5 Ways to Unleash Business Value with AI-Powered Data Management
Generative AI (GenAI) deployments are fast advancing beyond experimentation and pilots to value creation and delivering tangible business outcomes.
39% of the respondents in McKinsey’s 2024 global survey on AI indicated decreased operational costs and 44% indicated increased revenue from generative AI adoption.1
From streamlining processes and automating resource-intensive tasks for efficiency gains to helping businesses develop newer, enhanced products and services quicker, GenAI use cases are expanding rapidly across business functions and becoming a source of competitive differentiation for organizations.
Data Trust Deficit Thwarts AI-Driven Value Generation
Informatica’s recent survey of chief data officers, “CDO Insights 2024: Charting a Course to AI Readiness,” revealed that 99% of AI adopters encounter data quality, data privacy and protection and AI governance roadblocks in their AI journey.2
To accelerate business outcomes with AI, companies must ensure that the data fueling AI applications is high-quality and protected against privacy and security vulnerabilities throughout their lifecycle. Organizations also need to handle large-scale data in compliance with emerging AI regulations such as the EU AI Act and the Biden Administration’s Executive Order.
Governing large volumes of data across complex landscapes through legacy, fragmented and manual processes is not feasible. Organizations need modern data governance solutions that deliver predictive data intelligence and help build a trusted data foundation to drive business value from AI programs.
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Our eBook, "AI-Powered Data Governance: How to Scale Digital Business with Trusted Data and AI," outlines AI’s data challenges and how companies can leverage modern data governance to accelerate AI readiness. Explore key capabilities and examples of how clients have leveraged AI-powered data governance to drive business outcomes. Download now!
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Unleash Business Value with AI-Powered Data Governance
Every person in an organization uses data at some point in their daily work to make decisions and complete tasks. AI-powered data governance solutions can remove dependencies and bottlenecks on data teams and make high-quality and effectively governed data available and accessible securely across the enterprise. This helps build trust with data and empowers users to leverage AI with confidence.
Below are five ways in which AI-powered data governance can accelerate business value and improve outcomes.
1) Deliver Superior Customer Experiences – Extracting maximum value from customer data begins with tackling challenges such as data quality, data access, and data governance. Putting customer data together from multiple channels and in various stages of completeness and correctness to unlock deep, accurate customer insights and deliver engaging customer experiences can be daunting.
AI-powered data governance allows companies to identify and integrate customer data, often spread across data silos, to help ensure the most relevant and updated data is used in analytics and AI applications. Implementing master data governance for customer data helps create a single, standardized, authoritative source of data across the enterprise, leading to effective personalization and experience management while helping ensure data privacy and adherence to protection guidelines.
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Brazil’s electric power regulator ANEEL leveraged Informatica to improve customer service efficiency by 35% through centralizing, enriching and improving the quality and governance of its data. Read the full story here.
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2) Accelerate Time to Insights — Faster time to insight allows organizations to swiftly explore new opportunities and act on them with data-driven decisions. The disparate, diverse and inconsistent nature of business data often makes extracting conclusive insights tedious and time-consuming. Dependencies on IT teams for identifying and accessing the most relevant data assets for analysis can create bottlenecks that postpone data analysis and the generation of insights. Further, inconsistent data entry standards, insufficient metadata information, and a lack of business context add to the time and effort required to curate data for analysis.
Intelligent metadata management enhances data discovery, which shortens the time it takes to find and curate relevant data. This allows data users to focus on high-impact, value-adding tasks while relying on automation for routine manual-intensive ones. Data lineage capabilities provide full visibility into where data originates and its journey through various processes, enabling teams to understand its context and quickly diagnose and remediate issues. Streamlining and standardizing data-handling processes across the organization helps maintain the usability of data and enhances its readiness for AI. A centralized data marketplace can enable data consumers to gain easy, timely self-service access to verified data products, accelerating their data to insights journey.
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Providing data with greater agility and quality for business areas helped Banco ABC Brasil accelerate credit approval by 70% with Informatica. Read the full story here.
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3) Explore Growth Opportunities with Better Insights – Companies rely on data-driven insights for decisions such as entering new markets, improving products and services to meet unmet customer needs, identifying cross-sell and upsell opportunities and responding to market changes with agility. However, as data volumes grow, companies struggle to manage the increased complexity of data and maintain its integrity for use as a strategic asset.
Integrated, AI-equipped data governance tools enable companies to utilize high-quality, trustworthy and protected data to unlock unique insights to plan strategies, predict trends and make precise operational decisions. Innovations such as CLAIRE GPT aim to democratize the power of GenAI and provide intelligently guided data experiences that help users generate deep, data-driven insights regardless of their technical expertise.
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Vonovia SE, Germany's leading housing company built a foundation of trusted data with Informatica's AI-powered Intelligent Data Management CloudTM (IDMC) platform to harness competitive advantage. Read the full story here.
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4) Reduce Data Operations Costs – Training and operating AI models require large volumes of high-quality data. As the data sets grow more complex, the costs for identifying, integrating, labeling, cleaning, organizing and processing data before AI algorithms can use it can quickly spiral.
AI-powered data management solutions help leverage automation to catalog, classify, govern and protect data. This helps reduce the need for manual intervention, decrease labor costs and reduce the likelihood of incurring costs due to data errors. Robust data governance policies can reduce data redundancies, meaning less data must be stored, backed up and analyzed. Defining and implementing data access and security measures at scale protects sensitive information and reduces the financial risks associated with data breaches.
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Informatica helped TelevisiaUnivision improve decision-making across virtually every line of business and cut enterprise integration costs by 44% alone. Read the full story here.
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5) Reduce Risk Exposure and Avoid Legal Penalties – The rise in GenAI adoption has accelerated data privacy, security and governance risks. Governments and regulatory bodies worldwide are implementing regulations around the use of AI and companies need to align with these regulations to ensure compliance. Companies prioritizing responsible AI practices are better positioned to build customer and stakeholder trust and avoid data misuse, regulatory penalties and compliance litigation.
Ensuring the availability and accessibility of high-quality, safe and protected data helps drive reliable and trustworthy AI outcomes while mitigating privacy, security and compliance risks. AI-powered modern data governance helps quickly locate and classify sensitive information, enforce relevant data protection policies, and identify and rectify potential compliance violations, thereby reducing the risk of legal penalties.
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HTLF leveraged the Informatica cloud platform to enable cost-effective, AI-fueled growth and establish a robust data foundation that enhanced trust in their banking operations. Read the full story here.
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Trust Your Data to Deliver Optimal Business Outcomes
Traditional data management systems often struggle to keep up with the rapid expansion of data volume, variety and velocity that characterizes modern digital businesses.
AI-powered data governance helps build a trusted data foundation, which serves as the cornerstone for effective decision-making for scaling digital businesses by helping ensure accuracy, consistency and reliability in AI outcomes.
Next Steps
The eBook AI-Powered Data Governance: How to Scale Digital Business with Trusted Data and AI highlights how companies can leverage modern data governance capabilities to overcome the complexities of getting data ready for AI and maximize its value. Download.
1https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
2CDO Insights 2024: Charting a Course to AI Readiness
