Palantir and Stagwell launch AI platform to put data-driven marketing in the hands of local teams
Palantir and Stagwell Inc. have partnered on an AI-powered marketing platform that blends Palantir's Foundry, Code and Theory's orchestration software, and Stagwell's The Marketing Cloud data and solutions. The goal: give large, complex organizations a way to plan, execute, and measure campaigns at scale-without bottlenecking on centralized teams.
Mark Penn, Stagwell's chairman and CEO, said the idea emerged from conversations with Palantir CEO Alex Karp about building an AI-enabled marketing suite that actually makes decisions and launches campaigns. As Penn put it, the aim is simple: "Give me those people who you think will buy an umbrella on the next rainy day," then have the system identify the audience and run the play.
Why this matters for marketers
- Moves AI from deckware to daily use: Store managers, regional leads, and brand teams can ask questions in plain English and get back target audiences they can activate.
- Cuts build time for custom tools: Palantir says new AI capabilities mean teams with domain expertise can ship working workflows faster, with less traditional coding.
- Supports complex orgs: Built for enterprise-scale data and governance, so local teams can move quickly without breaking central standards.
How it works (at a glance)
The platform layers Palantir's data engine with Stagwell's marketing apps and orchestration. Foundry provides the connective tissue across first-party, third-party, and channel data so marketers can ask natural-language questions and get actionable segments.
According to Palantir's Kevin Kawasaki, the key shift is speed. Teams can "wrap the technology around the human" to sharpen decision-making and execute faster-far beyond the pace of traditional custom software timelines.
If you've experimented with AI copilots inside analytics or ads tools, this goes further: it's built to sit across the stack and operationalize decisions, not just summarize dashboards.
What you can ask the system to do
- Identify and size an audience based on behavior, context, and likelihood to act (e.g., "Who's likely to book a weekday stay next month within 10 miles of our new location?").
- Recommend channels and budget split for a local push based on historical lift and inventory.
- Launch and monitor campaigns with pre-built guardrails, then auto-adjust spend against performance targets.
- Standardize reporting so local managers see what matters and HQ sees the roll-up without rework.
Data, privacy, and control
Stagwell says the platform includes differential privacy techniques to protect user data while enabling precise audience building. That matters if you're working with sensitive first-party data, varied regional laws, and multiple partners.
Crucially, this isn't a black-box managed service. Penn emphasized that customers can operate the platform inside their own org, with their own data policies, instead of relying solely on an external team to run campaigns.
What this means if you run marketing
- Shift campaign ops closer to the edge: Equip local managers to self-serve targeting and activation with standard playbooks and shared data.
- Treat first-party data readiness as a priority: Map what you have, what you can actually use, and what's missing (consent, cleanliness, identity resolution).
- Define the questions that matter: Draft 10-20 high-utility prompts your teams ask weekly (e.g., "Which cohort is decaying fastest?" "Where is incrementality strongest?") and bake them in.
- Pilot, then templatize: Start with one region or line of business; once the workflow proves out, turn it into a reusable template for others.
- Set governance upfront: Decide who can launch what, set spend caps, and standardize measurement so you can compare performance across markets.
Who benefits most
- Retail and multi-location brands needing local activation with centralized oversight.
- Hospitality, QSR, and franchise systems juggling seasonal demand and regional nuances.
- Enterprises with strong first-party data that want faster time-to-market without adding headcount.
Early rollout and availability
Stagwell has begun a soft rollout with an initial focus on retail clients and plans to expand on an opt-in basis to its broader network. Expect variability by client: Kawasaki noted that two companies in the same category could receive materially different setups based on how they work with data, teams, and channels.
Bottom line
This partnership is about speed, control, and scale. If your teams spend more time wrangling data and requests than launching campaigns, an AI-first operating layer like this is worth a look-especially if you need local execution without losing central standards.
Next steps for your team
- Audit your first-party data and consent posture.
- List the top decisions you'd automate tomorrow if you could.
- Pick a single market or product line to pilot.
- Define success metrics that prove incrementality, not just clicks.
If you want to understand what a data backbone like this looks like under the hood, explore Palantir Foundry's approach to unifying data and operations here: Palantir Foundry.
For marketers building AI skills to lead these rollouts, this certification is a solid starting point: AI Certification for Marketing Specialists.
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