The importance of data and AI governance in delivering meaningful customer experiences cannot be overstated. To understand this better, let’s explore the behind-the-scenes journey of a simple consumer interaction through the lens of data and AI governance.

Consider that you are re-evaluating the current subscription plan provided by your telecom services provider. The telecommunications company has deployed a sophisticated chatbot to deliver customer interactions. As you engage with the chatbot, it needs to find and access trusted information about you, including your profile details, location and current plans. This is possible only when the customer relationship management (CRM) systems connected to the chatbot can easily locate and pull together various datasets from a data catalog, which is a centralized inventory of data assets. These applications must be able to find relevant data sets across disparate databases and determine if the information meets quality and compliance standards before relaying it for processing.

As your interaction progresses, the customer analytics and AI systems working in the background will rely on data intelligence to gather further details, such as your usage patterns, billing cycles and more, to build a contextual offer for you. Additionally, as the chatbot delivers its recommendations, multiple data protection and access control policies work in tandem to ensure operations align with applicable data privacy regulations (GDPR, CCPA) and uphold responsible AI standards.

Data management processes and systems must operate like clockwork to drive meaningful customer experiences. A single point of failure can lead to unintended consequences, including reputational damage, loss of customer trust, financial losses and even regulatory penalties.

Organizations increasingly prioritize customer experience (CX) and data governance to improve business outcomes. Informatica’s CDO Insights 2025 survey suggests that 43% of organizations identify improving customer experience as a top priority and 44% indicate data governance as a primary need for increased data management investments.¹

With 88% of consumers expecting assurance that companies handle their personal data responsibly and securely,²  the emphasis on effective and efficient governance of customer data is much needed.

Data and AI governance are pivotal in optimizing customer experience by ensuring customer data is managed as customers expect — accurately, securely and efficiently. Here are a few ways in which a foundation of trusted data enhances customer experience:

• Data quality assurance – High-quality data helps ensure customer insights are based on trustworthy data and improves decision-making accuracy.
• Responsible use of data and AI – Ensuring data is unbiased and maintaining transparency and accountability in AI models used to guide marketing, sales, service and support also helps to deploy responsible AI practices.
• Streamlined data management – Efficient data management processes reduce redundancies and enable quick access to valuable insights that can improve customer services.
• Data protection and compliance – Robust data and AI governance frameworks help safeguard customer data and help businesses adhere to regulatory requirements such as GDPR, CCPA, etc.
• Deeper insights – Establishing and enforcing clear guidelines and policies for governing data and controlling access empowers data users from different customer-facing departments to share data and derive meaningful and actionable insights.

86% of consumers will leave a brand they trusted after only two poor customer experiences.³

As a result, companies are moving fast to elevate their data and AI maturity with AI-powered data governance solutions to generate accurate customer insights, resolve inconsistencies in customer data, improve data quality, mitigate risk exposure and improve responsiveness.

Customer experience can directly impact an organization’s top and bottom lines.

Superior customer data leads to superior customer experiences — and superior customer experiences allow companies to command a premium for their products and services. Engaging with customers more meaningfully across their journey can unlock cross-selling and upselling opportunities while revealing unmet needs to increase wallet share.

It stands to reason then, that reducing redundancies in data and processes, improving data discovery, accelerating access to trusted data and ensuring comprehensive compliance to avoid financial penalties helps serve customers faster and with lower data management overheads.

Let us take a look at five customer experience optimization initiatives companies can execute by upleveling their data and AI readiness.

1) Enhance Customer Trust and Transparency – Customers know that companies capture their data. They demand companies be transparent about the information they gather, set up governance around it to safeguard their details and offer fair value in exchange.

A recent study reveals that consumers prioritize ‘data transparency’ as the top way organizations can build trust regarding the use and protection of personal data.⁴ Data and AI governance mandate transparency in data protection and security measures implemented to capture, store and use customer data. Emerging regulations such as the EU AI Act outline further guidelines on the explainability of AI models and their responsible use.

With modern data governance, companies can gain deep visibility into what data exists, inventory it and discover the data’s lineage and history, sensitivity level and transformations required across the data lifecycle. Transparent, well-defined processes for managing data and AI that demonstrate control and accountability for how customer information is used across the organization help build consumer loyalty to the brand.

2) Generate Reliable CX Outcomes with Generative AI – From creating personalized content to tweaking interactions for anticipating customer behavior and guiding product and service innovations, generative AI (GenAI) presents an immense opportunity to transform CX.

