You can’t build your annual marketing plan on best guesses and past performance data alone. Markets shift mid-quarter. Channels get more expensive overnight. You need a way to plan faster, adapt smarter, and defend every budget decision with data.
The solution: artificial intelligence and machine learning. This trend reflects the usage of AI in marketing across organizations. According to Salesforce, 75% of marketers are already either experimenting with or actively using AI in their operations.
AI turns marketing planning from a static document into a living system: one that models outcomes and surfaces blind spots. No more waiting until Q3 to realize a channel underdelivered.
In this article, you’ll learn how to build an AI marketing plan that gives you speed, accuracy, and control, plus the tools that power it.
Key highlights:
- An AI marketing plan uses predictive models and performance data to forecast ROI, simulate budget scenarios, and identify channel saturation points.
- Core components of an AI marketing strategy include: ROI forecasts by channel, scenario-based plans, marginal return curves, reallocation logic, and measurement frameworks tied to financial outcomes.
- Effective implementation of AI in marketing requires clean input ownership, alignment with finance on assumptions and revenue targets, and marketers trained in AI fluency and model interpretation.
- Keen’s MMM platform powers your entire planning system, from forecasting and scenario modeling to incrementality measurement.
Before we dive deep into the AI marketing concepts, here’s a quick overview of AI marketing planning tools to support your planning process.
| Marketing function | AI marketing tool | What the tool does |
| Marketing planning and forecasting | Keen | Models ROI by channel, simulates scenarios, and sets marginal return thresholds |
| Customer insights and segmentation | 6sense | Scores account intent, prioritizes segments, and syncs audiences for media planning |
| Retargeting and cross-channel media ads | AdRoll | Automates display, social, and email retargeting with AI-powered bidding and cross-channel attribution |
| Campaign orchestration and automation | Iterable | Builds behavior-triggered journeys across email, SMS, and mobile |
| Media optimization and bidding | Madgicx | Uses AI to test and optimize paid campaign performance across platforms |
| Measurement and performance modeling | Keen | Tracks marketing incrementality, calculates iROAS, informs reallocation and future plans |
What is an AI marketing plan?
An AI marketing plan is a strategy that uses machine learning, predictive models, and automation to plan, execute, and optimize marketing more effectively.
The goal of using AI isn’t to replace your marketing instincts. Instead, it helps you use data to guide your decisions before you make the investments.
Read more: The evolution of data-driven marketing
What are AI marketing planning tools?
AI marketing planning tools are software that use artificial intelligence to automate tasks, predict outcomes, and support decision-making across the marketing workflow. They’re designed to take in data from across campaigns and platforms to give you actionable insights.
AI marketing tools are used for:
- Forecasting sales and campaign performance
- Personalizing customer journeys
- Generating content at scale, be it for email marketing or content marketing
- Optimizing media spend in real time
- Cross-media measurement (not just last-click attribution)
Why do you need to use AI for marketing planning?
When you use AI for marketing planning, the benefits go beyond saved time. You get a more accurate way to create strategies based on modeled outcomes and real-time signals. It lets you leverage agile marketing and build a system that updates as your budget or channel performance shifts. AI improves the way you plan by helping you:
- Model marketing ROI before you commit budget: Simulate how different investments will perform before you launch any campaign. Using AI, you can test media mix changes, flighting strategies, or regional allocations and see projected iROAS based on historical and modeled data. That means fewer risky bets and more defensible budgets.
- Stress-test scenarios instead of picking one marketing plan: Model multiple scenarios so you’re not stuck choosing one plan. For example, “What if paid search gets 20% more?” or “What happens if CPMs spike in Q3?”) and see how those shifts affect revenue and marketing efficiency ratios—instantly.
- Replace manual marketing budget allocation with predictive inputs: Automate time-consuming steps like gathering performance data, calculating efficiency by channel, or estimating saturation curves. AI speeds up annual planning cycles and reduces the margin of error in every spreadsheet or presentation.
- Adapt your ad flighting strategy when the market changes: Respond faster when an important marketing KPI spikes or the performance drops. Instead of waiting for end-of-quarter reporting, you can use real-time signals to adjust your budget, protecting your ROI without rebuilding the entire media plan.
- Connect planning and measurement in one system: Close the loop between planning and execution with AI. With advanced modeling techniques like Bayesian MMM, your forecasts update based on actual results, so next quarter’s plan is smarter, without starting from scratch.
