Everyday Reflections

AI is gaining notoriety. Amazon laid off 14,000 employees in October. Most people were quick to point the finger at AI. It wasn’t about money or AI, but about “culture”, CEO Andy Jassy said on the earnings call. The idea was to remove excess layers caused by overexpansion, which was weakening task ownership and slowing down the leadership team, he added. 

Around the same time, a Meta spokesperson confirmed to CNBC that around 600 employees would be laid off in its AI unit. The reason was exactly the same: reduce layers and operate more nimbly. In short, it’s about reducing repetitive roles and shifting resources to high-growth areas. 

While there’s much collective fear about AI adoption, the reason for layoffs could be old-fashioned — dealing with bloated teams, cost cutting, or stemming from fears of an economic slowdown in the US.

New technology can make us nervous. But is AI taking away jobs or is it being used as an alibi to fix a short-sighted and bureaucratic work culture? 

AI will evolve and bring about transformation, but there’s currently a gap between hype and reality, and pressure of investment versus returns. A BCG report suggests that out of 1,250 firms, 60% had seen “minimal revenue and cost gains despite substantial investment” in AI. And a Deloitte survey showed that only 10% of organizations were getting “significant return on investment from agentic AI”.

Let’s consider Malcolm Gladwell’s acclaimed book Outliers, where he refers to the “10,000-hour rule” — it takes 10k hours of practice to achieve mastery over a skill. We could argue that for AI to lay off engineers, it would have to reach a certain level of productivity aka a tipping point. 

While we don’t know when that will happen, Gartner forecasts that by 2027, Gen AI will create new roles in software engineering and operations, prompting 80% of engineers to upskill.

Meanwhile, most effective CEOs are focused on building capacity to drive high-stake outcomes, states a Forbes article. AI is just one of the factors that can help with that. 

According to Goldman Sachs’ economists, Gen AI will raise the level of labour productivity in the US and other developed markets by around 15% when fully incorporated. If AI raises 15% productivity per engineer in a week, what value does that bring? Not much, as the company will require six human engineers working 40 hours per week each along with AI to gain 90% productivity of a single engineer.

The dynamics of capacity building are certainly changing due to AI. And the number of hires may fall as the technology improves and adoption rises. But the premise of AI being able to operate without human interaction, which investors are banking on, remains poor. 

Instead, for capacity-building we need to work towards making the existing workforce more upskilled to react to new challenges while more effectively deploying AI.

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