Only One in Five Singapore Professionals Show the Mindset Traits Epitome Global Calls AI-Ready
As Singapore organisations race to adopt AI tools, a workforce intelligence firm’s data suggests the technology isn’t the bottleneck. The people using it are.
Epitome Global, a Singapore-headquartered workforce analytics company, released aggregated skills assessment data in February covering Singapore and Malaysia between 2023 and 2025. The company found that only around one in five professionals consistently demonstrate the behavioural traits associated with AI readiness — specifically, persistence, curiosity, and reflective learning.
The firm has captured close to 1.3 million user profiles to date through its workforce intelligence platform, giving this particular finding a broader evidentiary base than a typical one-off industry survey.
The company’s own positioning matters for how the finding lands, too. Epitome Global works directly with both public and private sector organisations on workforce planning and skills assessment, meaning this data reflects patterns observed across real hiring and training programmes rather than a hypothetical survey sample assembled purely for research purposes.
Founded in Singapore in 2016, the firm has spent close to a decade building out the kind of longitudinal dataset that makes a claim like “only one in five” credible rather than anecdotal — a distinction that matters when the finding is being used to justify real training budget decisions rather than simply generating headlines.
A Digital Literacy Gap That Isn’t About Digital Literacy
The data, drawn from more than 200 participants across workforce development and organisational programmes, complicates the usual narrative around AI adoption. More than 70 percent of participants reported advanced digital literacy — technical familiarity with tools is not, on this evidence, the constraint most companies assume it to be.
The gaps showed up elsewhere instead. Around 56 percent of participants rated themselves at only a basic level in decision-making, and 42 percent reported basic confidence in computational thinking — the capacity to supervise AI outputs, question them, and integrate them meaningfully into a workflow.
Epitome Global’s CEO, Kevin Chan, summarised the disconnect directly: AI tools are scaling faster than workforce readiness. The differentiator in the next phase of adoption, he argued, won’t be which tools an organisation has access to, but how clearly its people can think, decide, and adapt around those tools.
Why Mindset Traits, Not Technical Skills, Are the Constraint
The traits Epitome flagged as scarce — persistence, curiosity and reflective learning — sit closer to psychology than to any specific software competency. That distinction matters for how organisations design their training response.
A worker can be taught to operate a new AI tool in an afternoon. Teaching someone to sit with an uncertain or wrong AI output, question it, and iterate toward a better one is a fundamentally different kind of development — closer to mindset coaching than software onboarding, and correspondingly harder to build through a single workshop.
That’s precisely the gap most corporate AI rollouts in Singapore currently skip over, according to the report’s broader trend analysis, which found that 65 percent of organisations remain focused on basic AI use cases rather than scaling deeper integration into core workflows.
The pattern isn’t unique to Singapore, either. Epitome’s regional data pointed to a parallel shift across Southeast Asia and India, where professionals in markets like the Philippines and Vietnam are moving from cost-based outsourcing roles into higher-value technical and product functions — a transition that similarly depends more on adaptive mindset than on any single certifiable skill.
The Workforce Trends This Points Toward
Epitome’s report placed the mindset-readiness gap alongside four other 2026 workplace trends, including intensifying “fire and hire” cycles as companies rebalance toward advanced technical and cross-functional capabilities, and growing strategic emphasis on senior employability as ageing workforces are asked to serve as reviewers and mentors for AI-assisted work.
Taken together, the trends point toward a labour market where the deciding factor for 2026 won’t be how many AI licences a company has purchased. It will be whether the organisation’s people can approach ambiguous, AI-assisted work with the persistence and curiosity to actually improve at it over time.
For organisations building out their training roadmaps this year, the data offers a fairly direct instruction: pair every technical AI rollout with a growth mindset workshop singapore employers can use to build the underlying thinking habits, or risk a workforce that has the tools but not the readiness to use them well.
The one-in-five figure is also worth sitting with rather than rushing past — it suggests most organisations are training the majority of their people for a version of AI readiness that only a small minority currently possess, a mismatch that no amount of additional software licensing will close on its own.