Data intelligence company Alation has laid down the automation intelligence law with its latest AI governance tool. In the rush to create all forms of AI (and let’s remember that predictive, reactive and a host of other strains sit alongside new generative functions), organizations clearly need a way to ensure their AI models are developed using secure, compliant and well-documented data. That’s the angle that the company is coming from with its governance offering.
This approach to AI governance stems from a data provenance analysis and control aspect in the first instance. It offers capabilities such as data lineage for AI auditability (where did that dataset come from anyway and who put it there?), AI documentation (as it sounds), data discovery and custom tagging (an ability to tag data objects with the name of a job, department or other entity to make them more searchable) and data quality flags.
Confidence To Create
With all those functions in place, Alation argues that organizations can more confidently conduct AI development, mitigate risks and optimize their AI investments.
“The potential for AI to revolutionize industries – from preventing financial fraud to accelerating drug development – is immense, but realizing that potential and driving true business value depends on trusted, high-quality data,” said Satyen Sangani, CEO and co-founder of Alation. “Alation’s AI Governance solution ensures AI initiatives are built on secure, compliant and transparent data, enabling faster innovation with confidence. As enterprises continue to invest in AI infrastructure to scale large models, Alation turns those investments into real-world applications that deliver measurable ROI, reduce risk and scale AI safely and ethically.”
As the penetration of AI deepens (and indeed widens), we might stop to ask whether these processes are actually getting tougher. Alation says they are and points to the chasm effect as organizations struggle to scale AI applications beyond proof-of-concept stages. This is the point where data environments grow and regulatory demands rise.
Research from McKinsey suggests that as few as 11% of organizations have successfully scaled these AI initiatives, largely due to challenges in data governance, compliance and security. Evolving information regulations across Europe, the Americas and beyond such as GDPR, the EU AI Act and frameworks like the OECD AI Principles and NIST AI Risk Management Framework, further complicate governance requirements.
IDC analyst Stewart Bond has lauded Alation for what he calls the delivery of the “critical guardrails” required to help keep AI initiatives safe, ethical and compliant. For Bond, it’s all about the ability to track and validate data before it feeds into AI models while supporting model development, documentation and wider validation exercises.
How Alation Works
By cataloging AI training datasets, large language model prompts, AI models and application programming interface (API) endpoints in one unified platform, Alation says it can ensure traceability across the AI ecosystem, enabling compliance and fostering collaboration.
“This transparency mitigates AI risks by allowing teams to trace errors, correct biases and maintain accountability throughout the AI lifecycle. With curated features ensuring data quality and best practices like model card (see below) documentation, Alation streamlines AI development, accelerates time-to-value and delivers governed collaborative AI outcomes. By reinforcing trust and explainability, Alation helps enterprises future-proof and centralize their AI efforts,” noted the company, in a press statement.
NOTE: A common enough term in machine learning, a model card works a lot like a food nutritional label. It provides a data sheet detailing how an AI model is supposed to work, how it is intended to perform and what training data was used to build the model. This function helps AI software engineers to understand the biases, behaviors and characteristics of a machine learning model as it starts to work for the AI use case in hand. Alation provides a single source of truth for documenting and managing AI models using model card templates.
The Alation AI and data governance framework flags non-compliant datasets and ensures AI models are built on reliable, governed data. This is intended to mitigate operational risks, prevent costly errors and safeguard data integrity so that organizations can meet the highest regulatory standards
The company also offers an AI Readiness Accelerator, an expert services offering designed to speed up AI adoption by providing expert guidance and best practices for model card development. Customers can also engage system integrators from the Alation ecosystem to implement these practices, ensuring they are prepared to scale AI initiatives and deliver measurable business impact.