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Exclusive Forrester Report on AI in Marketing
Why it matters:
AI has already made marketers more capable. What defines the next stage is coordination. For the Positionless Marketer, success is no longer about optimizing individual campaigns, but about orchestrating a system where every decision across journeys, offers, content, and timing works toward a shared goal. AI Decisioning Studio makes that possible by bringing four core AI agents into one coordinated environment. The result is not just better performance in each layer, but a compounding effect across all of them. That is what unlocks true Optimization Power: not isolated improvements, but connected decisions that drive measurable impact.
Key takeaways:
AI is one key to making the Positionless Marketer possible. It gives marketers the power to do more across strategy, orchestration, creative, and optimization, without relying on constant handoffs.
But as AI increasingly becomes embedded across marketing, a new challenge emerges: coordination and management of automated capabilities.
Marketers today may already have AI optimizing journeys, offers, content, and timing. But when those decisions happen in isolation, they still need to be stitched together manually. The result is not a connected system, but a collection of local optimizations.
And that defeats the promise of the Positionless Marketer.
The empowerment of Positionless Marketing is realized when those decisions work in harmony.
That is what AI Decisioning Studio enables. It brings together four core AI decisioning agents into one environment, so marketers have the power to coordinate decisions across journeys, offers, channels, content, and timing around a shared strategic goal.
This is Optimization Power at a new level. Not just smarter decisions, but smarter decisions working together.
See full talk on Optimove's AI Agents here.
Optimove’s AI capabilities have already been helping marketers improve specific parts of campaign performance. What is advanced by AI Decisioning Studio is that these capabilities come together.
Instead of operating across separate workflows, four core AI agents now work within a single strategy-led system. Marketers can activate them, monitor them, and align them to a shared goal.
The impact is not just better performance in each layer. It is that those improvements compound.
A better journey decision creates the right context for a better offer.
A better offer, channel, or message variation increases relevance.
A more relevant message performs better when delivered at the right time.
This is where decisioning becomes optimized.
AI Decisioning Studio currently brings together four core Optimove AI agents, each responsible for a different layer of decisioning. Together, they form a connected system for campaign execution.
Each agent focuses on a different decision:
| AI Agent | What it Decides | Scope of Optimization |
| AI Journey Decisioning Agent | What campaign should happen next | Across all eligible campaigns |
| AI Offer Decisioning Agent | Which offer, channel, or template variation to use | Within a campaign |
| AI Content Decisioning Agent | How the message should be presented | Content-level (e.g. subject lines) |
| Send Time Optimization Agent | When the message should be delivered | Per customer timing |
This is the orchestration layer.
The AI Journey Decisioning Agent determines the next best campaign for each customer across all eligible recurring campaigns. Instead of optimizing within a single campaign, it evaluates all available options, predicts the future value of each, and selects the one most likely to drive long-term impact.
Within AI Decisioning Studio, the AI Journey Decisioning Agent is the top layer of coordinated decisioning, ensuring that what happens next is aligned with the marketer’s broader strategy, not just the rules of an individual campaign.
Once the next campaign is selected, the AI Offer Decisioning Agent determines which variation each customer should receive. That can include the offer itself, the channel, and the template variation.
Using Optimove’s Customer DNA, including lifecycle stage, segmentation layers, and behavior-based micro-segments, it understands how different audiences respond to different actions.
It compares each action against a control group, measures both response and business impact, and calculates the incremental value each variation creates. Based on those analyzed insights, it gradually shifts more customers toward the combinations that perform best.
Rather than declaring one global winner, the agent continuously adapts. Different customer groups can receive different combinations of offer, channel, and message based on what is most effective for them.
The AI Content Decisioning Agent selects the right message targeting to each customer. It finds the content variation most likely to engage each customer and improves over time based on real performance data. Marketers can add multiple subject line variations, whether written manually or generated with GenAI, and the system is continuously learning from engagement signals to shift more sends toward higher-performing options.
In practice, this removes the need for manual testing cycles and turns content optimization into an always-on process running in the background. Teams using AI agents for content report 68% shorter content creation timelines (Demand Gen Report, 2025), and this agent takes the cycle further by eliminating the wait-and-measure loop entirely.
