PLAYBOOK ATLASPlaybook Atlas

Marketing

AI in marketing: explore 28 applications.

Connect audience insights, campaign work and measurement to a clear marketing decision.

Explore segmentation, content production, experimentation and budget planning, with the evidence behind each recommendation visible.

Plan your first AI move See the 28 applications

Where the 28 applications sit

Explore the domains
  1. 15Campaign Management
  2. 7Customer Engagement
  3. 7Market Research and Analysis
  4. 5Brand Management
  5. 3Sales Support

01Why AI now

Why marketing is moving on AI, in three figures.

Each figure links to its source.

  1. AI adoption: 75% of all marketers

    Salesforce says 75% of marketers were experimenting with or had fully implemented AI in 2024.

    Source: Salesforce

  2. Personalization: typical 10–15% revenue lift

    McKinsey says personalization most often produces a 10% to 15% revenue lift, with results ranging from 5% to 25% depending on the company.

    Source: McKinsey & Company

  3. 64% of CMOs lack budget to execute strategy

    Gartner’s 2024 survey of 395 marketing leaders found that 64% lacked the budget needed to execute their marketing strategy.

    Source: Gartner

How to evaluate a first project

Choose one decision and define the outcome before analyzing or generating content. Keep attribution reports, forecasts and causal experiments distinct. Review audience eligibility, product facts and measurement assumptions, then test a bounded change against a suitable baseline before expanding it.

02Capability map

Where marketing puts AI to work, domain by domain.

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

Inside Campaign Management

Applications in Campaign Management

What the use cases ask AI to do

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

  1. Reasoning

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

    61%

  2. Generation

    Creates: text, images, code and other content.

    33%

  3. Agentic

    Acts: plans, uses tools and completes multi-step tasks.

    6%

Under 1% each: perception and optimization.

03Workflow ideas

Ways AI could change the work, in marketing.

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 23 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 marketing uses most, and when to skip them.

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

  1. 01 · 12 applications

    API-Wrapper

    Thin application layer over a managed AI API.

    API-Wrapper, in depth

  2. 02 · 5 applications

    Workflow Automation

    Use AI inside orchestrated workflows to automate multi-step business processes.

    Use it when

    • When you have repetitive, rule-heavy workflows that still require human judgment or document understanding.
    • When the process spans multiple systems (ERP, CRM, ticketing, email) and manual coordination is slow or error-prone.
    • When large volumes of semi-structured or unstructured data (emails, PDFs, forms) must be processed consistently.

    Skip it when

    • When the process is highly creative, exploratory, or non-repeatable, with no stable sequence of steps.
    • When decisions are extremely high-stakes (e.g., life-critical medical decisions, major legal judgments) and regulations require full human control.
    • When you lack reliable access to the necessary systems or data sources to complete the workflow end-to-end.
    Workflow Automation, in depth

  3. 03 · 3 applications

    Predictive Analytics Solutions

    Business-facing predictive analytics family label.

    Predictive Analytics Solutions, in depth

05The applications

28 marketing 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 Segmentation and Personalization HubThis AI solution uses machine learning to profile customer behavior and dynamically segment audiences across channels. By powering hyper-personalized journeys, targeting, and experimentation, it boosts campaign relevance, increases conversion and lifetime value, and reduces wasted marketing spend.Silo → Int25 use cases
  2. Multi-Touch Attribution OptimizerThis application area focuses on accurately measuring the contribution of each marketing channel, campaign, and touchpoint to conversions and revenue, then using those insights to optimize spend. Instead of simplistic rules like last-click attribution, these systems analyze the full multi-touch customer journey across platforms and devices to assign fair, data-driven credit. They integrate data from ad platforms, analytics tools, and CRM systems to produce an objective view of what is truly driving incremental impact. AI and advanced analytics play a central role by modeling complex customer paths, estimating incremental lift, and continuously updating attribution weights as performance changes. The output directly informs budget allocation, bid strategies, and channel mix decisions, allowing marketers to reallocate spend from low-impact activities to the campaigns and touchpoints that demonstrably drive revenue. This improves marketing ROI, reduces wasted ad spend, and strengthens marketers’ ability to prove and defend the impact of their investments to business stakeholders.Opaque → Trans15 use cases
  3. Generative Marketing Content StudioAI Marketing Content Studio uses generative models to plan, create, and optimize marketing copy and assets across channels—email, social, ads, blogs, and more. It helps teams move from brief to publish-ready content in minutes, enabling higher output, tighter brand consistency, and always-on experimentation without proportional increases in headcount or agency spend.Human Creative → Augmented12 use cases
  4. Real-Time Marketing Personalization EngineThis AI solution uses AI to personalize marketing interactions across channels, from email to digital campaigns, in real time. By predicting consumer behavior and tailoring content, timing, and offers at the individual level, it increases engagement, conversion rates, and overall marketing ROI while automating execution at scale.Batch → RT8 use cases
  5. Customer Segment Discovery EngineThis application focuses on systematically grouping customers into distinct segments based on their behaviors, value, needs, and characteristics so that marketing teams can tailor campaigns, offers, and lifecycle programs to each group. Instead of relying on static, manual rules like age or location, it uses large volumes of transactional, behavioral, and engagement data to continuously refine who belongs in which segment and why. AI is used to automatically discover patterns in customer data, identify high-value or high-churn-risk groups, and keep segments up to date as customer behavior changes. This enables more precise targeting, personalized messaging, and better allocation of marketing budgets—ultimately increasing conversion rates, customer lifetime value, and campaign ROI while reducing wasted ad spend and manual effort.Computer Vision7 use cases
  6. Digital Marketing Strategy OptimizerMarketing Strategy Optimization is the systematic use of data and advanced analytics to design, execute, and continuously refine digital marketing strategies. Rather than relying on manual analysis, intuition, or one‑off experiments, this application area uses predictive models and automated insights to determine which audiences to target, what messages to deliver, which channels to use, and how to allocate budgets across campaigns. It matters because marketing spend is one of the largest, least efficient line items in many organizations, with significant waste from broad targeting, non‑personalized messaging, and slow reaction to performance data. By turning fragmented marketing data into actionable strategy recommendations, this application improves targeting precision, personalization at scale, and real‑time optimization of campaigns. The result is higher conversion rates and ROI, while reducing manual effort in planning, analysis, and reporting.Expert → AI5 use cases
All 28 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

    Require evidence for generated benefit claims and review endorsements and disclosures in their actual context.

  2. CAN-SPAM · commercial email

    Law or regulation

    United States · covered commercial email

    Commercial email must meet requirements including accurate sender information, non-deceptive subjects and a working opt-out. US CAN-SPAM and European consent rules should not be treated as interchangeable.

    FTC: CAN-SPAM Act compliance guide

    Source checked

    Project planning note

    Test sender identity, message classification, unsubscribe handling and suppression across the sending workflow.

Your next step

Find your first move in marketing.

Ask the workspace which move fits your company. Add your size, systems and constraints, and it works from these 28 applications to a plan your team can act on.

Plan your first AI move

Rather talk it through? Book a 30-minute call