Future-Proof Your Business
Executive Summary
Xylem stands at Level 2 of AI adoption in Marketing Operations, where individual team members use AI tools and early pilots exist, but systematic workflow automation and Revenue Operations collaboration remain limited. The company shows promising foundations with established AI policies, clear alignment to business objectives, designated AI leadership within Marketing Operations, and an internal AI assistant trained on company documentation.
Several challenges require attention to advance Xylem’s AI maturity: fragmented data across two Marketo instances limits effectiveness, cross-functional governance needs strengthening, experimentation lacks structured rhythm, and core marketing and revenue processes operate with minimal automation. We recommend focusing on four priorities over the next 90 days: completing the Marketo data audit, establishing a cross-functional team with Revenue Operations, publishing approved AI use cases, and launching targeted pilots tied to measurable outcomes.
Successfully implementing these recommendations will produce tangible benefits: faster campaign execution, improved data quality for lead scoring and routing, clearer AI usage guidelines, and enhanced collaboration between Marketing, Sales, and Revenue Operations teams.
The AI maturity model consists of four distinct levels that organizations typically progress through:
- Level 1: Individual AI experimentation occurs without formal policies or strategies. Benefits remain isolated to specific team members without systemic workflow changes.
- Level 2: AI usage expands to individual tasks like analysis or content creation. The organization acknowledges these efforts, but implementation remains inconsistent across teams.
- Level 3: AI becomes integrated into daily workflows, automating routine tasks such as classifying customer personas, analyzing sentiment, and personalizing email communications.
- Level 4: AI functions as a fully integrated component of operations, delivering highly customized customer experiences and significantly reducing time to market.
Based on our assessment, Xylem currently operates at Level 2 of AI maturity. Your teams show enthusiasm for AI adoption with some promising initiatives like the internal Marketing Operations Assistant and targeted email follow-up capabilities. However, your approach lacks formalization, with limited structured experimentation, minimal Revenue Operations collaboration, restricted data access across systems, and few automated workflows. Moving forward requires formalizing your pilot methodology, enhancing data quality across both Marketo instances, and strengthening coordination with Revenue Operations to align AI initiatives with revenue objectives.
Team &
Skills
01
Building AI capabilities starts with your people. Currently, your team demonstrates basic AI knowledge with occasional training opportunities. The positive indicators include genuine interest among team members, a designated AI Champion, and access to high-level educational resources. Your internal Marketing Operations Assistant that answers process questions and provides standard operating procedures represents an early success.
The next phase of team development requires a structured approach to building capabilities and establishing regular experimentation. We recommend implementing a targeted 6-8 week skill development plan covering three key areas: (1) Foundations including Marketo-specific AI features, segmentation logic, quality assurance procedures, and prompt writing fundamentals; (2) Applied workshops with hands-on experience building lead scoring experiments, persona classifiers, and email optimization routines; and (3) Guardrails addressing privacy, brand consistency, approval workflows, and secure prompt patterns.
Complementing this skill development, establish a monthly experimentation cycle where teams run 1-2 small tests with clear plans, baseline metrics, and simple reporting. Document all results in a shared workspace to facilitate knowledge transfer and enable other teams to build upon successful approaches.
01
Strategy
02
A coherent AI strategy provides the foundation for sustainable adoption across the organization. Your company has made progress with established policies and moderate leadership support. AI initiatives align with business growth objectives, though planning remains short-term, and formal cross-functional leadership between Marketing and Revenue Operations has yet to be established.
To strengthen your strategic approach, create a joint Marketing Operations and Revenue Operations working group with a focused 90-day charter. Include representatives from Sales Operations and IT to address integration requirements and risk management. Define 2-3 specific near-term outcomes with assigned budgets and clear ownership, such as reducing lead response time by 15%, improving MQL-to-SQL conversion rates by 5%, and reducing campaign build time by 20%.
Develop a straightforward implementation roadmap: complete the data audit, finalize pilot selection and performance metrics, and confirm budget allocations within 30 days; run pilot programs with weekly measurement and address data access challenges in days 31-60; scale successful pilots, discontinue underperforming initiatives, and document proven approaches in days 61-90. This phased approach ensures you can demonstrate value quickly while building toward longer-term transformation.
02
Data
03
High-quality, accessible data forms the backbone of effective AI implementation. Your current data environment presents significant challenges with limited access to clean information and partial system integration. While privacy and security guidelines exist, teams only occasionally leverage AI for data deduplication and enrichment, and the two separate Marketo instances create friction in data management.
