Future of Marketing
Marketing for the agentic era.
From AI adoption to customer experience orchestration.
A playbook for the future of marketing.
AI is reshaping every stage of the customer journey. Discover the capabilities needed to orchestrate connected, personalized customer experiences — combining AI with human ingenuity, trusted governance, and unified data.
The fundamentals of great marketing.
Every major technology shift has changed the role of the marketer. Search changed discovery. Social changed engagement. Mobile changed the experience. New AI innovations are changing marketing in a more fundamental way. Success isn’t determined solely by whether customers can find your brand. It’s increasingly determined by how AI understands, represents, and recommends your brand. It's tempting to read that as a story about technology. It's really a story about marketing.
The fundamentals of great marketing haven't changed. Great marketers still build trust, shape perception, tell stories that resonate, and earn preference and loyalty. What has changed is the scale, speed, and number of channels where those fundamentals now need to come to life. AI makes that scale, speed, and reach possible. Customer experience orchestration is the strategy that channels it into business results.
The brands redefining customer experience are no longer optimizing disconnected systems. They are orchestrating a connected system, where brand visibility, conversational engagement, content supply chains, governance, organizational readiness, and a trusted AI foundation operate together. In this system, AI works as both coworker and capability, giving marketers the ability to deliver more relevant experiences, at greater speed and scale, while empowering human creativity, authenticity, and insight that customers value most.
Discover how marketing is changing in the agentic era with Emily Ketchen, SVP and CMO, Intelligent Devices Group and International Markets, Lenovo.
Learn more | Learn more how marketing is changing in the agentic era
Meet the AI-empowered, zero-tolerance customer.
Customers increasingly begin with AI. How customers find you, how you surface in AI-generated responses, and how your brand connects across an expanding set of surfaces is being rewritten. As discovery changes, so do the demands on the content your brand creates and delivers.
Three findings from Adobe 2026 AI and Digital Trends Consumer Report, a global survey of 4,000 customers, paint a picture of a customer who evaluates faster, expects more, and increasingly forms opinions on channels many brands are only beginning to understand.
- Discovery is being rewritten.
Around 25% of customers now name AI-powered platforms as their primary research tool, ahead of brand websites, reviews, and ratings. Among those already using AI for research, 42% say they always or frequently treat AI assistants as their primary source. And in August 2026, Adobe Digital Insights consumer data revealed that AI-driven traffic to retail sites is up 62% year-over-year. Buying decisions are increasingly shaped in conversational interfaces on AI platforms, creating a new challenge for brands that have spent years primarily optimizing for search.
- Brands have five seconds or less to capture attention.
The report1 found that 69% of customers say brands have five seconds or less to capture their attention in a promotional email, ad, or social media post. Immediate relevance, distinctive content, compelling offers, and authenticity matter more than familiarity alone. Brands don't just need more content, they need content that earns attention instantly.
- Personalization without orchestration can damage the brand.
Nearly 45% of customers disengage if they receive too many promotions, even relevant ones. Almost 50% disengage when personalized experiences arrive at the wrong time, while roughly 40% tune out when offers don't match where they are in the buying journey. Personalization succeeds only when content, timing, and context work together.
of customers say they always or frequently treat AI assistants as their primary source.
of customers say brands have five seconds or less to capture their attention.
of customers disengage if they receive too many promotions.
Learn how brands are using AI to radically transform marketing for the better with Anil Chakravarthy, President, CXO Business, Adobe.
Why marketing needs a new operating model.
Most marketing functions still run on a quarterly rhythm, where you plan the campaign, map the journey, set the personalization rules, and launch. Customers have never moved this way. Today, they decide in seconds, move across channels on their own schedule, and expect to be recognized in the moment, not on the timeline a planning cycle allows.
Marketing leaders are taking on a broader responsibility. They’re no longer simply managing campaigns and channels. They’re increasingly responsible for how their brands are understood across a rapidly expanding digital ecosystem. They also recognize that the environments shaping their brands have become much broader than the channels they directly manage.
