The growing consensus is that AI isn’t the great disruptor that many first anticipated it would be. It isn’t leading to wholesale job losses and instead is making us rethink how we complete tasks and how roles could be redesigned.
During our latest webinar:
- 36% of attendees said they believe AI will mainly change tasks within existing roles
- 31% said it will eventually lead to new roles and career paths being created
There’s a clear sense that right now, people and organisations have the chance to adapt to this new technology – presenting an opportunity to build skills and capability ahead of time. And if HR has a seat at the strategy table, businesses can begin to implement targeted experiments that will eventually inform wider workforce change decisions.
- 51% of attendees say AI experiments exist but skill models and roles haven’t changed yet
But none of this is to say the path ahead looks clear. Considering the speed at which AI is still evolving, the journey we’re all on is more likely to resemble an obstacle course than a clear running track. And it will be our collective flexibility and resilience that determines both individual and organisational success moving forward.
What are organisations still missing when adopting new technology?
The integration of AI has generated unprecedented noise within the world of work – much of which has been driven by a fear of falling behind. As most organisations look to quickly embrace this new technology, there’s still an element of uncertainty as to whether AI creates genuine value.
ManpowerGroup’s 2026 Talent Barometer found that AI usage is up 13% year on year, but that employee confidence in using it dropped 18%. On top of this, 42% said they believe automation may replace them within two years.
When organisations rush into the implementation phase of a new tool or resource, they inevitably miss critical steps in laying the foundations for successful adoption – resulting in a workforce that is both unprepared and resistant.
“Clients are feeling the urgency more than the mastery… the real value of AI only comes when organisations redesign tasks and workflows with AI and shifting expectations in mind. When they actively support people to use AI well – raising AI fluency – that’s what moves the dial.”
- Nicola Rundle, Global Solutions Architect
Failing to plan and prepare simply leads to AI being layered on top of existing roles and processes – making for more noise and confusion without necessarily improving results. And so the question for leaders is how can we ensure new technology is implemented in a way that supports positive disruption, in a world so heavily dictated by speed?
Has an innovation speed gap already taken hold?
Whenever new technology or systems come into play, innovation speed gaps are a big issue.
As was seen in the early 2000s, businesses began buying and integrating content management systems and e-commerce platforms that their internal processes and ways of working were not ready for. For a long time, organisations were trying to use these new tools for outdated practices – leading to insufficient outcomes and a lag in innovation.
Today, a similar gap is emerging whereby the processes and products being used by teams were never designed to work at the speed in which AI is now demanding we operate.
“Organisations invest a lot in new ‘shiny objects’ but they don’t build the foundations to actually use them. Unless you’ve got a strategy, governance and data in place to take full advantage of new technology, AI will move faster than the organisation can evolve.”
- Marike Carstens, Global Lead Product Innovation & Development
However, the technology isn’t the limiting factor, rather the way it’s being adopted. Organisations are investing in AI before they’ve taken the time to consider how humans and AI are meant to work together. As a result, their attempts to bridge any capability gaps are inadvertently amplifying and widening them instead. And if these gaps are allowed to grow, so too will people’s distrust.
Implementing AI with explainability and trust at its core
When it comes to change, the most important decisions must happen before anything is switched on.
“You have to be very clear about how you want to govern AI before it becomes part of your core processes… once it is embedded in your workflows, it becomes incredibly difficult, both politically and operationally, to change again.”
- Marike
All key stakeholders must be aligned on the operational aspects of AI early on – with clarity on what it’s designed to do, what information it uses, where humans step in and how someone can question or appeal an outcome if needed. Only then can trust, confidence and a sense of explainability be secured for all, from the outset.
“Explainability is about responsibility. It’s about being able to clearly explain why a decision was made, in a language that people can understand, and being willing to stand behind that explanation if it ever gets challenged.”
- Nicola
At the end of the day, AI should be treated the same way as a new employee: define its role, its authority, how it’s supervised and most importantly, when human judgement takes over. Only then will leaders be capable of communicating and implementing technological change that is not only accepted but welcomed by the wider workforce.
To discover five key takeaways that can help inform the way in which your organisation integrates AI, and much more, catch up on our webinar today.