Completing the Marketo audit represents a critical next step. This should include a comprehensive field inventory with ownership documentation, sync behavior mapping to CRM, and required field status; standardization of values for lifecycle stages, job titles, industries and regions; verification of consent and preference capture mechanisms; and confirmation of person and account matching rules across both Marketo instances and your CRM system.
Develop an “AI-ready data” checklist that specifies minimum input requirements for each use case, data freshness targets, and quality assurance mechanisms including automated alerts for empty fields, invalid values, and synchronization errors. While building these foundations, implement quick wins through AI-assisted data cleanup: normalize job titles and tag personas using a lightweight model, automate enrichment for missing firmographic data, and generate comment summaries in records to accelerate sales handoffs.
03
Efficiency
04
Automation represents a significant opportunity area for your organization. Currently, your teams operate with minimal automation across core Marketing or Revenue Operations processes, with AI occasionally supporting email follow-up for specific leads. Implementing targeted process automations can dramatically improve operational efficiency while demonstrating AI’s practical value.
We recommend piloting 2-3 specific process automations within your Marketo and CRM environments. First, implement persona classification to automatically categorize leads into 4-6 segments based on title, department and industry information, then present this classification to Sales with concise summaries. Second, develop lead routing quality assurance that identifies records missing critical fields (region, product interest) and requests completion before assignment. Third, create a campaign build assistant providing standardized program templates, copy verification, UTM validation, and timing recommendations.
For each automation initiative, create standard playbooks defining input requirements, decision logic, handoff procedures, and contingency plans. Implement weekly exception reporting to ensure human review of cases the automation flagged or couldn’t process. These focused automation efforts will demonstrate concrete value while building momentum for broader AI adoption.
04
Customer
Experience
05
Personalized customer experiences drive engagement and conversion. Your current personalization capabilities show moderate sophistication in messaging, with limited application of journey mapping, sentiment analysis, or highly tailored experiences. Account-based marketing personalization remains undeveloped.
A progressive approach to personalization will yield the best results. Begin with segment-level dynamic content customized by industry and buying role, using AI to generate multiple copy variants per segment for testing. Next, implement behavioral triggers sending relevant follow-up communications based on specific actions like website visits or content downloads. Then develop an initial journey map identifying 3-5 key moments from lead to opportunity, measuring drop-off points and adding timely content or sales alerts.
Launch two intelligence pilots to demonstrate additional value: a subject line and call-to-action generator with strict brand and compliance verification, and a basic sentiment and intent analysis from form comments and emails to guide follow-up strategy. For account-based marketing, select three strategic accounts, create comprehensive briefs combining firmographics, known contacts and engagement metrics, then test tailored content and measure performance lift.
05
Conclusion
Based on our assessment, we’ve identified a practical path forward for advancing Xylem’s AI marketing capabilities over the next 90 days. First, establish the organizational foundation by designating pilot owners from Marketing and Revenue Operations teams, publishing clear AI usage policies covering prompts, personal information handling and approval processes, and launching a monthly showcase for teams to demonstrate results. Second, strengthen data foundations by completing the two-Marketo audit, finalizing field mappings, addressing critical data quality gaps, and implementing automated checks for consent, value validation, and duplicates.
We recommend launching three high-impact use cases: persona classification to improve routing and messaging relevance, a campaign build assistant to increase speed and consistency, and lead routing quality assurance to reduce mishandled leads. Track success through specific metrics including campaign build time, quality assurance defects, lead response time, MQL-to-SQL conversion rates, and pipeline generated from AI-assisted programs.
Several risks require proactive management: address data fragmentation between Marketo instances through shared taxonomies and regular reviews; overcome limited experimentation culture by implementing small, time-bound tests with visible results tracking; and mitigate compliance and brand risks by establishing prompt and content safeguards with human approval for external communications.
For an enterprise of your scale, consistency and governance are particularly important. The recommendations focus on contained initiatives that minimize risk while demonstrating value. Your existing Marketing Operations Assistant provides an excellent foundation – expand its role as the central repository for standard procedures, approved prompts, and successful pilot playbooks to guide teams effectively.
A structured support plan will accelerate your progress: provide focused training for Marketing and Revenue Operations teams covering practical AI applications, partner with your teams to implement the initial pilots with clear performance measurement, and develop a 6-9 month roadmap that scales successful approaches and connects marketing and revenue teams around shared objectives.
To begin implementation immediately, start with the data audit and the three recommended pilots. Establish biweekly coordination meetings with Revenue Operations and document all findings in your Marketing Operations Assistant to facilitate knowledge sharing. This approach balances quick wins with systematic capability building, positioning you to advance to more sophisticated AI applications as your organization matures.