This new pace and elevated content requirements are straining every marketing organization. Customer data is scattered across systems that were never designed to work together, leaving no team with a complete view of the customer. Content takes weeks to travel from brief to launch, by which point the opportunity often passes. Separate teams deploy separate AI tools for different use cases, creating isolated efficiencies instead of connected customer experiences. All of this is unfolding under tightening financial pressure, even as the expectation to drive productivity keeps climbing.
Meeting this moment requires more than adopting AI. Marketing leaders need an operating model that helps them deliver relevant, personalized experiences at the speed, scale, creativity, and authenticity customers expect.
Customer experience orchestration is at the heart of the operating model for this new marketing era. Adobe defines customer experience orchestration as the integrated AI-powered system and supporting processes that optimize and deliver personalized experiences to every customer, on any channel, at the right time, across the full customer lifecycle — prospect, acquire, engage, convert, and retain.
The six components that follow show how marketing leaders can put customer experience orchestration into practice by strengthening brand visibility, making customer engagement conversational, evolving the content supply chain, and underpinning it all with governance, organizational readiness, and a trusted agentic foundation.
6 key components of an effective marketing model.
1. Define your brand visibility strategy.
Brands no longer control every conversation about who they are. AI platforms surface the brand with the clearest, most structured, and AI-readable content, while giving greater weight to third-party citations, trusted sources, and community signals than content published on a brand's own website.
This matters more with every passing quarter. Among customers who already use AI for research, 42% say they always or frequently treat AI assistants as their primary source.1 Brand visibility is no longer determined solely by how well content performs in search. It's increasingly determined by how well content is understood, trusted, and surfaced by AI systems. The opportunity is to consistently influence how your brand is understood across owned content, communities, reviews earned media and AI-powered experiences. Yet, many organizations are still flying blind. The AI Visibility Index 2026 study found that 45% of marketers say they cannot properly measure AI visibility,2 highlighting the need for new approaches to understanding how brands are represented across AI-powered discovery experiences.
To strengthen brand visibility, marketing leaders should:
- Understand how their brand appears across the entire customer journey, including AI assistants, summaries, and third-party surfaces where customers increasingly begin their research.
- Structure content so that it is accurate, trustworthy, and easily understood by both search engines and AI-powered experiences.
- Build a brand visibility strategy that extends beyond owned channels, ensuring the brand appears consistently and credibly wherever customers evaluate their options.
What is brand visibility?
Brand visibility is a brand's ability to be clearly discovered, accurately represented, and consistently trusted wherever and however customers evaluate options, especially through AI-powered search and conversational interfaces.
2. Make customer engagement conversational.
Brand visibility gets customers to your business. Customer engagement is what happens next. Increasingly, customers expect to interact with a brand the way they would with a knowledgeable colleague, through one continuous, personalized conversation rather than a series of disconnected campaigns.
For marketers, this is a structural shift. The siloed campaign is giving way to continuous engagement that creates value across the entire customer lifecycle. This relationship cannot be built in a single interaction. Only 12% of customers feel ready to buy after one personalized message, while for 40% the tipping point comes after three to five interactions.1 B2B buyers are also looking to navigate more of customer journey on their own terms. A recent Gartner report revealed 67% of buyers prefer a sales rep-free experience. In this environment, the most effective customer engagement builds relevance and trust over time, making it one of the strongest drivers of both loyalty and revenue.
To make customer engagement conversational, marketing leaders should:
- Recognize each customer in real time and build on every interaction instead of starting from scratch.
- Close the gap between understanding what customers need and delivering it in the moment.
- Create conversational interfaces that connect customers directly to your brand's expertise.
- Let systems handle routine decisions at scale, while people set the strategy, standards, and brand voice.
Scaling personalized marketing with AI agents with Margaret Jobling, CMO, NatWest Group.
