Thinking of data as a strategic business asset isn’t new. Just look back to the era of Big Data, now decades old. What’s changed? Well, data has evolved into a globally accessible asset that can be utilized in new and creative ways, especially as fuel for AI and agentic transformation.
A recent report from thought leadership agency FT Longitude, commissioned by Boomi, highlights the critical importance of robust data management practices as organizations strive to harness AI’s full potential. This blog summarizes some of the report’s key findings, explains why they matter, and illustrates how Boomi can help organizations navigate these challenges effectively.
Data Management Is Crucial to Effectively Employing AI
“The State of Data Management for AI: Lessons From 300 Data Leaders Scaling AI” reveals a fundamental truth: “There’s no AI without data.” As organizations deploy AI technologies, reliable and efficient data management processes create the foundation for success. While over 70% of companies surveyed expressed confidence in their data management practices, many still rely on manual processes. Manual processes have never scaled easily. Adding AI to the manual process mix simply makes scaling more important — and less achievable.
Ignore Data Management at Your Peril
As AI systems become more integrated into business operations, the quality and consistency of the data feeding these systems directly impact their effectiveness. Companies that fail to prioritize data management risk inaccuracies that can lead to poor decision-making, wasted resources, and damaged reputations. In other words, don’t feed your AI systems junk food!
The report also indicates that while 77% of respondents trust the accuracy of the data their AI systems rely on, only half trust the overall quality of their organizational data. This discrepancy highlights a critical gap that organizations must address to ensure the reliability of their AI initiatives.
Build Trust in AI Through Data Governance
To build trust in AI models, organizations must establish strong data governance and management processes. The report emphasizes that many companies are aware of this need but often prioritize data processes over other essential aspects of AI development, such as ethics and bias detection.
For instance, Ranajay Nandy, Vice President of Data and Analytics at Citizen Watch Group, underscores the importance of a robust data management strategy. His organization recognized that inaccurate data posed a significant business risk and took proactive steps to ensure data hygiene. This approach is echoed across the report, which suggests that while some data management tasks are automated, many still require human oversight to maintain accuracy and compliance. This also aligns with Boomi’s approach to agentic transformation: Always Keep a Human in the Loop.
The Challenge of Manual Data Management
Though manual data management is never advisable, it may work in the short term. But as a policy, it becomes increasingly unsound as organizations scale their AI efforts. As AI models evolve, the potential for bias and inaccuracies grows. Companies must transition to more automated and centralized data management solutions to mitigate these risks.
In the report, Director and Digital Consulting Architect at Huron Kevin Thompson advocates a dual approach of automation and centralization to support AI readiness. By centralizing data flows, organizations can ensure that their decision-making processes are based on a comprehensive and accurate dataset, ultimately leading to better business outcomes.
Empowering Data Management for AI
At Boomi, we understand the challenges organizations face in managing their data effectively. Our platform offers a comprehensive suite of tools designed to streamline data integration, centralization, and automation. Here’s how Boomi meets the challenges highlighted in the report:
- Automated Data Integration: Boomi’s integration capabilities allow organizations to connect disparate data sources seamlessly, ensuring that AI systems have access to high-quality, up-to-date information.
- Centralized Data Management: The Boomi platform enables businesses to create a unified view of their data, facilitating better governance and oversight. This centralization is crucial for maintaining data accuracy and consistency across the organization.
- AI-Powered Data Governance: Boomi leverages AI to enhance data validation processes, reducing the need for manual checks while ensuring that data quality remains high. This approach allows organizations to focus on strategic initiatives rather than slogging through routine data management tasks.
- Scalability and Flexibility: As organizations grow and their data needs evolve, Boomi’s platform can scale accordingly, providing the flexibility required to adapt to changing business environments.
The Path Forward
The findings from the FT Longitude report should come as no surprise. They simply laser-focus on what most organizations already know: that they should prioritize data management as they scale their AI initiatives. As AI continues to transform industries, those who establish a strong data foundation will be better positioned to leverage its full potential. Boomi is committed to helping organizations ensure that they can trust their data and make informed decisions based on that data with confidence.
Read “The State of Data Management for AI: Lessons From 300 Data Leaders Scaling AI” for more data from business leaders working to safely implement and scale AI within their organizations.