New-age companies deploy AI across operations

According to reporting by Economic Times CIO, listed Indian "new-age" companies are deploying AI across everyday operating functions to cut costs and improve scale. The article cites Delhivery as having deployed "large language models and multimodal AI" across voice, vision, location intelligence and real-time transaction processing, and says the company told investors on an earnings call that AI has reduced documentation, improved customer communication and made claims handling more efficient. Economic Times CIO also reports that Nykaa has built an online experience including an AI-powered skin scan and personalised app discovery. The coverage frames AI use cases across logistics, customer support, discovery, marketing and store productivity.
What happened
According to Economic Times CIO, listed Indian new-age companies are expanding AI beyond product features into core operating functions. The article reports that Delhivery "has deployed large language models and multimodal AI across voice, vision, location intelligence and real-time transaction processing," and that the company told investors on an earnings call that AI is being used across order manifestation, mid-mile, last-mile and post-delivery processes. The same reporting says the company's management stated AI has reduced documentation, improved customer communication and made claims handling more efficient, and that it had trimmed teams earlier handling claims and parts of customer service without a material increase in technology team size or inference costs. Economic Times CIO also reports that Nykaa has built an online experience with an AI-powered skin scan to identify skin concerns and recommend products, and that AI is being used to personalise app discovery and improve conversion.
Technical details
The reporting describes deployments in two broad technical areas: first, logistics and fulfillment where the article attributes use of large language models and multimodal AI for voice, vision, location intelligence and real-time transaction processing; second, consumer-facing experiences where computer-vision driven skin-scans and personalization models are used to drive discovery and conversion. The article does not name specific model families or vendors.
Industry context
Industry context: Companies applying AI to operations commonly target cost-to-serve reductions, routing and delivery optimization, automated customer triage, and personalized discovery to raise conversion. Observed patterns in comparable deployments include a mix of inference at the edge (voice/vision at store or device) and centralized real-time processing for routing and claims, which typically increases reliance on monitoring, data quality, and latency controls.
What to watch
For observers, the article highlights three measurable indicators: reported reductions in manual handling and failed deliveries, changes in operating costs tied to inference, and metrics linking AI-powered discovery to conversion lift. Economic Times CIO does not provide independent performance numbers; the reporting relies on company disclosures and earnings-call remarks.
Takeaway
The coverage documents a shift toward using AI as an operational lever across logistics and customer-facing workflows among listed new-age firms in India, per Economic Times CIO reporting. Industry stakeholders should track deployment scale, monitoring practices, and end-to-end performance metrics as these systems move from pilots into everyday operations.
Scoring Rationale
This is a notable industry story: multiple listed companies moving AI into operations affects practitioners managing production ML systems, data pipelines, and inference economics. It is not a frontier model release, so its impact is significant but not transformative.
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