What to include in your AI-generated marketing plan
An AI-generated marketing plan is built on live inputs, predictive modeling, and performance loops. Every component should help your team make faster, better decisions throughout the year. Your AI-generated marketing plan should include:
1. Marketing investment forecasts by channel
Replace top-down budgets with bottom-up ROI projections. Use AI models trained on past performance and market data to estimate returns at different spend levels across each tactic. For example, Keen’s marketing elasticity engine (MEE) is built on decades of marketing data to support accurate forecasts:
2. Saturation curves and marginal return breakpoints
Your plan should take into account mROI or the point of diminishing returns for each channel. Use this information to set upper limits on spend and avoid overspending on tactics that are already tapped out. Here’s how Keen platform breaks it down in an easy-to-understand view:
3. Scenario models tied to business outcomes
Include multiple versions of your plan: one for baseline growth, one for aggressive investment, and one for budget risk. AI tools like Keen let you model revenue, efficiency, and iROAS across each version.
Read more: Introduction to scenario-based marketing planning
4. Live data input dependencies
Define which data sources will feed your plan throughout the year: media platforms, CRM, media attribution tools, MMM models, and more. This is how your AI system learns and improves.
5. Marketing performance thresholds and auto-adjust rules
Don’t just define your marketing goals and objectives. Define what happens if performance falls short. For example, if your performance marketing KPI drops below a certain percentage, the system should trigger a reallocation scenario.
Best AI tools for marketing planning to start with (by function)
You don’t need to rebuild your tech stack to get started with AI. The right tools layered into your existing workflow can unlock better forecasting, faster planning, and more accurate performance measurement. Use the following AI tools for marketing planning, from strategy to execution.
1. For demand forecasting: Keen
Use Keen’s MMM platform to model ROI by channel, forecast marginal returns, and run scenario-based plans. The platform turns historical and live data into media investment recommendations, giving you the numbers to support every budget ask.
Keen’s AI marketing plan generator can work based on your business goals, revenue targets, and more.
2. For customer insights and segmentation: 6sense
Use 6sense to tap into intent signals and predictive account scoring to prioritize where and when to engage. Sync these high-fit audiences with your planning models in Keen to allocate media more effectively.
3. For retargeting and cross-channel ad automation: AdRoll
AdRoll adjusts your bids and campaign timing based on user behavior, unifying your cross-channel marketing efforts under one platform. You can easily feed AdRoll’s performance data with MMM tools like Keen to further forecast with complete visibility into retargeting’s contribution to the overall media efficiency.
Read more: The ultimate guide to cross-channel optimization
4. For campaign personalization: Klaviyo
Klaviyo builds AI-personalized journeys across email, SMS, and mobile. Pair campaign performance data with Keen to understand cross-channel contribution and reallocate based on outcomes.
5. For measurement and performance modeling: Keen
Keen’s marketing measurement solution goes beyond platform attribution. Measure true financial impact using incrementality, iROAS, and media elasticity, so you can optimize based on what’s actually driving results.
How to use AI to create a marketing plan
AI tools won’t deliver results unless your workflows are set up to support them. To have a successful AI change management process, follow these steps:
- Assign a single owner for model inputs: Predictive analytics rely on clean, consistent data, from media spend, performance, goals, to campaign metadata. If no one owns the inputs, accuracy breaks down. Assign a marketing ops or analytics lead to manage what goes into the model and ensure updates happen consistently.
- Use model assumptions to align marketing with finance: When you use AI to plan with metrics like iROAS or marginal return, your assumptions matter. Transparent assumptions help the finance team justify your budget. If your revenue goals can’t be met with the proposed spend, the model makes that visible up front.
- Know when to challenge the AI model: AI doesn’t replace your judgment. It supports it. Models like Keen’s are trustworthy, built with a low margin of error, and are easy to interpret. But your team should still pressure-test the outputs. If the forecast looks off or market conditions shift, you need people who can ask the right questions and make smart overrides.
- Build new AI fluency skillsets: Working with AI means more than using a tool. Your team needs to know how to read model outputs, explain performance shifts clearly, and run experiments that feed the next planning cycle. You’ll need to train your team to trust the system gradually and shift from manual workflows to model-driven decision-making.
Build AI-powered marketing campaigns with Keen
Planning isn’t hard because you don’t know what to do. It’s hard because you’re making high-stakes decisions under pressure. Decision fatigue, internal pushback, constant scrutiny, and no room for error. That’s the real weight behind your annual plan.
This is where Keen’s real value lies, providing you relief through clarity and control. With our annual planning platform, you can:
- Predict what each channel will return before you spend
- Stress-test multiple plans against real revenue targets
- Catch budget inefficiencies before the finance team does
- Prove your strategy with metrics that actually hold up under pressure, like iROAS and incrementality
Start with the part of your plan that keeps you up at night. Keen gives you the insight and confidence to own it.
Request a demo to see how you can use Keen’s AI marketing planning solution.
