PLAYBOOK ATLASPlaybook Atlas

Consumer

AI in consumer: explore 40 applications.

Use product and customer evidence to improve a specific product, launch or service decision.

Explore customer-feedback analysis, product information, demand planning and consumer-experience workflows for product and operations teams.

Plan your first AI move See the 40 applications

Where the 40 applications sit

Explore the domains
  1. 14Personal Care & Beauty
  2. 9Supply Chain Management
  3. 6Customer Engagement
  4. 6Product Development
  5. 5Market Research

01Why AI now

Why consumer is moving on AI, in three figures.

Each figure links to its source.

  1. CPG AI adoption: 71% in 2024

    In McKinsey's 2024 survey of 63 CPG leaders, 71% had adopted AI in at least one business function, up from 42% in 2023.

    Source: McKinsey & Company

  2. AI forecasting saved more than $40M

    BCG reports that one global FMCG company used AI demand forecasting to save more than $40 million by avoiding write-offs and other inefficiencies.

    Source: Boston Consulting Group

  3. AI agents: 92% plan deployment within a year

    Deloitte's 2026 survey of 300 consumer products executives found 92% were likely to deploy AI agents or autonomous systems for key functions within 12 months.

    Source: Deloitte

How to evaluate a first project

Pick a product, channel and responsible owner. Tie feedback themes to source comments and approved product facts, then test a concrete change. Keep missing specifications and unsupported product claims visible; sentiment summaries and modeled demand need separate checks before they influence a launch or investment.

02Capability map

Where consumer puts AI to work, domain by domain.

Pick a domain to see its applications. Each one opens a full report.

Inside Personal Care & Beauty

Applications in Personal Care & Beauty

What the use cases ask AI to do

Share of the consumer use cases, by the kind of work the AI does.

  1. Reasoning

    Analyzes, predicts and decides: scoring, forecasting, classifying.

    64%

  2. Generation

    Creates: text, images, code and other content.

    36%

Under 1% each: perception, optimization and agentic.

03Workflow ideas

Ways AI could change the work, in consumer.

Atlas groups these applications by the changes they propose to a workflow. These preliminary classifications help you explore ideas; each application still needs a review of its sources and operating requirements.

Workflow categories in this catalog

Share of the 35 applications assigned a category.

How to evaluate an application

  1. Start with a bounded task

    Identify the inputs, the person responsible, and the decision or output the workflow must produce.

  2. Check the support for each method

    Look for source-backed details about the specific implementation, including its limits and human review.

  3. Measure the pilot

    Record the current baseline, agree on acceptance criteria, and test on representative cases before expanding.

Explore applications

04What gets built

The approaches consumer uses most, and when to skip them.

Knowing when not to use one matters as much as knowing when to.

  1. 01 · 7 applications

    Generative AI

    Models that learn data distributions to generate new text, images, code, and media.

    Use it when

    • When you need to generate natural language, code, or media that would be expensive or slow for humans to produce manually.
    • When tasks involve ambiguity, open-ended questions, or creative exploration rather than strict right-or-wrong answers.
    • When you can ground the model on reliable internal or external data sources to improve factuality.

    Skip it when

    • When the task requires strict determinism, formal guarantees, or regulatory-grade traceability (e.g., certain financial calculations, safety-critical control systems) without a robust verification layer.
    • When you lack access to high-quality, authoritative data or subject-matter expertise to validate outputs in a high-risk domain.
    • When a simple rules engine, search, or template-based system can solve the problem more reliably and cheaply.
    Generative AI, in depth

  2. 02 · 6 applications

    AutoML-Platform

    Managed platform for training and operating predictive models quickly.

    AutoML-Platform, in depth

  3. 03 · 5 applications

    RecSys

    AI pattern for predicting and ranking items a user is likely to prefer.

    Use it when

    • You have a large or growing catalog of items (products, content, ads, jobs, etc.) and users struggle to manually discover relevant options.
    • You can reliably log user interactions with items (views, clicks, purchases, likes, completions) and maintain a stable user/item identity.
    • Personalization or relevance is a key driver of business value (engagement, revenue, retention, satisfaction).

    Skip it when

    • Your catalog is very small or static, and users can easily browse all options without assistance.
    • You lack sufficient interaction data or cannot reliably track user behavior due to privacy, technical, or regulatory constraints.
    • User identity is highly transient or anonymous, and you cannot build meaningful histories or segments.
    RecSys, in depth

05The applications

40 consumer applications, each with a full report.