3. Evolve your content supply chain.
AI has put high-volume content production within everyone's reach. Content volume is no longer a competitive advantage. What matters now is whether content has the creative integrity, brand coherence, and customer relevance to rise above a sea of sameness.
A connected content supply chain links planning, creation, management, activation, and measurement into a single coordinated flow. Teams create once and adapt intelligently across channels and formats. Strong creative ideas scale without losing what made them compelling, while performance data feeds back in real time to improve what gets created next. On average, AI-powered content supply chains reduce time to market by 36%,1 without the brand drift that volume typically produces.
To evolve the content supply chain, marketing leaders should:
- Connect planning, creation, management, activation, and measurement into a single workflow, eliminating handoffs that slow content from brief to market.
- Build continuous feedback into the content lifecycle, using performance insights to improve both the content that's created and the experiences it delivers.
- Design content for reuse, so creative ideas can be intelligently adapted across channels, formats, and audiences without starting from scratch.
The first three components are the customer-facing capabilities of customer experience orchestration. Their success depends on three foundational capabilities: governance, organizational readiness, and a trusted agentic foundation.
Discover how AI is scaling content production with Varun Parmar, Senior Vice President and General Manager, GenStudio and Customer Experience Orchestration, Adobe.
4. Enact an effective and enforceable governance strategy.
Most organizations still treat governance as overhead, something to handle once the real work is done. The ones building durable advantage treat it as infrastructure, because as AI agents absorb more of marketing’s day-to-day work, the guardrails that define how they operate only grow more consequential. Governance, in other words, is how a brand keeps its promises at scale.
The stakes here are genuinely human. Customers trust brands that are transparent. One-fifth of customers say they can reliably detect AI in interactions. At the same time, unexpected AI involvement can cause disengagement. More than a third (37%) of customers say they would disengage if they learn they are interacting with AI when expecting a person. However, this is not a reason for brands to slow down, but a reason to be deliberate about transparency and quality. The policy-practice gap compounds this risk: 55% of organizations say they have strong AI governance policies, yet only 43% report that those policies are routinely followed. That follow-through only holds at scale if governance is built into the platform.
The platform can enforce the rules, but people still write them, watch them, and decide when to change them. The gap between policy and practice is closed by the people behind the technology, not by the technology itself.
At enterprise scale, good governance comes down to:
- Write the rules that define what agents may do, where they must stop, and who decides when that changes.
- Encode those rules so agents apply them consistently across millions of decisions, not case by case.
- Build brand and commercial safety into the workflow itself, so it travels with every action instead of waiting at a review gate.
The AI inflection point.
Discover additional best practices for designing, implementing, and scaling enterprise AI initiatives in The AI Inflection Point guide. It looks at the operating models, talent, and measurement practices that turn AI from a handful of pilots into a durable, enterprise-wide capability.
5. Build organizational readiness.
Choosing the AI technology marketing teams pilot is the straightforward part. The harder and more durable competitive advantage lies in how teams are structured, skilled, and aligned around delivering orchestrated customer experiences at scale. CMOs are looking for pathways to align teams in their implementations and translate that into action to capture the compounding benefit of AI transformation. Research conducted by IDC on strategic C-suite collaboration revealed 42% of marketing executives believe they own the budget for marketing technology, but only 15% of IT leaders agree. Customer experience orchestration requires genuine collaboration across marketing, IT, legal, data science, and creative, supported by a CMO–CIO relationship that goes beyond coordination to shared accountability for outcomes.
CMOs who give their teams structured permission to experiment with trusted tools, clear guardrails, dedicated enablement time, and visible executive support are building organizational capability that compounds over time. Those who treat AI adoption as a technology procurement exercise will find the technology underperforms because the organization around it was never designed for it.
To build organizational readiness, marketing leaders should:
- Structure teams around shared customer outcomes, bringing together marketing, IT, legal, and data instead of operating in silos.
