How AI-First Retail Strategies Like Macy's Are Reshaping Ecommerce Video Production

By VEONIB | 2026-07-14

Quick Answer

Retailers adopting an AI-first operating philosophy—exemplified by Macy’s—are embedding intelligence into search, personalization, and operations, creating a blueprint for ecommerce merchants to automate and personalize video production at scale for higher conversion and faster time-to-market.

TL;DR

Table of Contents

According to “Repositioning retail for the AI era” published by MIT Technology Review Insights, legacy retailers like Macy’s are moving beyond flashy AI pilots toward an embedded, AI-first operating philosophy. Senior director of engineering Murali Murugan describes this as redesigning how decisions happen—so every customer experience feels more relevant by default. The article highlights that the biggest transformation is invisible: how products surface in search, how inventory moves, and how engineers ship code faster. For ecommerce merchants, the most actionable takeaway is that the same principles can be applied to video production. Instead of manually producing one-size-fits-all product videos, merchants can adopt an AI-first workflow that generates personalized, optimized videos at machine speed—directly from product URLs. This article unpacks Macy’s strategy and translates it into a practical blueprint for AI-powered ecommerce video creation.

Hero Image Alt Text: AI-first retail transformation concept showing Macy's integration of conversational commerce, personalized recommendations, and automated video production Caption: Retailers like Macy's are embedding AI into every layer of the shopping experience, offering a model for ecommerce video automation. OG Image Title: AI-First Retail Strategy for Ecommerce Video Production | VEONIB Suggested Visual: A split-screen image: left side shows a Macy's storefront with "Ask Macy's" interface, right side shows an automated VEONIB video pipeline from product URL to finished ad.

The Shift from AI Pilots to Integrated Systems

Original Fact: Macy’s has moved from isolated AI experiments to an integrated “AI-first” approach where intelligence is embedded into personalization, search, operational planning, and software development. According to Murali Murugan, “AI first isn’t about adding intelligence on top—it’s about redesigning how decisions happen so the business moves faster and every experience feels more relevant by default.”

Early wins in search recommendations and customer engagement built internal momentum, making scaling “a business decision, not a technology debate anymore.” This mirrors a broader retail trend: compressing the gap between customer signals and business actions.

VEONIB Insight

For ecommerce merchants, the lesson is clear: AI should not be a bolt-on feature but a foundational layer. In video production, this means integrating AI from the product page URL to the finished marketing video. Instead of manually scripting, storyboarding, and editing each video, an AI-first pipeline can ingest a product URL, analyze the product, generate a script, create a storyboard, prompt an image model, and produce a video—all autonomously. Macy’s approach proves that when AI is embedded rather than layered, speed and relevance compound. Merchants who treat video as a batch-production task rather than an on-demand craft will fall behind.

Conversational Commerce and Its Impact on Product Discovery

Original Fact: Macy’s launched Ask Macy’s, an AI-powered shopping assistant that acts like a personal stylist. Customers describe their needs conversationally (e.g., “outfit for a prom”) and receive curated recommendations informed by past purchases, preferences, and context. This represents a shift from keyword search to contextual discovery.

VEONIB Insight

Conversational commerce changes how products are discovered—and therefore how video content must adapt. Product videos that simply list features won’t suffice when customers arrive via a conversational query. Instead, videos need to be context-aware: showing a dress in a prom setting, or a suitcase for a beach vacation. AI video generation tools can produce multiple variations of the same product video tailored to different contexts (formal, casual, travel) without human re-shooting. Macy’s approach suggests that ecommerce video creators should think beyond generic “product highlight” clips and invest in scenario-based video assets that match the conversational intent of modern shopping assistants.

AI as an Invisible Layer for Personalized Shopping

Original Fact: Macy’s sees AI as an invisible layer augmenting human judgment, not replacing it. The long-term vision is retail that feels seamless, adaptive, and personalized—powered by systems customers may never notice. Murugan emphasizes continuous improvement: “learning from mistakes, quickly adapting to newer technology standards, timing, and execution which compound into a meaningfully better customer experience.”

VEONIB Insight

This invisible layer concept is directly translatable to video. The best AI-generated product videos should not feel like “AI videos”—they should feel like natural, high-quality content that just happens to be personalized to the viewer. For merchants, this means using AI to automatically adjust video thumbnails, captions, product highlights, or even call-to-action overlays based on viewer data (past purchases, browsing history, location). The technology runs in the background; the customer only sees relevance. VEONIB’s workflow follows this principle: the AI analyzes the product and audience signals, then generates a video that fits the context—all without the merchant needing to understand prompt engineering.

Implications for Ecommerce Video Generation

Original Fact: The MIT Technology Review article focuses on retail operations, not video. However, the underlying AI-first philosophy applies to any customer-facing content, including video. Macy’s strategy prioritizes speed, personalization, and data-driven decision-making.

