Unless you’ve been under a rock, you’ll know that AI has been – and continues to be – everywhere. From boardrooms to coffee breaks, it’s dominating conversations across industries and at all levels. While AI promises faster decision-making, increased efficiency, and sharper insights, the reality on the ground is more complex.
Employees are understandably wary. Concerns about job loss, surveillance, or being reduced to a number are common, and they are valid. AI can support and accelerate change, but it cannot – on its own – make that change real. Change ultimately happens when people understand, accept, and adopt it.
That’s why AI should be implemented with transparency and care. It should augment & enhance, not replace, human-led change. The future of organisational transformation isn’t just about more technology – it’s about technology that strengthens human connection and trust, rather than eroding it.
What AI Can Offer to Change Practitioners
For change practitioners, AI presents both an opportunity and a challenge. On one hand, it has the potential to make our work more efficient, allowing us to focus on what we do best – engaging with people. On the other hand, it demands that we stay clear on our role as human interpreters, translators, and enablers of change.
Prosci®1 report change practitioners are already using AI for streamlining communications and freeing up time for more strategic/people-centred work, amongst other tasks. Here are some more tangible ways AI can help:
- Sentiment and Feedback Analysis
Instead of manually collating survey results or trawling through chat threads, AI can aggregate and interpret large volumes of employee sentiment in real time. This allows change practitioners to spot concerns early, respond quickly, and identify pockets of resistance or disengagement before they become real problems. - Personalised Communication
AI tools can identify and group stakeholder audiences and tailor messaging to their interests, concerns, or readiness for change. This doesn’t replace human storytelling – but it can help ensure messages land more precisely and consistently, making communication efforts more meaningful and effective. - Predictive Analytics
Forecasting adoption risks is one of the most powerful ways AI can support change. By analysing past patterns, engagement signals and how people are responding in real time, AI can help map adoption risks and highlight areas where challenges may arise. This gives change practitioners a clearer picture of where to focus attention, allowing them to step in early and provide targeted support to ensure adoption stays on track. - Automation of Admin Tasks
Reporting, tracking, drafting standard comms, formatting presentations – these are all necessary but time-consuming. Automating these activities through AI frees change managers to spend more time where they add real value: listening, empathising, and supporting people through the change curve.Be careful with this though, if people feel like they are being engaged by a robot, it might alienate them and make them feel under-valued.
These tasks highlight that: AI can sharpen our tools, but it can’t do the work of trust-building.
1https://www.prosci.com/blog/ai-in-change-management-early-findings
Why Human-Centricity Still Matters
Even as AI gets more sophisticated, there are fundamental human elements of change that it can’t replicate – and likely never will.
- Trust is earned between people, not between people and algorithms. AI may be able to analyse sentiment, but it cannot build the emotional safety that makes people willing to engage openly.
- Leaders and change practitioners are still needed to actively role-model behaviours, adapt to subtle cultural dynamics, and respond in real time to emotion, subtlety, and context.
- Ethical risks are real. AI can reflect and even amplify existing biases in data. It can flatten out cultural differences or prioritise the loudest voices. Over-reliance on AI could mean missing out on the messy, human conversations where the most meaningful insights often emerge.
This is why a ‘human-in-the-loop’ approach isn’t just a good idea – it’s essential.
Practical Use Cases
As referenced earlier, the relevance of AI in change isn’t theoretical; it’s already happening in various forms across the world, including in New Zealand and Australia.
- Large Transformations
In large programmes – such as ERP rollouts, major infrastructure projects, or public sector reforms – for example, AI can help monitor engagement across possibly thousands of stakeholders simultaneously and flag business units that are showing lower engagement with training modules. Change practitioners are able to use this intel to intervene proactively and deliver targeted support/coaching and ultimately reduce resistance and keep the project on schedule. This is a great improvement to relying solely on periodic surveys to gain a real-time view of attitudes, perceptions and adoption readiness. - SMEs and Mid-sized Organisations
Smaller organisations often struggle to resource full change functions. AI tools can help them access a level of insight and structure that previously required larger teams, for example through automated pulse surveys, comms drafting, and adoption dashboards. - Public Sector
Public agencies face unique pressures around transparency and trust. AI can provide a scalable way to analyse community or employee sentiment via public or internal enquiries, enabling earlier identification of recurring concerns. This insight allows FAQs and other communications to be updated proactively and highlights areas needing additional attention. Crucially, these AI-driven insights must be paired with a deliberate human approach, ensuring people feel genuinely heard and respected – not merely monitored or managed by machines.
Good Practice & Principles
The way organisations use AI in change management will determine whether it builds trust or undermines it. Some key principles include:
- Transparency – Be clear with employees about how AI is being used in their change journey.
- Consent & Privacy – Respect boundaries and explain what data is collected, why, and how it will be used.
- Human Oversight – AI should inform human decisions, not make them.
- Cultural Sensitivity – It’s critical that AI doesn’t erase or overlook diverse perspectives. A human lens is needed to honour cultural nuance and uphold bicultural and multicultural values.
AI as a Partner, not a Replacement
The future of change management isn’t a choice between people and technology, but a strategy that brings them together. AI brings scale, speed and insight; People bring empathy, trust and context.
When aligned, transformation becomes sustainable and human-centred: technology amplifies what people can do, rather than replacing it.
Change happens at the speed of trust — and trust can’t be automated.
If you’re embarking on a change initiative and want support in any area of implementation or adoption, Millpond can help. We offer Business Analysis services to uncover the core issues and ensure any solutions, including AI, deliver real value; Change Management services to support awareness, acceptance and adoption activities as well as Project Management Services to deliver your project successfully, from start to finish.
Stay tuned for details on PMI’s new CPMAI certification and how it can support organisations in implementing AI projects successfully — including how Millpond can assist with training and guidance.
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