Timing is the final decision layer.
The Send Time Optimization Agent identifies the optimal moment to engage each customer based on their individual behavior patterns and historical engagement signals. Instead of assigning a fixed send time, marketers define a send window, and the system determines the best delivery time for each individual within that window.
This ensures that each message is delivered when the customer is most likely to engage, maximizing the effectiveness of the journey, offer, and content decisions that precede it.
Each of these agents improves performance on its own. The real power is realized because they work as a highly coordinated system.
The AI Journey Decisioning Agent identifies the next best campaign. That decision creates context for the AI Offer Decisioning Agent to determine the best offer, channel, or template variation. That, in turn, shapes how the AI Content Decisioning Agent presents the message. And all of it becomes more effective when the Send Time Optimization Agent delivers it at the moment each customer is most likely to engage.
This is the difference between optimization and decisioning. Optimization improves one thing in isolation. Decisioning improves a series of connected things. Gartner projects that 40% of enterprise applications will embed AI agents by the end of 2026, up from less than 5% in 2025. The question is no longer whether marketers will adopt AI agents. It is whether those agents are working together, or running amuck in parallel without coordination.
Most marketing AI tools still treat these decision layers separately. AI Decisioning Studio closes that gap by bringing them into one coordinated system, where every decision builds upon the one before it. This is what turns Optimization Power into something much more powerful: continuous, connected decisioning.
With this level of coordination, the marketer’s role evolves.
Instead of manually managing decisions across campaigns, channels, content, and timing, marketers define the strategy, set the goal, and let the AI agents optimize it.
At the same time, they gain visibility and control. From one place, they can see which AI agents and optimizations are already active, add more with a click, and expand AI decisioning without managing each layer separately. They can also see the impact in the same place, making it easier to measure results and understand where to adjust next.
This is Positionless Marketer in practice: less time spent configuring campaigns, more time spent shaping the strategy that guides how AI executes. Less operational complexity, more strategic control.
AI agents are powerful. But their real value comes from working together.
Inside AI Decisioning Studio, four core agents coordinate decisions across journeys, offers, content, and timing, turning disconnected optimizations into a connected system.
For marketers, this changes how execution works. Instead of managing complexity, they orchestrate outcomes.
And that is what defines the Positionless Marketer. Not someone doing more tasks, but someone with the power to set direction, align execution, and scale results through coordinated intelligence.
For more insights, contact us to request a demo.
In this proprietary Forrester report, learn how global marketers use AI and Positionless Marketing to streamline workflows and increase relevance
Sophie is a product marketing manager with a communications and marketing background. She specializes in go-to-market strategy, product messaging, and digital engagement for SaaS and B2B companies. She combines creative storytelling with a data-driven mindset to clarify product value and build stronger connections with target audiences. Sophie holds a degree in Communications and Marketing from Reichman University (IDC Herzliya).
AI Decisioning Studio is a unified environment within the Optimove platform where marketers can manage, monitor, and coordinate four core AI agents. It brings journey, offer, content, and timing decisions together under a shared strategy, enabling connected execution rather than isolated optimization.
AI Decisioning Studio currently includes four core agents: the AI Journey Decisioning Agent, the AI Offer Decisioning Agent, the AI Content Decisioning Agent, and the Send Time Optimization Agent. Additional agents are expected throughout 2026.
Marketing automation executes based on preset rules and triggers. AI decisioning goes further by learning from real-time data, predicting outcomes, and adapting decisions continuously. Where automation follows a fixed path, decisioning evaluates all options and selects the one expected to generate the most value for each customer.
The agents operate in a coordinated system. The Journey Decisioning Agent selects the best campaign, which provides context for the Offer Decisioning Agent to choose the right variation. The Content Decisioning Agent then selects the most effective message, and the Send Time Optimization Agent determines the ideal delivery moment. Each decision layer builds on the one before it.
Yes. Marketers define the strategy, goals, and constraints. AI Decisioning Studio gives full visibility into which agents are active, how they are performing, and where adjustments can be made. Marketers can configure agents, activate or deactivate them, and interact with them via chat, all without technical expertise.