However, demonstrating the return on investment (RoI) of GenAI initiatives has been challenging. 97% of data leaders indicated difficulty demonstrating the business value of GenAI initiatives, with 90% citing data reliability as a barrier to moving GenAI pilots to production.⁵

GenAI models require large volumes of accurate, consistent and unbiased data for training. A data and AI governance framework helps monitor and maintain the data quality standards across data pipelines to prevent GenAI solutions from hallucinating or generating unreliable outcomes. It also helps ensure GenAI solutions comply with data privacy and security regulations and promotes responsible AI governance in customer interactions.

3) Power High-Impact Customer Interactions—The window to delivering impactful customer interactions is getting smaller and smaller. Companies need the responsiveness and agility to meet customers in their preferred channels during interaction, with highly accurate customer insights and then engage them meaningfully for mutually favorable outcomes.

This requires a unified data ecosystem that can break down data silos and deliver real-time, trusted data for CX applications to generate insights and action them. Quick access to relevant and reliable customer data enables companies to provide timely responses and interactions.

A connected data management approach can empower organizations to optimize customer experience delivery for high-impact, timely, data-driven interactions that drive business value and enhance customer satisfaction.

4) Deliver Personalization and Segmentation – Customers expect tailored experiences, which pushes the demand for effective customer data segmentation to deliver more targeted marketing and personalized recommendations. This requires capturing customer data across touchpoints and handling it responsibly. Customer analytics and AI systems need this data to be discoverable, enriched with context, accessible and protected before leveraging it to generate insights.

A robust data and AI governance program helps organizations balance safeguarding customer data's privacy and security exposure and making it available to teams responsible for customer interactions to curate personalized and highly relevant customer experiences.

5) Reduce Customer Acquisition Costs – Customer acquisition costs indicate how much a business spends to attract new customers. Managing and governing customer data is a significant cost component for most organizations.

Applying comprehensive data and AI governance capabilities to drive customer data management best practices significantly reduces costs. Organizations can avoid wasting resources on managing redundant customer data by identifying and eliminating inaccurate, incomplete and duplicate data. Focusing on the most relevant, high-quality data also improves conversion rates by allowing more effective campaign segmentation and targeting.

Streamlining data management processes and leveraging AI-based automation can reduce the time, cost and effort required to access and analyze data for customer initiatives.

Holiday Inn Club Vacations (HICV), a leading brand in the hospitality industry, wanted to drive greater personalization and meaningful customer experiences for clients. However, their customer data was spread across siloed systems, leading to a lack of a comprehensive view and understanding of data quality issues. Establishing data lineage across systems and workflows was cumbersome and manual. Additionally, their data landscape was riddled with inaccuracies and duplicate contacts. Ultimately, it compromised the client’s ability to deliver relevant, personalized experiences.​

Informatica's Intelligent Data Management Cloud (IDMC) helped simplify HICV's data architecture and consolidate customer data from seven main systems into one platform. The cloud-based solution allowed HICV to improve the pace and scale of data ingestion, automate data lineage, apply data quality rules and merge duplicate entities into trusted profiles.​

The client gained a trusted view of customer journeys from start to finish. They could consolidate data into one authoritative source to deliver delightful customer experiences across online and offline touchpoints, building long-term loyalty.​

Informatica's IDMC provides a single, efficient AI-powered environment designed to support your customer experience strategy. It helps companies overcome data silos to create a unified view of customers. IDMC also strengthens data and AI regulatory compliance and enables seamless accessibility to trusted, secure and high-quality data for generating customer experience insights.

IDMC offers integrated data management and governance capabilities, including:

• Data integration to access data from diverse sources
• Data cataloging for inventorying and understanding customer data
• Data quality management to enhance the accuracy and reliability of customer data
• Master data management (MDM) to create an authoritative source of customer information
• Data privacy and access management to handle customer data safely
• Data marketplace to facilitate data sharing and collaboration

For more information on how IDMC can support your CX optimization initiatives, visit https://www.informatica.com/use-cases/customer-experience-optimization.html

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¹ Informatica CDO Insights 2025
²https://business.adobe.com/uk/resources/digital-trends-report.html
³https://www.businesswire.com/news/home/20220202005525/en/86-Percent-of-Consumers-Will-Leave-a-Brand-They-Trusted-After-Only-Two-Poor-Customer-Experiences
⁴https://blogs.cisco.com/security/data-transparency-and-its-impact-on-customer-trust
⁵ Informatica CDO Insights 2025