- Create the conditions for responsible AI adoption with trusted tools, clear guardrails, dedicated enablement time, and visible executive support.
- Build shared accountability between the CMO and CIO, so customer experience, governance, and data become shared business priorities.
The CIO–CMO imperative.
The top priorities for generative AI adoption in marketing organizations are building AI governance and quality controls and establishing AI safety and ethics protocols,1 both of which fall primarily within the CIO’s remit. The brands making the most durable progress are the ones where the CMO and CIO genuinely share accountability for these outcomes, not just coordinate on them. Discover how the relationship between CIOs and CMOs is evolving in the age of AI.
6. Implement a trusted AI and agentic foundation.
Brand visibility, customer engagement, and the content supply chain can all be strengthened independently. Many organizations are doing exactly that, only to discover they've improved individual capabilities rather than create connected customer experiences. Customer experience orchestration depends on a trusted agentic foundation that brings those capabilities together into one coordinated system. This foundation enables AI to work in two ways. First, as coworkers that collaborate with marketers to orchestrate, optimize, and govern customer experiences. Second, as autonomous AI agents that execute tasks within enterprise guardrails. Together, they ensure every action is grounded in trusted data, governance, and human oversight.
This foundation starts with data. Whether supporting marketers as AI coworkers or executing workflows as autonomous agents, AI can only act on a shared, accurate view of the customer if the underlying data is unified, governed, and accessible. However, data integration remains the single biggest transformational challenge, with only 4% of organizations reporting fully integrated, accessible data.3
Unifying data is the prerequisite for customer experience orchestration, giving coworkers and autonomous agents the shared context they need to work together. Coworkers help marketers orchestrate campaigns, customer engagement, and operations, while agents execute approved tasks at speed and scale. Throughout, marketers remain responsible for strategic direction, human oversight, and accountability.
To build a trusted agentic foundation, marketing leaders should:
- Unify customer data so every agent operates from the same, accurate, and real-time view of the customer.
- Encode brand, governance, and commercial rules into how agents operate, so decisions remain on-brand and on-policy by default.
- Design for human oversight, with people setting the strategy and exercising judgment while agents execute at speed and scale.
Without this foundation, agents work against each other rather than with each other. With it, customer experience orchestration becomes possible at enterprise scale.
This is the real shift. AI is no longer something that sits on the side generating insights. It's embedded directly into the experience workflows where journeys are designed and delivered, so it doesn't just inform teams but actually helps them execute. The agents doing that work are powered by models built specifically for customer experience and content use cases, with the flexibility to incorporate different models as needed.
But the same property that makes the foundation powerful, agents acting independently across millions of decisions, is what turns governance from a policy choice into a structural requirement. At low volume, governance is a document. At enterprise scale, it has to be infrastructure.
6 key components of an effective marketing model
The two-year horizon — design for both humans and agents.
The next two years will shape which brands have assembled this operating model in time. In this horizon, agents become three things to a marketing organization at once. A new audience to be discovered by as customers delegate decisions to assistants that shop, compare, and act on their behalf. A tool that marketers use to plan, produce, and optimize at machine speed. And a teammate that handles execution while people set strategy, judgment, and brand standards. Designing for all three at the same time is what it now means to design for both humans and agents.
This is the point at which enterprise architecture stops being digital-first and becomes agent-aware. Adobe 2026 AI and Digital Trends Consumer Report highlights the urgency — 78% of organizations expect agentic AI to handle at least half of customer support interactions within 18 months, yet fewer than 25% are running agentic AI pilots today. The gap between expectation and adoption is where the next competitive advantage will emerge as brands building connected AI systems today create an advantage that will be difficult to close.
The brands that lead are the ones that build right.
The next generation of marketing won’t be defined by who adopts AI capabilities first. It will be defined by who builds the operating model that connects data, content, people, and AI to deliver relevant, trusted customer experiences at scale.
Discover how Adobe CX Enterprise helps organizations put customer experience orchestration into practice.
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