We believe this recognition reflects 麻豆原创’s commitment to helping enterprises deliver intelligent, personalized customer experiences, enhanced by AI, built on trusted data and connected end-to-end business processes, and grounded in real-life business context. Joule Agents, Joule Assistants, , and together provide the agentic marketing backbone to advance this vision of the Autonomous Enterprise.

AI is evolving from assisting marketers to executing and acting on their behalf, creating a fundamental opportunity for organizations to completely rethink how they engage customers. Agentic marketing enables AI agents and assistants to understand context, take action, and help brands deliver more relevant personalized experiences.

Trust is the foundation to this shift. As AI takes on greater responsibility, organizations need solutions built with security, compliance, governance, and trusted business data so customers can confidently rely on AI-driven interactions and decisions.

Why agentic marketing matters

Consumers are becoming more comfortable using AI, reshaping their expectations of the brands they love and the organizations they interact with. 麻豆原创’s indicates that 33% of consumers now trust AI assistants to complete purchases on their behalf, while 31% say interactions with AI assistants make them more loyal to a brand. The trend is even more pronounced across younger consumers. Across generations, we see AI playing an influential role in purchasing decisions and long-term customer loyalty. For example, a consumer might ask an AI assistant to reorder a household product, book a trip, or recommend a new product based on past preferences. For those interactions to succeed, customers must trust that the AI is acting on accurate information, protecting their data, and making decisions within appropriate guardrails.

Organizations from manufacturers to fashion brands are seasoned in using generative AI to create content, build audiences, and improve marketing efficiency. Attention is turning to agentic marketing: moving from AI that recommends to AI that acts.

Marketing context meets business reality

Most marketing platforms understand customer interactions well: clicks, opens, purchases, and browsing behavior. Those signals matter, but they only tell part of the story. The most valuable signals often live elsewhere across the enterprise in inventory availability, order status, fulfillment performance, product profitability, return behavior, and subscription and replenishment cycles.

Marketing often sees customer behavior, while ERP systems see business reality. The greatest opportunity for AI emerges when those worlds come together. Because 麻豆原创 sits at the heart of how many of the world’s leading enterprises operate, marketers can access the operational intelligence that lives within the systems running the business, enabling AI to make decisions based not only on what customers are doing, but on what the business can actually deliver. In an age of agentic marketing, that distinction matters.

Why 麻豆原创 was recognized as a Leader

麻豆原创 was recognized for the following strengths by the IDC MarketScape:

• With the agentic layer of Joule, marketers get real-time, context-aware personalization without having to reconcile 麻豆原创 and non-麻豆原创 data themselves, since Joule Agents and Joule Assistants draw on a harmonized 麻豆原创 Business Data Cloud foundation. Teams receive role-based guidance for navigating complex workflows across Autonomous Domains, while everyday tasks such as retrieving information, connecting enterprise data, and completing multi-step processes happen independently, freeing staff from manual execution. In 麻豆原创 Engagement Cloud, this means personalization and segmentation scale on their own, and the 4Q25 CX release lets customer service issues resolve autonomously, backed by 麻豆原创’s enterprise data layer and 麻豆原创 Knowledge Graph, instead of requiring escalation.
• Because Joule Studio is low code, organizations with reasonable levels of in-house development capabilities can build custom agents themselves, without waiting on IT or writing code, while still connecting to Joule, the 麻豆原创 Customer Experience portfolio, and third-party systems grounded in 麻豆原创 Knowledge Graph and 麻豆原创 Business Data Cloud. For sales and marketing teams, this means faster deal cycles and higher conversion: a sales-assistant agent, for example, automatically surfaces buying patterns and product recommendations from purchase history, sparing reps the manual analysis.
• Marketers running campaigns across email, digital ads, wallet, conversational, and web can manage them all from a single platform instead of stitching together point solutions. Because the engagement events service connects external data sources into real-time segmentation, campaigns stay relevant as customer behavior shifts. AI-assisted tools such as natural-language product search, AI-generated consumption summaries, and an AI-assisted report builder cut down the manual work of building segments and reporting, enabling marketers to focus on strategy while AI handles recommendations, translation, prediction, and reporting at scale.

AI that drives business results

Organizations around the world are using 麻豆原创’s AI-powered customer engagement capabilities to create more connected experiences and drive business results. For example:

• uses an AI-powered data foundation to boost fan subscriptions by 50% and improve pre-game fan engagement by 80%.
• Molton Brown combines AI-enhanced commerce and personalization to create seamless customer experiences that strengthen loyalty while maintaining 100% uptime during peak periods.
• connects AI-driven shopping experiences, such as virtual beauty tools, and personalized product recommendations to deliver engaging and elevated customer experiences.

