AI and job cuts: What the block layoffs signal for pharma and beyond

In the past few months, the corporate world has seen a surge in workforce reductions that are explicitly tied to artificial intelligence (AI) and automation — not just general cost-cutting. The biggest recent example comes from fintech firm Block Inc., which announced plans to cut over 4,000 jobs — roughly 40 % of its workforce — as AI tools reshape how it builds and runs its business, according to multiple news reports.

Block’s CEO Jack Dorsey said the layoffs were driven by efficiency gains from “intelligence tools” and that most companies are “late” to this realisation, suggesting that smaller, AI-powered teams can operate more effectively than larger ones of previous eras. Investors rewarded the move, with shares rising more than 20 % after the announcement.

My comment about the investors awarding job cuts is that, just “wow”. Are the investors also using the AI in this sci-fi movie of life?

This public acknowledgement — that AI itself rather than exogenous economic shocks is a structural driver of job cuts — marks a shift in corporate narrative compared with previous downsizing cycles, where layoffs were attributed to financial struggles, reorganisations, or macro pressures.

Is Pharma next? The short answer: not like tech – yet

While broad headlines claim “AI is slashing jobs,” the situation in the pharmaceutical industry is more nuanced.

A recent analysis from BioPharma Dive noted that pharma companies are cautious about directly eliminating jobs because of AI, primarily because many scientific, clinical, and regulatory roles require judgement and deep domain expertise that current AI cannot fully replicate.

Recruitment experts like Jae Yoo of EPM Scientific have been quoted as saying that AI is more likely to rehouse and reshape jobs than replace them one-for-one in pharma. Instead of cutting entire departments, the industry is seeing roles evolve — with AI augmenting tasks in research, data analysis, and operational workflows.

As pharma leaders have also noted in industry communications, roles that require curiosity, creativity and critical thinking are less at risk of outright elimination, and new roles in AI oversight and data science are emerging.

What the block example tells investors?

1. Cost efficiency through AI works — investors notice
   In fintech and tech sectors, companies that explicitly tie job cuts to AI gains are being rewarded by markets with share price increases — as seen with Block. This demonstrates that investors are already pricing in efficiency improvements from automation, even before productivity metrics fully materialise.

2. Pharma may be slower to adopt cuts, but adoption is coming
   Pharma’s AI transformation has so far focused on R&D acceleration, trial optimisation, and administrative automation, not headcount reductions at scale. But structural pressures — such as R&D productivity declines and competition for talent — may push companies toward streamlining operations wherever AI can add measurable value.

3. AI creates new, not just replaces old roles
   If pharma follows the general trend described in industry analyses, AI will not simply replace jobs but transform them. Roles in data curation, model governance, regulatory AI oversight, and computational biology are becoming more prominent, offsetting some displacement effects. But the new jobs require less humans (apparently).

Structural differences: pharma vs tech

It’s important to underscore that the AI-driven layoffs seen at companies like Block, Salesforce, and others — where AI tools are replacing workforce tasks directly — do not yet appear in pharma at the same scale. The reasons include:

• Scientific and clinical complexity: many pharma tasks involve experimental design, patient interaction, regulatory nuance, and cross-disciplinary synthesis that AI augments but does not fully replace.

• Regulatory risk: the pharmaceutical industry is highly regulated, making wholesale automation of certain functions slower and more cautious.

• Talent scarcity: deep expertise remains irreplaceable for many strategic functions.

However, pharmaceuticals are not immune to broader automation pressures seen across industries. Tech giants such as Amazon and Microsoft have also linked AI integration to workforce changes, even if not always publicised as such.