The widest first, by the number of use cases each covers. Every report shows what changed, how it works, who has done it and what can go wrong.

  1. Customer Sentiment AnalysisCustomer Sentiment Analysis is the systematic extraction of emotional tone and opinions from unstructured customer feedback—such as product reviews, support conversations, social media posts, and complaints—and converting it into structured, actionable insight. Instead of manually reading thousands of comments, organizations use models that classify sentiment (e.g., positive, negative, neutral, or more granular emotions) and often tie these attitudes to specific products, features, or issues. This application matters because consumer-facing businesses are overwhelmed by the volume, speed, and multilingual nature of modern feedback channels. Automated sentiment analysis enables real-time monitoring of satisfaction, early detection of emerging problems, and richer understanding of what drives loyalty or churn. The output informs product roadmaps, merchandising decisions, marketing messaging, and customer service priorities, turning raw text into a continuous “voice of the customer” signal at scale.Batch → RT29 use cases
  2. Consumer Feedback Sentiment IntelligenceAI models ingest reviews, chats, social posts, and survey responses to classify consumer sentiment by polarity, intensity, topic, and aspect across products and services. These insights power smarter segmentation, real‑time satisfaction monitoring, and product/experience improvements that increase conversion, loyalty, and lifetime value.Batch → RT25 use cases
  3. Consumer Review Sentiment IntelligenceTurn permitted customer-review data into a product issue queue with supporting excerpts. Distinguish the aspect discussed, sentiment, product version and source channel so product and service teams can investigate recurring complaints. Review sentiment is a signal from reviewers, not a representative satisfaction survey or proof of business impact.Speech-NLP22 use cases
  4. Seasonal Demand Intelligence for Consumer GoodsThis AI solution uses AI to detect, forecast, and act on seasonal shifts in consumer demand across retail, CPG, and ecommerce. It fuses sales, images, logistics, and external signals to optimize forecasting, inventory, and market expansion decisions, reducing stockouts and overstocks while improving promo and product launch ROI.React → Pred12 use cases
  5. BeautyFlow AI - Onsite Search and Support OptimizationAI optimization suite for beauty ecommerce that personalizes search and homepages, measures recommendation impact, surfaces search behavior insights, automates onboarding and support routing, and improves retention through behavior-based re-engagement and experimentation.Expert → Platform8 use cases
  6. SkinSignalReal-time skincare recommendation engine that re-ranks products during active sessions using live consumer behavior signals to keep suggestions aligned with current intent.Expert → AI8 use cases
All 40 applications, A to Z

Work with us

The catalog shows what is possible. A sprint decides what you should fund.

Reading every report still leaves the hardest question open: which move is worth funding first, here, given your constraints. That is the sprint: two weeks, fixed scope, and a candid answer either way.

Book a 30-minute callHow the sprint works

Two weeks Fixed scope A candid fit-or-no-fit answer

  1. 01

    Three ranked opportunities

    A decision-ready shortlist scored against value, feasibility, evidence, risk, and time to proof.

  2. 02

    One pilot-ready workflow

    A bounded operating design with actors, handoffs, data needs, controls, and success measures.

  3. 03

    A defensible 90-day plan

    Build-versus-buy guidance, ROI assumptions, risk treatment, sequencing, and executive decisions.

06Rules & standards

Rules and standards to check, with their scope and sources.

Selected US and EU references for these workflows. Applicability depends on jurisdiction, organization, data and intended use. The planning notes are Atlas editorial guidance; they are not official implementation-time estimates or an exhaustive list of obligations.

  1. Truthful advertising and substantiated claims

    Law or regulation

    United States · FTC jurisdiction

    Advertising claims must be truthful, non-deceptive and supported by evidence. These principles also matter when AI drafts product descriptions, recommendations or campaign copy.

    FTC: Truth in Advertising

    Source checked

    Project planning note

    Keep product claims tied to approved specifications and evidence, including claims generated from customer feedback.

  2. COPPA · children’s online privacy

    Law or regulation

    United States · covered online services involving children under 13

    COPPA covers child-directed commercial services and certain operators with actual knowledge that they collect children’s personal information. Check the amended Rule, parental-consent requirements and applicable exceptions for the actual service.

    FTC: Complying with COPPA

    Source checked

    Project planning note

    For connected toys or child-directed services, determine age-related scope before collecting voice, image or account data.

Your next step

Find your first move in consumer.

Ask the workspace which move fits your company. Add your size, systems and constraints, and it works from these 40 applications to a plan your team can act on.

Plan your first AI move

Rather talk it through? Book a 30-minute call