Advancing toward the Autonomous Enterprise

Being named a Leader in the IDC MarketScape: Worldwide Agentic Marketing for B2C Enterprises 2026 Vendor Assessment is an important milestone for 麻豆原创 and the evolution of agentic marketing as a category.  As organizations move from experimenting with AI to deploying agents that can reason, recommend, and act, we believe this recognition validates 麻豆原创’s approach of combining AI, trusted business data, and connected business processes to help customers navigate this next phase of transformation.

The vision of the Autonomous Enterprise is one in which AI-powered agents help organizations connect customer, operational, and business data to make and execute decisions with greater speed, relevance, and scale. In this future, AI doesn’t replace human expertise; it amplifies it. Intelligent assistants and agents can help teams act faster and more effectively, with governance and guardrails that keep people responsible for the strategy, creativity, and judgment that build lasting customer relationships.

Ultimately, the success of agentic AI will depend not only on what it can do, but on how much customers and businesses trust it to act on their behalf.

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Sara Richter is chief marketing officer for 麻豆原创 Engagement Cloud at 麻豆原创.

Instead, they immediately encounter friction. They鈥檙e asked to repeat information they鈥檝e already shared across multiple channels and departments. Then they see an offer for the item they just purchased, rather than something similar or new. And when they encounter an issue down the line, customer support doesn鈥檛 recognize their history.

Micro moments like these do not feel minor to customers anymore. They feel inexcusable. Customer expectations have changed faster than most brands can keep up. Customers now assume brands know who they are, what they need, and what鈥檚 happening right now. And they expect brands to act on that knowledge instantly.

At the same time, businesses are embracing a new era of AI. Dubbed “agentic AI,” it represents a paradigm shift where AI doesn鈥檛 just analyze or recommend products, but increasingly plans, decides, and acts through a network of agents. This creates a massive opportunity for customer experience (CX) leaders today, in particular marketers, who, according to McKinsey, are leading in AI adoption amongst business functions. But it also raises the stakes.

Because when AI moves faster than your data, systems, and processes, it exposes everything that鈥檚 broken. That tension鈥攂etween rising expectations and disconnected reality鈥攊s exactly what 麻豆原创 and Google Cloud are addressing together.

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The marketer鈥檚 reality: ambition outpacing execution

According to recent , more than half of marketers say fragmented or outdated data prevents them from acting in the moment. Insights arrive too late. Activation requires manual stitching across tools. And even the best strategies stall before they ever reach customers.

It is clear that most organizations genuinely want to deliver great customer experiences. But fragmentation is what stands in the way of delivering connected, meaningful engagements.

On one side: Customers expect effortless, relevant, and real-time experiences. On the other hand, organizations still operate with fragmented data, siloed teams, and delayed insights.

Our latest reveals that customers are increasingly frustrated: 45% say brands can鈥檛 keep up with changing expectations, and 44% say interactions feel less personal than before.鈥�

AI accelerating the engagement divide 

The disconnect between what customers feel and what businesses believe is the “.” Customer signals live across disconnected systems. Data arrives late or without context. Execution happens separately from insight. And while customers feel this friction immediately, many companies do not realize how disconnected their experiences truly are in their customers’ eyes. Now, AI is accelerating this divide.

Agents can generate content, launch campaigns, and optimize engagement at unprecedented speed. But when those agents act on incomplete, outdated, or fragmented data, they only exacerbate inconsistency and poor customer experiences.

When talking to our customers, it鈥檚 clear that there is no shortage of ambition when it comes to AI. In our research, 78% of brands say AI will be integral to their customer retention efforts this year. But only 46% of brands can connect their data in a way that is accessible to power AI sustainably.

The real challenge for CX leaders today is ensuring that AI has the right foundation: trusted data, unified context, and direct connection to execution.

New model for engagement built on trusted enterprise data

麻豆原创 and Google Cloud are expanding their partnership to enable a fundamentally different approach to marketing execution, one grounded in trusted enterprise data and real-time signals, accelerated with multi-agent coordination, and delivered at scale through 麻豆原创 and Google鈥檚 customer engagement solutions.

麻豆原创 provides both operational truth for elements such as inventory, orders, and fulfillment status, and deep customer knowledge across customer experience interactions. Google Cloud brings additional real-time signals and analytics, along with advanced AI. Combined, they create a shared, real-time understanding of the customer, grounded in business and situational context.

