Is Your Data Ready for AI? Why Data Quality and Governance Matter in Automotive — and How Informatica Can Help
As the automotive industry accelerates toward AI-driven innovation, there’s one critical question every leader should be asking: Is our data ready for AI? From enhancing customer experiences to optimizing supply chains and even enabling autonomous vehicles, AI is reshaping how we build, market and use cars. But here’s the catch: AI is only as powerful as the data it relies on. Without robust data quality and governance, even the most advanced AI models can lead to costly errors, inefficiencies or compliance issues — outcomes no automotive company can afford.
Why AI Needs High-Quality Data to Succeed
First things first: AI depends on accurate, reliable data. In an industry where precision matters, poor data quality can have major consequences. Imagine a driver-assistance system that makes decisions based on inaccurate sensor data, or a marketing AI tool that misreads customer preferences due to inconsistent data. In cases like these, the risks impact not only customer satisfaction but also safety, brand reputation and regulatory compliance.
In fact, according to Gartner® “At least 30% of generative AI (GenAI) projects will be abandoned after proof of concept by the end of 2025, due to poor data quality, inadequate risk controls, escalating costs, or unclear business value.”1 Think about that for a moment. Companies are investing heavily in AI infrastructure only to see projects stall — or even backfire — because their data wasn’t good enough. Clearly, prioritizing data quality and governance is more than just a “nice-to-have”; it’s essential for making sure AI initiatives deliver real value.
What Data Quality and Governance Bring to the Table
So, why exactly are data quality and governance so crucial? Let’s break it down:
- Accuracy and reliability: High-quality data helps ensure that AI systems make accurate, data-driven predictions and decisions. This is crucial for automotive applications like predictive maintenance, inventory forecasting and personalized marketing. With accurate data, you reduce errors, improve operational efficiency and enhance customer satisfaction.
- Compliance and risk reduction: In an industry with strict safety and regulatory standards, inconsistent or incomplete data can create serious risks. Data governance frameworks help ensure data meets regulatory requirements and can be trusted, reducing compliance risks and safeguarding brand reputation.
- Scalability: For AI to scale successfully across an organization — from R&D to customer service to manufacturing — data governance needs to be in place. Strong data governance means that AI models can access clean, consistent data, enabling seamless scaling across different departments and applications.
What Industry Analysts Are Saying
The need for quality data and governance in automotive AI isn’t just a trend, it’s a widely acknowledged best practice backed by industry thought leaders. Here’s what the experts have to say:
- McKinsey: In a recent report on AI in the automotive industry, McKinsey underscores that data quality is essential for effective AI applications, from customer personalization to predictive maintenance. Poor data quality, McKinsey notes, can erode AI’s accuracy and lead to costly or even dangerous mistakes.2
- Gartner: According to Gartner “At least 30% of generative AI (GenAI) projects will be abandoned after proof of concept by the end of 2025, due to poor data quality, inadequate risk controls, escalating costs or unclear business value.”3
In our view, the stakes are high, and automotive is no exception. Inaccurate or incomplete data can directly impact safety, compliance and customer experience.
- Deloitte: Deloitte has found that organizations with strong data governance are far more likely to achieve reliable AI outcomes. They emphasize that data governance is not optional but foundational to any organization seeking to deploy AI responsibly and effectively.4
How Informatica Supports Automotive Data Quality and Governance
Informatica is a leader in data management solutions, and our suite of tools is designed to help automotive companies establish robust data quality and governance frameworks. These tools help ensure that AI initiatives are built on a foundation of clean, reliable and compliant data.
Here’s how Informatica can help automotive organizations:
- Automated Data Quality: Informatica AI-powered data quality solutions automatically identify, clean and standardize data across the enterprise. This means data is reliable and consistent, reducing errors and improving the accuracy of AI-driven insights.
- Business outcome: With automated data quality, companies can increase operational efficiency, enhance customer experiences and reduce costly errors in AI outputs.
- Data Governance and Compliance: Informatica data governance solutions enable organizations to enforce data standards, ensuring data integrity and compliance with industry regulations. With Informatica Data Catalog, data assets are fully traceable and auditable, which is essential for regulatory adherence in areas like safety standards and customer data privacy.
- Business outcome: Effective governance minimizes compliance risks, reduces regulatory fines and builds customer trust, especially important in customer-facing or safety-critical applications.
- Scalable Data Integration: Informatica Data Integration and Engineering allow companies to unify data from diverse sources — whether it’s IoT data from connected vehicles, supply chain information or customer profiles — into a single, clean and accessible source of truth. This integrated data foundation is essential for scaling AI applications across the organization.
- Business outcome: Scalable data integration enables organizations to deploy AI at scale across functions, from R&D to customer service, creating more streamlined, data-driven decision-making processes.
- Data Governance Automation with AI: Informatica uses AI to automate governance processes, tagging and managing data in real time. Informatica Data Governance, Access and Privacy allows companies to respond quickly to regulatory changes or shifts in business needs, ensuring their data governance remains relevant and adaptive.
- Business outcome: Automating governance allows for faster, more agile responses to compliance requirements and evolving business goals, reducing the manual workload and making data governance sustainable in the long run.
Is Your Data AI-Ready?
So, here’s the big question: Is your data AI-ready? If not, it might be time to consider a data quality and governance strategy that can handle the demands of automotive AI. The right data foundation not only enables your AI models to deliver accurate and actionable insights but also ensures that your systems meet regulatory standards and protect brand reputation.
Next Steps: Get Your Data AI-Ready with Informatica
As AI reshapes the automotive landscape, companies that invest in data quality and governance will be well-positioned to lead the industry forward. Are you ready to unlock the full potential of AI with reliable, high-quality data? Informatica data management solutions can help you build a data strategy that drives real business outcomes — from operational efficiency to customer trust and regulatory compliance.
Let’s make sure your data is as reliable as the cars you build. After all, when AI drives the future, high-quality data is the fuel that makes it all possible. Visit www.informatica.com to learn more.
1Gartner Press Release, “Gartner Predicts 30% of Generative AI Projects Will be Abandoned After Proof of Concept by End of 2025,” July 29, 2024, https://www.gartner.com/en/newsroom/press-releases/2024-07-29-gartner-predicts-30-percent-of-generative-ai-projects-will-be-abandoned-after-proof-of-concept-by-end-of-2025. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.