Humans Will Make or Break AI Transformations
For the optimum AI outcome focus on humans not the tech
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The AI revolution is upon us, but it is the human component that will decide its fate, not the AI, and it is well overdue that we focus on the human side of the equation.
Backing up this bold statement is the reality that in this recent survey, the top two key factors limiting AI development were human-related: 34% of companies can’t find AI talent, and 34% are battling employee resistance!
When employee resistance is a leading factor inhibiting AI implementations, you know that companies are doing something wrong.
Frankly, this phenomenon isn’t new, and with every new innovation, AI included, there is a tendency to focus on the tech over the people.
In my book “Innovation Lab Excellence,” I write:
“Innovation isn’t about the tech, but instead the relation of people to tech.”
Given the results above, it seems more true with AI than with the technologies that preceded it.
Note: this is the opposite of what you’re being sold by tech companies on a daily basis. The general pitch is that if you adopt some new plug-in technology, your problems will all be solved.
Put AI on this system and you’ll reap tremendous rewards, use an Agentic AI on that one and your problems will all go away.
We’ve heard it before, but for some reason, we are happy to be fooled once more. Why do we consistently fall for the message that tech will solve our problems?
In short, because we all wish it would work as advertised. Systems are easier to deal with than people, so at some level, we are victims of our own desire for a magical outcome. Sadly, it is people who pay.
You can’t blame us for wishful thinking, but at the same time, we must take some responsibility for ignoring the obvious.
People use AI, adopt AI, fight AI, and cause either its success or demise.
👉AI is about people, not tech:
🔹 Human-Centric Approach
Organisations that adopt a human-centric (also referred to as human-enabled) approach to AI transformation enhance the value derived from AI adoption. By putting employees at the centre of the internal transformation process, like client-centric approaches externally, organisations can achieve multiple benefits. This approach not only enables adoption but also accelerates impact, fosters resilience, and builds long-term capabilities.
🔹 Leadership Role
Leaders play a crucial role in driving and championing AI transformation. They should ensure an open-source approach and actively support AI initiatives. The development of new skills and attitudes is foundational to successful AI transformation. Leaders should actively lead by example, drive and support AI initiatives while promoting an open-source approach.
🔹 Upskilling & Reskilling
Traditional approaches to learning and development need to be reconsidered to address the AI skills gap. Organisations should adopt dynamic, experiential, and continuous learning models to close the AI skills gap. Prioritising a culture of continuous learning and innovation enables the smooth scaling of AI initiatives.
🔹 Pivotal Role of CHROs
Chief Human Resources Officers play a potentially pivotal role in unlocking and maximising the value that AI brings to organisations. They should lead the AI-driven transformations of hierarchy, work models, and career paths. CHROs should, but often fail to, lead the transformation of talent strategies, work models, and organisational culture to align with the new realities AI brings.
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