Humans in the Loop

Generative AI has gone from being almost a sci‑fi novelty to a super important part of our daily lives, this smart assistant is rewriting the rules of learning at work, and we need to work with a fresh mindset to thrive in the future.

Benjamin Laker writing in Forbes, says the secret weapon to this new learning paradigm is nothing mystical but a classic education principle: the growth mindset. He uses the brilliant phrase, “embracing failure as data for improvement” and carving out time for side‑projects are the hallmarks of those who will flourish in an AI‑augmented world . It is a simple pivot: swap fixed notions of talent for a belief in plasticity, and you gain the resilience to experiment, iterate and keep pace with machine‑speed change.

“AI is rewiring how we learn, and it is a game‑changer for L&D”
Josh Bersin

L&D guru Josh Bersin warns though that the seismic shift AI brings is not being met by seismic changes in training. In Chief Learning Officer, he argues that “AI is rewiring how we learn, and it is a game‑changer for L&D” . Traditional, one‑size‑fits‑all e‑courses will not do the job. Instead, learning must be woven into the flow of work with AI offering on‑demand answers, and is part of the solution and personalised pathways.

That is where a growth mindset meets practical tools. Andrew Morse of Aquent insists that “a growth mindset is key to generative AI expertise” urging teams to treat AI not as a black box but as a collaborator. He points to examples where creative and marketing teams used AI to draft campaign ideas then rapidly refined them through human critique – combining machine scale with human judgement. This is the play and practice part of learning. Experiment like a boss!

The real test comes in job design. Dr Kellie Nuttall of Deloitte Australia argues that simply waiting for new roles to emerge will not work. Organisations must proactively “embed AI into real workflows, prototype new job designs and create capability roadmaps” if they want to harness human skills such as ethical reasoning and creativity . In practice, this means piloting hybrid human‑AI teams, measuring outcomes and iterating before a full roll‑out.

Taken together, these voices point to a clear playbook. Cultivate a mindset that prizes learning over expertise, leverage AI to personalise and accelerate training, and rethink work itself so humans and machines each do what they do best. This is so much easier to put in a blog post than to realise. It will take unlearning years of embedded ways of working and being. The current workforce faces the hardest adaptation. Like learning to be a car mechanic after shoeing horses for a living.

We need to learn to learn, and then to learn again. And again.