clear ownership”

This is a leadership problem, not a tech one.

You can’t build with AI until you know what you’re building for. And right now, many organisations are still waiting for that direction to come from the top.

“Waiting on strategic policy and approval before AI can be implemented and risks mitigated,” one respondent shares with us.

It’s a sentiment echoed across industries: people want to move, they’re just waiting for direction.

Fear and fatigue are real, and so is trust

AI isn’t just a technical shift, it’s an emotional one. For some employees, the potential of AI feels like a threat rather than an opportunity. And that shapes how it’s received, even in pilot stages.

“I’ve found a resistance from the team due to a concern around job security,” said one participant.

When people don’t understand how AI fits into their role, or worry it could replace them, enthusiasm quickly turns into quiet pushback. The data backs this up:

• 46.2% cite “security or compliance concerns” as the biggest barrier
• 10.3% point to “lack of trust”
• 15.3% say there’s “no training”, which only worsens that anxiety

Burnout, not optimism

A surprising theme emerged in some open-ended responses: fatigue. For many, tech-enabled “productivity” hasn’t always delivered better outcomes, just more pressure.

“Productivity improvements have never helped in the past,” one respondent wrote. “They’ve just led to higher expectations and burnout. AI is not a way forward as a society if we don’t fundamentally rethink our systems.”

It’s a powerful reminder that even the best tools won’t succeed if they’re layered on top of broken processes or disconnected cultures.

The blockers aren’t always what you’d expect

Some of the most-cited reasons for slow adoption weren’t deeply technical, they were practical and immediate:

• Limited budget – 36.6%
• Lack of relevance to my work – 16.8%
• Lack of access to tools – 11.5%

This matters, because it tells us AI isn’t failing because it’s complicated, it’s failing because it hasn’t been meaningfully integrated. If employees don’t see how AI helps them, or they can’t get to the tools at all, progress stops before it starts.

So, what now?

The first step isn’t buying tools, it’s creating space for clarity, communication, and small wins. This might mean:

• Bringing departments into strategy-setting conversations
• Addressing fears head-on through honest leadership
• Investing in real training that shows how AI can make work better, not just faster

Because when blockers are this human, the solutions need to be too.

Access our free report here to explore what’s really slowing AI down and how to start moving forward with clarity and confidence.