From social media panic to AI reality: we are learning to slow down

Less than two decades ago, at the advent of social media in the global media space, traditional media was given a hurried funeral. Commentators predicted the death of newspapers, editors warned reporters to brace up for job losses, and journalism schools quietly wondered if they were training students for extinction. About 15 years on, that funeral is still unfinished.

Newspapers may be thinner, radio less dominant, and television more fragmented, but traditional media did not die. Instead, it adapted, coexisted, and, in many ways, reinvented itself alongside social platforms.

Today, a strikingly similar panic surrounds artificial intelligence (AI). AI, like social media before it, is being framed as a revolutionary force that will upset work, eliminate jobs, and fundamentally redefine organisations. From Davos to Lagos boardrooms, the language is breathless: ‘turbocharged productivity’, ‘leaner teams’, and ‘machine-led efficiency’. Yet the lived reality, particularly in Nigeria and much of Africa, is far more measured. CEOs are discovering that AI’s impact on work is slower, messier, and more human-dependent than the hype suggests.

When generative AI tools entered mainstream use, executives expected a near-immediate productivity boom. Many assumed that once employees had access to AI, output would automatically rise. Instead, companies are encountering hesitation, scepticism, and uneven adoption.

Global experience illustrates this clearly. At Cisco, leadership learned that making AI training mandatory actually produced negative results. Rather than driving sustained usage, it bred resentment and resistance. Only when employees were given choices, multiple tools and freedom to experiment did adoption improve.

This lesson resonates even more strongly in Nigeria. Workers already operate in an environment shaped by job insecurity, inflation, and repeated restructuring. For many, AI is not seen as a helpful assistant but as a silent auditor of relevance. When CEOs push AI aggressively, employees often respond defensively, limiting experimentation rather than embracing it. The result is a paradox: expensive tools deployed, but little meaningful change in day-to-day work.

One reason AI’s impact has been slow is fear of redundancy, fear of uselessness, and fear of being measured against a machine. In Nigerian offices, these fears are amplified by weak social safety nets. Losing a job often means losing access to healthcare, education, and stability for extended family members. It is therefore unrealistic to expect enthusiastic AI adoption without first addressing trust.

Executives are beginning to realise that AI transformation is not just a technical project but a cultural one. Trust cannot be commanded through policy memos or performance metrics. It must be built through transparency, explaining what AI will and will not be used for, where human judgement remains central, and how workers can grow alongside new tools rather than be replaced by them.

Another sobering reality is that access to AI does not equal competence in using it. Many employees can open an AI tool, but few know how to integrate it meaningfully into complex workflows. Prompting, validation, ethical judgement, and contextual understanding are skills that require deliberate training.

Some executives argue that the solution lies in hiring younger, AI-native graduates. Globally, this approach is gaining traction. But in Nigeria, where youth unemployment is already a ticking time bomb, replacing experienced workers with younger ones is neither socially responsible nor economically sound.

As Deloitte has observed, most organisations have invested heavily in AI technology while neglecting investment in people. Nigerian companies mirror this imbalance. Training budgets are often the first casualty of cost-cutting, yet without sustained learning, AI remains underutilised. CEOs are now slowly accepting that real returns on AI will only come when training is treated as infrastructure and not as a perk.

Perhaps the most underestimated barrier to AI productivity is organisational design. Many Nigerian companies still operate with outdated workflows, poorly defined roles, and undocumented processes. Introducing AI into such environments is like pouring petrol into an open flame.

Even global firms like Google and Amazon recognise that transformative productivity gains require redesigning work itself. Job descriptions, team structures, and decision-making processes must be rethought. For Nigerian organisations, particularly in banking, government, and traditional media, this is painstaking, time-consuming work.

Startups, especially in fintech and digital media, offer a glimpse of what is possible. Built from scratch in the post-ChatGPT era, many are naturally AI-native. Legacy organisations, however, face years of transition before AI can genuinely reshape productivity.

A looming question in global boardrooms is whether AI will eventually shrink workforces. Some executives admit that if productivity rises while growth slows, headcount reductions may follow. At companies like SAP, leadership has so far opted to keep headcount flat while growth continues.

In Nigeria, this conversation is especially sensitive. With millions of young people entering the labour market yearly, any perception that AI will accelerate job losses risks social backlash. Nigerian CEOs are therefore approaching AI cautiously, not out of ignorance, but out of necessity.

Sadly, Nigeria desperately needs productivity growth to compete globally. But productivity that comes at the cost of widespread job destruction, without pathways for reskilling or new industries, is unsustainable. In this context, AI’s slower-than-expected impact may be a blessing. It buys time to rethink education, labour policy, and social protection.

The premature burial of traditional media offers a valuable lesson. Social media did not eliminate journalism but changed it. Reporters adapted, editors evolved, and audiences learned to navigate multiple sources. AI will likely follow a similar trajectory.

For Nigerian CEOs, the implications are clear. Pressure will fail where choice can succeed, as technology investment must be matched by human investment. Organisational redesign matters more than any emerging tools. Above all, patience is strategic, not a weakness.

AI’s revolution in the workplace will come, but not on the timelines promised by those preaching it. When it does, it will be deeper and more disruptive than current incremental changes suggest. By slowing down, learning deliberately, and centring people in the transformation, Nigerian executives have an opportunity to shape an AI future that enhances work rather than hollowing it out.