Beyond the Hype: Leading AI with People at the Centre (Participatory Development)

Image/Canva Alt-text: People working at desks in a bright, modern office.

As we see and hear more hype about AI, with social media platforms constantly over promising on what AI can deliver, what is often forgotten, or not included in these conversations, is “Participatory Development”. 

For some, AI may look like the technology that has come to rescue people from their mundane tasks. For others, these so-called “mundane” tasks not only provide a welcome break in their day but, more importantly, they help play their bills and give them a sense of purpose.

What’s often missing in the AI hype is contribution from those for whom, the AI tool is meant to “rescue” or save - the people on the ground actually doing the work. 

Whether building an HR-AI solution or other, Participatory Development means these communities should be actively involved in shaping the solutions meant to help them

Instead, AI developers (often working unilaterally) and/or leaders who lack a full understanding of the value chain, identify a solution, based on assumptions about how the chain should work, rather than how it actually operates, including staff workarounds. Spurred on by their echo chambers or media hype, they design, build, or buy AI tools, and then expect people to fit around the technology. Unsurprisingly, they later wonder why (AI) adoption rates remain stubbornly low once the tools are deployed downstream.

Shouldn’t we instead involve people first, identify the problems they face, and only then build AI solutions tailored to their needs? After all, who decided that what the world most urgently needed was an AI tool that can create a bird eating a pink elephant? Granted some may call this creativity.

We’re frequently told that AI is worth US$ 244 billion and that CapEx on AI infrastructure could surpass US$3 trillion in the next three years. Yet the question remains: which US$3 trillion+ problem is AI actually trying to solve?

There’s no doubt that AI has enormous capabilities, but the real challenge is its application

Identify a Problem First

Like any startup, shouldn’t AI developers or those leading AI projects first ask: what problem are we trying to solve? Could this be addressed by recruiting more staff or offering additional training? Could the solution be automation, or do we really need AI? If so, can we justify the costs, time, training, as well as human intervention? 

After all, if an AI tool needs constant monitoring and/or correction, is it truly saving us time? And, if we remove the human-in-the-loop, might the AI tool we rely on actually exacerbate existing inequalities? 

Finally, what about the very people this tool is meant to ‘rescue’. Have they been consulted in its design and testing, or will problems only come to light once it fails under real-world pressure?

Why Users need to be included from the start (Participatory Development)

A story is told about a well-intentioned NGO that built a water well in a rural community in the global south only to find that some women were unexpectedly unhappy with the change. In many rural communities, the daily task of fetching water is often fraught with risk and involves long walks to distant (water) sources. While this is a hard and risky chore, for some, it was also an opportunity to bond, share news, support one another as well as maintain community ties. So, when the  well was installed, some women felt a sense of loss. This is a cautionary tale about overlooking Participatory Development. 

AI development isn’t just about infrastructure, it’s about integrating AI strategically while keeping people at the centre.

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If you’d like to learn more about embedding AI Literacy and Responsible AI in your organisation, then please free to contact me on LinkedIn or, visit ExecutiveGlobalCoaching.com to learn more about how we work

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1. Responsible AI - (this one) Putting People and Culture at the heart of AI Strategy.

2. Leading with Emotional Intelligence (EQ)

3. Inclusive Leadership in the era of AI