The global rush to adopt artificial intelligence (AI) is accelerating, with organisations pouring resources into productivity tools, automation systems and digital platforms. But beneath the hype lies a dangerous blind spot: readiness is not about technology, it is about people.
That was the warning from Vera Solomatina, SVP of people and culture at inDrive, at the recent Women in Tech conference in Cape Town.
AI readiness
“AI readiness should be measured by the level of internal trust in an organisation,” she said. “Organisations are investing heavily in technology, but seem to underinvest in the psychological safety of the people who will actually work with it.”
Solomatina argued that companies are mistaking installation for integration. “Buying an AI platform only creates the illusion of transformation,” she noted.
“Real readiness is when employees feel safe saying ‘I don’t understand how this works’, and are given the tools and resources to learn.”
Gaps
The gap between deployment and adoption, she said, is where most stumble. Reskilling programmes, often rolled out at scale, miss the mark.
“What works is contextual, embedded learning built into real workflows, not delivered as standalone courses,” she explained.
“Mandatory e-learning and programmes designed exclusively for senior or technical staff don’t typically work. This approach rarely translates into behaviour change or true adoption.”
Collaboration
Instead, Solomatina pointed to peer-led collaboration as a more effective model.
“We’ve seen that the best AI ambassadors are often not the most senior people,” she said. “If upskilling only reaches leadership and tech teams, you create an AI-literate elite and a disengaged majority that simply widens the readiness gap.”
HR
She insisted that human resources must move upstream in AI decisions.
“HR must move from being a function that responds to AI decisions to being the architect of how AI processes and tools will be implemented,” she said.
“That means the chief people officer needs to be at the table where automation decisions are made, not brought in afterwards to manage potential issues.”
New skills
This shift demands new skills from HR leaders: data fluency, awareness of AI ethics and the ability to interrogate bias.
“If the data used to train models reflects historical biases, automation doesn’t remove those biases; it scales them,” Solomatina warned. Diversity and inclusion, she argued, must be embedded into AI design, not bolted on afterwards.
Her message was clear: AI readiness is not a technical milestone but a cultural one. Without trust, psychological safety and inclusive design, organisations risk building systems that alienate rather than empower.