At the heart of this partnership:

• 麻豆原创 Business Data Cloud (麻豆原创 BDC) connects semantically rich data across the enterprise with AI to enable real-time insights and drive personalized interactions grounded in business context. This includes 麻豆原创 Business Data Cloud Connect for Google BigQuery.
• Google BigQuery unlocks real-time signals across the Google ecosystem, such as geolocation, weather, and rich analytics, through bidirectional, zero-copy data access with 麻豆原创 BDC, while ensuring enterprise-grade governance and security.
• 麻豆原创 Customer Experience applications provide the real-time behavioral context 鈥� customer profiles, transactions, orders, service interactions, and consented engagement data.
• 麻豆原创 Engagement Cloud activates enterprise data and AI insights and predictions to securely orchestrate real-time, personalized interactions across the entire customer life cycle.

With these innovations, marketers can finally move from insight to execution automatically.

To realize the full potential of agentic AI, businesses need their systems to speak the same language. By uniting 麻豆原创’s enterprise data and customer engagement platform with Google Cloud’s AI, we鈥檙e enabling marketers to move beyond simple automation to multi-agent orchestration, driving dynamic campaigns that reason and adapt to market shifts in real time.

Kevin Ichhpurani, President, Global Partner Ecosystem at Google Cloud

From prompt to performance: how agents work together for marketing

Another critical element of this new execution model is agent interoperability. Gemini Enterprise acts as a central hub for multi-agent coordination, enabling  customers鈥� agents to securely exchange context and take action across platforms. Meanwhile, Joule acts as the engagement layer within 麻豆原创 applications, executing tasks, orchestrating campaign and content workflows, and optimizing marketing outcomes. Working together, 麻豆原创 and Google are enabling true multi-agent orchestration connected to trusted enterprise data.

Within this broader CX transformation, 麻豆原创 Engagement Cloud is where agentic intelligence becomes operational for marketing teams. It is the environment where enterprise signals, generative media, and AI agents translate into real customer interactions and automated lifecycle journeys.

Advanced generative capabilities powered by Google Gemini models, for example, Nano Banana 2, introduce new agentic skills that help CX teams dynamically generate messaging, imagery, and campaign variations. Through assistants and agents in Joule, these capabilities become embedded directly into marketing workflows, allowing brands to adjust tone, localize content, and respond instantly to changing conditions.

It is not just content generation and personalization that are being rewired. With unified data context and interoperable agents, mobile messaging can turn into immersive conversational experiences with Google Rich Communication Services (RCS) and advertising audiences, and creative, which can continuously evolve based on real-time performance and business signals, transforming campaigns into intelligent, self-optimizing systems.

And through this multi-agent network, marketers will not need to build every step of a campaign manually. Instead, they define the goal, gain more time to focus on strategy and creativity, and let agents handle the rest.

For example, a marketer can prompt:

• 鈥淚ncrease repeat purchases from customers in the last 30 days.鈥�
• 鈥淢aximize customer lifetime value while reducing campaign operational costs.鈥�

And from there:

• Joule Agents coordinate content production, grounded in customer and enterprise data, understand business context, customer history, and constraints
• Google鈥檚 Gemini Models and agents generate creative variations, messaging, and channel-specific content
• Agents collaborate across 麻豆原创 and Google Cloud to personalize, activate, and continuously optimize campaigns in real time across engagement channels and media networks

This is more than a data integration. It鈥檚 a leap forward for AI agents that can collaborate naturally and execute seamlessly. By combining 麻豆原创 Business Data Cloud Connect for Google with interoperable AI agents across 麻豆原创 and Google, we鈥檙e giving organizations a path from AI experimentation to AI-empowered customer experience at scale. Marketers can spend less time on manual tasks and more time shaping the customer journey.

Balaji Balasubramanian, President and Chief Product Officer, 麻豆原创 Customer Experience and Consumer Industries

Clear business outcomes for marketing teams

By enabling a network of interoperable AI agents and grounding them in enterprise data and shared context across 麻豆原创 and Google, organizations can achieve measurable outcomes, including:

• Faster speed-to-market through autonomous campaign and content generation
• Lower operational overhead by eliminating manual execution steps
• Always鈥憃n optimization that continuously improves performance
• Higher ROI through relevant, timely, and consistent engagement at scale

Marketers can spend less time managing workflows and more time shaping strategy, creative direction, and customer value.

