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Measure how ready your organization is to scale Customer Experience Orchestration with AI— enabled by the enterprise-grade control required to move quickly, safely, and at scale.
Customer Experience AI Maturity Index
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Continuously — always-on optimization powered by AI across journeys and touchpoints
Frequently — ongoing testing across key journeys
Occasionally — structured for select campaigns or use cases
Rarely — testing is limited and ad hoc
How consistently are you testing and optimizing customer experiences?
Exponential — dynamically generated content at scale, leveraging generative AI
Scaled — high-volume production across channels with Ai-assisted content creation
Growing — increased output with some efficiency gains
Limited — constrained by manual creation
How would you describe your content production capacity today?
Same day or real-time — AI-driven content creation and activation
Days — supported by automation and AI-assisted workflows
1–3 weeks — defined workflows, but still dependent on manual effort
Months or more — manual processes and approvals delay execution
How quickly can you get a new piece of content into market?
Orchestrated — real-time, adaptive journeys powered by AI-driven decisioning
Connected — journeys orchestrated across key touchpoints, with AI-assisted decisioning
Coordinated — some cross-channel journeys
Siloed — channel-specific execution
How effectively are your customer journeys orchestrated across channels?
Foundational — AI-driven personalization adapts experiences in real time across channels
Significant — real-time data used in key use cases, with AI-assisted personalization
Limited — periodic updates inform personalization
Minimal — mostly static segmentation
How much does real-time data inform your personalization?
Optimized — AI-driven insights and tools actively manage and optimize brand visibility
Measured — structured visibility into AI-driven discovery performance
Limited — fragmented or anecdotal insights
Not at all — no visibility into AI discovery channels
How well do you understand and manage your brand’s presence in AI-driven discovery?
Fully automated and scalable — governance enables speed without delays
Mostly integrated — governance is embedded in key workflows
Partially streamlined — some workflows are optimized, but friction remains
Manual and reactive — approvals frequently delay execution
Which best describes how governance and approvals function in your workflows today?
Embedded, enforced, and auditable across AI-driven workflows
Standardized across teams, with policies applied to AI use cases
Defined but inconsistently applied
Unclear or undefined
How clearly defined are policies governing customer data in AI-driven experiences?
Clearly defined and operationalized — roles are embedded across workflows, including AI-driven processes
Documented, but inconsistently applied — roles are defined but not consistently followed across teams or workflows
Defined, but undocumented — roles are generally understood but not formalized
Ad hoc — roles and responsibilities are informal or unclear
How clearly defined are roles and responsibilities as AI is deployed across the enterprise?
Fully traceable and auditable across all AI-driven content, decisioning, and customer-level data usage
Traceable for key workflows, including AI-assisted processes and data usage
Partially documented
Not traceable
How easily can you trace how content and decisions were generated?
Very high — AI-assisted and policy-driven systems enforce brand integrity across content and experiences
High — automated workflows and checks are in place, with manual brand review for exceptions
Moderate — guidelines exist but inconsistently applied
Low — relies heavily on manual review
How confident are you in maintaining brand integrity at scale?
Finish
Accountable and outcome-driven — ownership is explicit and tied to outcomes across both human and AI-driven workflows
Aligned — ownership is clearly established across functions
Partially defined — ownership exists but varies by team or workflow
Fragmented — ownership is unclear and siloed across teams
How clear is ownership across content, data, and decisioning workflows?
Diagnosis Your customer experiences are not connected in a way that scales—and AI and data cannot be consistently applied to improve them. What’s happening • Content and journeys are designed and executed in silos • Personalization is inconsistent and difficult to operationalize • Visibility is limited across channels and AI-driven discovery What’s breaking • No unified flow from data → content → journey → measurement • No shared operating model across Marketing, Technology and Risk partners • No consistent control layer to support scale Why it matters • AI and content investments produce isolated wins – not enterprise value • Customer experiences remain fragmented • Scale is limited by lack of coordination and confidence
Experiences are not connected across content, data, and journeys
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Customer Experience Orchestration Maturity How effectively your organization delivers connected, scalable customer experiences— balanced by the control required to sustain them.
View your detailed diagnosis
Diagnosis You are scaling customer experiences with AI—but faster than your organization can consistently orchestrate and control them. What’s happening • Content production and activation are accelerating • Journeys and personalization are expanding rapidly • Teams are moving fast across channels and AI-driven discovery What’s breaking • Governance is not embedded in content and journey workflows • Brand and compliance controls are applied inconsistently • Limited traceability of how experiences are created and delivered Why it matters • Speed introduces risk instead of compounding value • Approval cycles slow as scrutiny increases • Experiences must be reviewed, reworked or rolled back
Experience velocity is outpacing governance and control
Diagnosis You have the control required to scale customer experiences—but your organization cannot operationalize AI and execution at the speed needed to deliver them. What’s happening • Strong governance frameworks exist • Clear policies and risk controls are in place BUT: • Content and journeys are slow to launch and evolve • Personalization is limited by execution speed What’s breaking • Governance exists outside of execution workflows • Approval processes create friction instead of flow • Teams struggle to operationalize AI and content at scale Why it matters • Growth is limited despite investment in AI and content • Opportunities for personalization and optimization are missed • Execution cannot keep pace with market demand
Experience creation is well-governed, but they are not delivered at scale
Diagnosis You are scaling customer experiences with both execution and control—where AI is fully embedded to continuously optimize and orchestrate experiences across channels and at the individual customer level. What’s happening • Content, journeys and personalization operate as a connected system • Experiences are continuously optimized and personalized at the individual level – not just segment-based • Governance is embedded directly into workflows, ensuring experiences are on-brand, compliant and auditable at scale What’s working • Marketing, Technology, and Risk operate as a unified system • Decisions are fast, traceable, and aligned to shared KPIs • Brand is actively managed across channels and AI driven discovery environments with consistent, governed outputs Why it matters • Experiences are delivered in the right moment – relevant, personalized and consistent across every • touchpoint • Personalization scales without sacrificing brand integrity, compliance or customer trust • AI and CX investments translate into measurable growth through more precise, high-quality customer • experiences
Experiences are connected, controlled, and continuously optimized