VEONIB Insight

Ecommerce video production today still relies heavily on manual workflows: shoot a video, edit it, upload it, A/B test. That’s the equivalent of running a retail search without AI—slow and one-size-fits-all. An AI-first video pipeline can generate hundreds of product videos per day, each optimized for different platforms (Amazon product pages, TikTok Shop, Instagram Reels, YouTube Shorts) and different audience segments. Key capabilities include:

For merchants selling on multiple channels, this reduces time-to-market from days to minutes and eliminates the creative bottleneck.

Comparison: AI-First Retail Video vs. Traditional Video Production

Aspect Traditional Video Production AI-First Video Production (e.g., VEONIB)
Time per video 1-3 days (shoot, edit, render) 5-15 minutes (automated pipeline)
Personalization One video for all audiences Multiple variations per segment
Scalability Requires larger creative team 100+ videos per day from single product feed
Cost per video $500–$5,000+ Fraction of a cent (compute/marginal)
Iteration speed Manual re-editing Re-run pipeline with new parameters
Creative control Full human control (pro) Guided automation with human override (pro)
Platform optimization Manual resize and reformat Automatic aspect ratio and length optimization
Data integration Rarely connected to product analytics Directly uses product URL data, reviews, and sales signals

VEONIB Insight: The AI-first approach does not eliminate human creativity—it automates the repetitive layers so merchants and creators can focus on strategy, branding, and high-impact visual decisions. Macy’s “continuous improvement” philosophy applies here: AI-generated videos should be treated as living assets that improve with each iteration based on performance data.

How VEONIB Enables an AI-First Video Workflow

Original Fact: The source article does not mention video generation. VEONIB provides the analysis from an ecommerce perspective.

VEONIB Insight

VEONIB operationalizes Macy’s AI-first philosophy for video. The workflow mirrors the integrated intelligence Murugan describes:

  1. Product URL input → The AI analyzes the product’s attributes, pricing, reviews, and positioning.
  2. Product Analysis → A structured report highlights unique selling points, target audience, and creative angles.
  3. Script Generation → Multiple script variants are created for different platforms (TikTok, Meta, Amazon).
  4. Storyboard Generation → A visual sequence is planned with scene transitions and camera movements.
  5. Image Prompt Generation → Prompts for image models (e.g., Stable Diffusion, DALL-E) ensure consistent product representation.
  6. Video Prompt Generation → Prompts for video models (e.g., Runway, Pika) to animate the scenes.
  7. AI Video Rendering → The video is generated with lip-sync, motion, and effects.
  8. Voiceover & Subtitles → AI voice and text overlays complete the asset.
  9. Publishing → Direct integration with Shopify, Amazon, TikTok Shop, and other platforms.

This pipeline embodies the “gap between signal and action” that Macy’s prioritizes: a product listing signal directly triggers a video action. For merchants handling hundreds or thousands of SKUs, this is the only way to maintain video coverage at scale.

Recommendations

For Shopify Merchants:

For Amazon Sellers:

For TikTok Shop Sellers:

For Content Marketers and Video Creators:

For SaaS Founders and Developers:

FAQ

How is Macy's AI-first approach different from typical retail AI?
Most retailers add AI on top of existing workflows. Macy’s embeds intelligence into core decision systems—search, personalization, operations—so AI becomes the default, not an add-on.

Can small merchants replicate Macy's AI strategy without a huge budget?
Yes. The principles—embedding AI, automating repetitive tasks, personalizing at scale—are accessible via cloud services and platforms like VEONIB that turn product URLs into videos.

Does AI-generated video replace human creativity?
No. It automates the time-consuming repetitive parts (scripting, rendering, formatting) so humans can focus on strategy, branding, and quality control.

What is the first step to adopting an AI-first video workflow?
Start with a single product feed. Use a tool like VEONIB to generate one video, test its performance against a manually produced video, and then scale based on results.

Which ecommerce platforms benefit most from AI video generation?
Any platform with many SKUs and frequent product updates—Shopify, Amazon, WooCommerce, TikTok Shop—benefits because video coverage can be maintained automatically.

How does conversational commerce influence video content?
Customers arriving from conversational queries expect context. Videos should reflect the scenario (e.g., “wedding guest dress”) rather than generic product features.

References

Sources

Try VEONIB

VEONIB automatically transforms any product URL into a complete asset package—product analysis, video script, storyboard, image prompts, video prompts, and a finished AI marketing video—ready for ecommerce platforms. Visit VEONIB to integrate AI-first video production into your store today.

Credibility Assessment

The core factual information—Macy’s AI-first approach, Ask Macy’s conversational assistant, the shift from pilots to integrated systems, and quotes from Murali Murugan—comes directly from the MIT Technology Review Insights article. That article is a sponsored content piece produced in partnership with Infosys, which means the editorial independence is limited; however, the strategic insights are based on actual Macy’s engineering practices. VEONIB’s analysis about applying these principles to ecommerce video generation is original interpretation, not sourced from the article. Uncertainties include the measurable impact of Ask Macy’s on conversion rates, which the source does not disclose. Recommendations for video workflows are derived from VEONIB’s experience and should be validated per merchant.