Experiment first, strategy later: How AI is entering the workplace - HRM Asia

TEXT START: New AI models have arrived over the past three years faster than most employers could evaluate them.

The Dissection

This is a field report on diffusion lag disguised as a strategy memo. It documents rising AI use, widespread employee-led experimentation, weak employer visibility, and widening gaps by occupation, education, and company size.

What the text is really doing is converting a system-level labor-substitution question into an HR implementation problem: visibility, rules, training, governance, and measurement. It acknowledges task disruption while keeping the frame on “successful transformation,” not whether human employment remains economically necessary.

The Core Fallacy

The article treats slow organisational absorption as a counterweight to AI capability. It is not. A 38% adoption rate measures institutional delay, not a ceiling on what AI can do.

Under the Discontinuity Thesis, P1 is the decisive variable: once AI achieves durable cost and performance superiority, P2 prevents institutions from preserving large human-only economic domains. P3 follows. Tasks disappear, entry routes narrow, and fewer workers are required. Training may make workers more capable of using AI; it does not create enough economically necessary work to employ them.

The article’s emphasis on human verification is another unproven assumption. Verification itself can be automated, narrowed, or concentrated among a small number of indispensable controllers. “Human in the loop” is often just a temporary label for a shrinking loop.

Hidden Assumptions

• AI will remain mainly a complement to jobs rather than a mechanism for eliminating them.
• Organisations can redesign work without materially reducing headcount.
• Job-specific training can preserve employability after the underlying tasks lose value.
• Wider access will distribute AI’s gains instead of distributing displacement more evenly.
• Employers can choose the pace of adoption despite competitive pressure to cut costs.
• SME support and national training systems can preserve mass participation rather than merely delay unequal collapse.
• Employer ignorance is a temporary governance defect, not evidence that diffusion is bypassing formal control.
• The fact that employees currently expect other jobs to be hit means their own positions are structurally safe.

Social Function

Primary classification: transition management. Secondary classification: ideological anesthetic and partial truth.

The data is real: adoption is slow, uneven, and initially task-level. But the article uses that true observation to make the transition appear governable through better HR practice. It gives institutions a checklist for administering the shock while redirecting attention from ownership and labor displacement toward training, compliance, and organisational learning.

It is not pure copium. It accurately describes the lag phase. Its failure is mistaking the lag phase for a stable future.

The Verdict

Accurate on the incubation chamber, blind to the corpse.

The article does not refute AI-driven obsolescence. It records its early conditions: shadow deployment, compounding skill gaps, concentration among cognitive workers, and a widening divide between those who control AI-enhanced work and those excluded from it.

Once firms identify which experiments create value, competitive pressure will force strategy to follow: workflows will be redesigned, entry-level tasks will vanish, and labor demand will compress. HR can measure and administer that process. It cannot restore the mass employment–wage–consumption circuit.

Under DT logic, this is not capitalism adapting. It is the machinery warming up before the cuts become official.