What the Latest Salesforce and YouGov Data Reveals About AI Adoption in Singapore?

I was reading through the latest Salesforce and YouGov data on AI adoption, published on July 8th, and it included a result that surprised me a bit.

The report indicates that Singapore is one of the least AI-sceptical workforces in the survey. Yet it also has the lowest level of everyday AI usage.

The combination of those stats deserves some digging into.

Only 29% of Singapore desk workers describe themselves as AI sceptics, well below the global average of 37%.

At the same time, just 6% say AI is a core part of their daily work. That’s the lowest figure across the 14 markets surveyed and almost half the global average of 11%.

If people are open to AI, why aren’t they using it?

Could the answer be hidden elsewhere in the report?

Among Singapore workers whose AI pilots were unsuccessful, 40% said the outputs were too generic, the highest of any market surveyed and ten percentage points above the global average. Another 38% said they didn’t trust the outputs.

That definitely adds more colour to the initial conclusions.

This doesn’t sound like a workforce resisting AI. It sounds like a workforce that tried AI, found the results underwhelming, and quietly moved on.

Too often, we assume slow adoption is a people problem. We talk about resistance to change, culture, or digital readiness.

The data suggests another possibility.

Perhaps the bigger issue is the quality of AI implementation.
If the outputs are generic, lack business context, or fail to solve real problems, employees won’t keep using the tools, no matter how many generic training sessions they attend.

Successful AI deployment isn’t just about giving people access to a model. It’s about grounding that model in your organisation’s data, workflows, customer knowledge, and expertise, so the outputs are sufficiently relevant to earn trust.

People don’t adopt AI because they’re told to. They adopt it because it consistently helps them do their jobs better.

For leadership teams, perhaps the deliberation isn’t:
“How do we overcome AI scepticism?” but “Have we built AI experiences that are genuinely worth coming back to?”

Because the bottleneck may not be willingness, it could be execution.

My view is that the data signals from the other markets will start to catch on to the failed pilots for the same reasons.

We need fewer tools, more workflow redesigns. Start from where the friction is and then work on the adoption.

Source: Salesforce and YouGov, survey of more than 1,500 desk workers across 14 markets, conducted between December 2025 and January 2026, published July 8th 2026.