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Let me tell you about a Tuesday morning in a buying office in Gurugram.
2019. Peak season. A team of six merchandisers — combined experience of over 60 years — sitting around a table. The task: write product descriptions for 120 SKUs of a new women's ethnic wear collection. Deadline: 48 hours.
They finished in 52 hours. Three people worked through the night.
I ran the same exercise last month. One person. Claude AI. 120 product descriptions.
Four hours. Every piece industry-accurate, brand-appropriate, platform-optimised.
That is not an anecdote. That is a 92% reduction in time. For one task. In one week. Of one season.
Multiply that across an entire buying cycle — and you begin to understand why I believe AI is the single most significant shift Indian apparel has seen since the introduction of modern retail formats in the early 2000s.
The Numbers Nobody Is Talking About
India's apparel market is valued at approximately $75 billion and is projected to reach $115 billion by 2026. We have over 45 million people employed across the textile and apparel value chain. We are the world's second largest exporter of textiles, shipping to over 100 countries.
And yet — a significant percentage of the skilled time in this industry is spent on tasks that require language rather than expertise.
Consider what a typical mid-size apparel brand manages in a single season:
300 to 800 SKUs requiring product descriptions, care labels and catalogue copy. 15 to 40 vendor relationships requiring regular written communication — purchase orders, quality briefs, delivery follow-ups, rejection notes. Trend reports for buying teams that inform ₹10 crore to ₹100 crore worth of purchase decisions. Tech packs and specification sheets for every new style developed.
In a buying house handling ₹500 crore worth of merchandise annually — which is not large by industry standards — the volume of written communication produced every year runs into tens of thousands of documents.
Most of it is produced manually. Inconsistently. At the cost of hours that senior professionals should be spending on decisions — not documentation.
This is the problem AI solves. And it solves it completely.
What 27 Years Taught Me About This Moment
I started in textile engineering and moved into apparel buying at a time when fax machines were still the primary mode of vendor communication. I have watched this industry absorb computerised inventory systems, ERP platforms, digital sourcing portals, e-commerce and omnichannel retail.
Each of those shifts changed how we worked. None of them changed what we knew.
AI is different. For the first time, a technology is not just changing how work gets done — it is changing who can do it well.
Here is what I mean
A junior merchandiser in 2024 with two years of experience and strong AI fluency can produce a trend report that matches the quality of one produced by a ten-year veteran working manually. Not because the junior person has the same knowledge — they do not. But because AI can supply the structure, the language, the format and the industry context that previously only came with years of practice.
The implications of this are significant — and they cut both ways.
For organisations: the productivity gains are real, immediate and compounding. A team of 10 that integrates AI into its workflow does not just save time. It multiplies its effective output — producing the volume of work that would previously have required 25 to 30 people.
For individuals: the stakes are higher. The gap between a professional who combines deep expertise with AI fluency — and one who relies on expertise alone — will widen every year from this point forward. The experienced professional who also masters AI does not become replaceable. They become irreplaceable.
The Three Places AI Creates Immediate Value In Indian Apparel
Based on my own experience applying these tools across buying, merchandising and retail content functions — here is where the return is fastest and most measurable:
Vendor Communication
The average apparel professional spends between 8 and 12 hours per week on vendor emails alone — follow-ups, quality briefs, rejection notes, price negotiation correspondence, delivery scheduling. AI reduces this to under 2 hours, with higher consistency and significantly improved professional quality.
For a team of 10 merchandisers, this is 60 to 100 recovered hours per week. Per week.
Content and Catalogue Production
India's D2C fashion market alone is growing at 40% year-on-year. Every brand in this space needs product descriptions, category pages, campaign copy, size guides and trend editorials — every season, at scale. AI makes this achievable without large content teams, at a fraction of the cost.
A brand producing 500 SKUs per season was previously looking at ₹3 to ₹5 lakh in content production costs. With AI, the same output costs under ₹50,000.
3. Buying Briefs and Trend Intelligence
The quality of a buying brief determines the quality of what gets sourced. A vague, inconsistent brief produces vague, inconsistent product. AI enables buying teams to produce standardised, detailed, strategically aligned briefs — consistently, across every buyer, every season.
For a retail chain like the ones I have worked with — operating 100 to 200 stores across Tier 2 and Tier 3 India — a 10% improvement in buying decision quality compounds across millions of units. The financial impact is not marginal. It is transformative.
The Honest Conversation About Jobs
Every technology shift in the history of this industry has raised the same question — and this one deserves an honest answer.
Will AI eliminate jobs in Indian apparel?
It will eliminate certain tasks. The manual, repetitive, language-heavy tasks that consume skilled professionals' time without requiring their judgment. Those tasks will largely be automated within five years.
What it will not eliminate — and cannot — is the expertise that makes those tasks meaningful. The buyer who knows the difference between a dobby weave and a jacquard not just technically, but commercially. The merchandiser who has spent a decade reading Indian consumers across six states. The sourcing head who knows which mill delivers on time and which will need three follow-ups.
That knowledge does not become less valuable when AI arrives. It becomes the irreplaceable input that makes AI output worth anything at all.
The real risk is not that AI replaces experienced professionals. The real risk is that experienced professionals who do not adapt are replaced by less experienced professionals who do.
What Indian Apparel Must Do Now
The industry does not have the luxury of a long adoption curve. AI is not a future consideration — it is already reshaping the competitive landscape globally, and India's apparel exporters and domestic brands are competing against peers in Bangladesh, Vietnam and Turkey who are moving fast.
Three immediate actions matter most.
First, identify the highest-volume writing tasks in your organisation and pilot AI on one of them this season. Measure the time saving. Calculate the cost saving. Build the business case internally.
Second, invest in AI literacy at the merchandiser and buyer level — not just at the leadership level. The organisations that win will be the ones where AI fluency is embedded in the workflow, not bolted on as a leadership initiative.
Third, recognise that India's greatest competitive advantage in global apparel — its depth of human expertise — becomes more valuable, not less, when combined with AI. We have 45 million people in this industry who know things that no algorithm was trained on. That knowledge, amplified by AI, is an extraordinary competitive weapon.
A Final Word
I have spent the last several months writing. Four books — including two motivational books launching on May 10th and a Textile Engineer's Encyclopedia in two volumes scheduled for June 2026.
Writing clarifies thinking. And the clearest thought I have had through this process is this:
The Indian apparel industry has survived partition, liberalisation, the rise of fast fashion, the collapse of Future Group, a global pandemic and the explosion of D2C commerce. It has survived because the people in it are resilient, resourceful and deeply knowledgeable.
AI is not the disruption that breaks this industry.
It is the tool that finally gives this industry's knowledge the scale it deserves.
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CREDITS: Contributed by Rahul Vohra who is a textile engineer and senior retail leader with 27+ years of experience in apparel buying, merchandising and value fashion retail. He is simultaneously launching two motivational books on May 10th — "Conquer Time, Conquer World: The 24-Hour Revolution" and "If This Does Not Motivate You, What Will?" — both available in physical and digital formats from Day 1. His Textile Engineer's Encyclopaedia — two volumes — releases in June 2026.
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