Author: Sonya Poonian
Whether AI improves your organisation this year will depend less on the tools you buy and more on how you lead people through change. This is not a technology project; it's a leadership challenge.
For People, Comms and Ops leaders, this is a defining window. Decisions made now will shape not just technology adoption, but capability, confidence and competitiveness for years to come.
AI isn't a toolkit; it's a catalyst for reimagining how work gets done. Many leaders I speak with can feel the ground shifting — business expectations are rising while a new stability point hasn't yet arrived. The opportunity is to understand the tools, their potential, and how to harness them for your function, team, people and your business. This is a moment of significant opportunity; the chance to shape the next era of work, not just react to it.
Over the last 12 months, working across sectors, we've helped organisations move from pilots to performance by embedding AI tools and use cases into real workflows and building human skills, AI literacy and capability to sustain change. Investment is needed in teams to leverage these tools to enable your people and function to be at their most innovative and provide greater value.
Here's what makes adoption stick and compounds value:
1. People-first change is essential
Upskilling and psychological safety are the foundations of ROI. Adoption stalls when people don't trust AI or see its relevance. Create environments across all management levels where experimentation is safe, roles are clear, and everyone sees themselves in the future of work.
2. AI literacy, upskilling and capability building is key
Dedicated enablement turns interest into impact. Prioritise relevant, role-based training and practical practices so teams become AI enabled in the work they already do. If inertia is happening, taking action and investing in capability building is critical.
3. AI as a force multiplier
AI isn't just about automation — it's about amplification. The best results come when AI is woven into daily workflows and underpinned by live, contextual training, enablement and ongoing reinforcement. The most successful teams use AI to unlock new ways of working, freeing team members for higher-value, more creative work.
4. Guardrails build confidence and speed
Approved tools, standard prompts and clear escalation paths create a safe space to experiment. With clarity and autonomy, teams learn faster and scale small wins. When teams have clarity and autonomy within these boundaries, they experiment more, learn faster, and embed AI into their daily work. Start small — start somewhere.
5. Redesign for human skills
As routine tasks shrink, human strengths rise — critical thinking, creativity, empathy, adaptability. Capability, mindset, aptitude and attitude beat seniority every time — measure skills growth, not tenure and leverage AI to augment and drive value creation.
6. Leadership and transparency
Role model curiosity, invest in your own learning and be open about the journey. Make growth visible and valued — especially for leaders and exec teams. This builds trust, in a changing landscape, and signals that change is a shared endeavour.
7. Measure impact, not activity
Move from 'AI everywhere' to 'AI impact.' Prioritise business and people outcomes (quality, speed, risk, engagement) over deployments. With capex scrutiny rising by executive teams, robust change management and clear ROI are non-negotiable.
8. Inertia will happen, act against it
Overwhelm creates stall. Teams won't embed this alone and it's difficult to expect them to do so with such a significant transformation. Provide upskilling, training, team guardrails and a structured path. (We use a maturity model to guide teams from early experimentation to strategic, data driven use.)
Closing thought
This is not a technology project; it's a leadership challenge. The organisations that thrive will treat AI as a catalyst for human potential, rather than a cost saving tool, where AI literacy, capability, trust and culture become differentiators. The next 12 months will define the next decade.
Will you experiment at the edges, or embed AI at the core? Will you let change happen to you, or will you lead it? Because in the end, AI doesn't transform work — people do.