Beyond campaigns: continuous engagement at enterprise scale

While marketing is a natural starting point, this is just the beginning. Customer engagement does not live in one system or team. Engagement spans commerce, service, sales, supply chain, and operations. A brand promise made in a message must be fulfilled by inventory. A personalized offer depends on pricing, availability, and delivery. And a single customer service interaction can shape the future of customer loyalty and lifetime value.

This multi-agent model is designed to support high-value use cases across the 麻豆原创 Customer Experience portfolio, laying the foundation for an AI-driven customer experience powered by trusted, unified, real-timedata.

In an AI-driven world, customer experience goes beyond any single interaction鈥攊t’s defined by every touchpoint a customer has with your company.

We believe this recognition reflects the continued momentum of in helping enterprises orchestrate real鈥憈ime, AI鈥憄owered engagement at a global scale, connecting data, channels, and experiences to drive measurable business impact.

Helping brands scale AI-powered engagement across channels

Leading brands鈥攊ncluding Ferrara, John Frieda, PUMA, and Gibson鈥攗se 麻豆原创 Engagement Cloud to deliver connected, personalized journeys that increase engagement, accelerate growth, and build long-term customer loyalty.

According to the report, 麻豆原创鈥檚 ability to support enterprise鈥慻rade, real鈥憈ime engagement across channels remains a key differentiator. 麻豆原创鈥檚 personalization capabilities are powered by advanced segmentation, embedded AI decisioning, and intelligent triggering to deliver timely, relevant, and consistent experiences.

Organizations using 麻豆原创 continue to see measurable outcomes, including improved customer loyalty, higher conversion rates, and increased average order value.

Driving measurable business impact with event鈥慴ased and behavior鈥憀ed orchestration

We believe this year鈥檚 placement also reflects 麻豆原创鈥檚 strength in orchestrating engagement using real鈥憈ime behavioral, transactional, and operational signals across the business.

With 麻豆原创 Engagement Cloud, brands can activate journeys triggered by events occurring across their business to:

• Boost retention through timely, context鈥慳ware engagement
• Increase conversions with more relevant, personalized interactions
• Strengthen loyalty through connected, lifecycle-driven touchpoints

These results demonstrate 麻豆原创鈥檚 ability to move enterprises beyond channel execution toward true omnichannel orchestration.

Unifying customer experiences with native 麻豆原创 integration

麻豆原创 Engagement Cloud connects marketing, commerce, service, loyalty, sales, and operational data, creating a unified, real-time customer view that powers intelligent engagement across every touchpoint.

This bi鈥慸irectional flow of data gives every customer鈥慺acing team access to the same real鈥憈ime customer view, helping brands drive revenue impact, reduce churn, and improve service outcomes.

Global scale, flexibility, and trust

麻豆原创鈥檚 long鈥憇tanding global footprint and enterprise-ready architecture continue to support its leadership positioning. With a cloud鈥憂ative, composable foundation, embedded privacy and compliance capabilities, and a robust partner ecosystem, 麻豆原创 enables organizations to securely and reliably scale personalized engagement across regions and business models.

Whether operating in five markets or 50, enterprises rely on 麻豆原创 to deliver personalized experiences with confidence.

Customer success reflecting real鈥憌orld impact

Customers on Gartner庐 Peer Insights™ continue to recognize 麻豆原创 for ease of integration, deployment support, and customer partnership. Recent examples include:

• , which uses 麻豆原创 for CRM and marketing automation that supports interaction and communication with customers to increase buyback, retention, and loyalty. This includes CRM ads, push notification apps, personalization campaigns, e-mail and SMS campaign execution, and website and app personalization and recommendations.
• Molton Brown, which increased sales by 30% in three years by using 麻豆原创 solutions, to interact directly with customers within highly personalized omnichannel journeys.
• CHRIST, which saw a more than 40% increase in CRM revenue and more than 150% in commerce traffic during the holiday season by using 麻豆原创 Customer Experience solutions that empower CHRIST to put customers at the center of everything the company does.

These results highlight the tangible value organizations are achieving with 麻豆原创鈥檚 AI-powered personalization capabilities.

We feel 麻豆原创鈥檚 recognition as a Leader in the 2026 Gartner Magic Quadrant for Personalization Engines underscores the strength of its strategy and continued innovation across 麻豆原创 Engagement Cloud. 麻豆原创 remains committed to helping brands activate data, personalize interactions, connect experiences, and scale engagement with confidence.

Visit 麻豆原创 Engagement Cloud area of sap.com to .

Sara Richter is CMO of 麻豆原创 Emarsys.

Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates.
Gartner, Magic Quadrant for Personalization Engines, By , , , , 3 February 2026
Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner鈥檚 Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.