Collibra has recently unveiled its latest product, Collibra AI Governance, aimed at assisting organizations in deploying trusted AI securely and efficiently. The new product, integrated with the Collibra Data Intelligence Platform, facilitates collaboration among data, AI, and legal teams to ensure adherence to legal and privacy regulations, mitigate data risks, enhance model performance and return on investment, and expedite the time to production.
With the increasing pressure on organizations to harness AI as a competitive edge, a recent IDC survey revealed that 71% of respondents are already utilizing AI, with an additional 22% planning to do so in the next 12 months. Companies that have effectively implemented AI initiatives have reported a 3.5x return on their investments. However, without proper governance and a comprehensive understanding of the underlying data, deploying AI can lead to unfavorable outcomes such as model bias, inaccuracies, legal and ethical implications, trust issues, and more. The repercussions may include reputational damage and regulatory fines if AI models do not perform as expected. Collibra AI Governance bridges this gap by providing a purpose-built mechanism to securely govern AI and its underlying data through established rules, processes, and responsibilities.
Laura Sellers, Collibra’s Chief Product Officer, emphasized the challenges faced by organizations looking to prioritize or already heavily invested in AI. Concerns regarding the unpredictable nature of AI, alongside barriers like time, resources, errors, legal issues, and data security, have prompted the development of Collibra AI Governance. This platform aims to allay the concerns of CIOs, CDOs, data leaders, and legal teams by offering a unified solution to govern AI and its supporting data through automated workflows, processes, and policies, ensuring trusted AI implementation across the organization.
Collibra AI Governance empowers enterprises to deliver more valuable, ethical, responsible, and compliant AI by enabling the following capabilities:
1. Defining and documenting AI use cases easily: AI projects can be managed and monitored through an intuitive, business-user-friendly interface.
2. Tying AI directly to data for greater understanding and transparency: Link AI use cases to the data they rely on, incorporating continuous data quality checks and best-in-class governance capabilities.
3. Guarding sensitive data: Integration with Collibra Data Privacy and Collibra Protect aids in identifying and safeguarding sensitive data, such as personally identifiable information, through data discovery and access policies.
4. Connecting business context to the data supporting AI: Enhanced project data with details like goals, business value, and team roles to ensure alignment, collaboration, and transparency.
5. Ensuring regulatory and legal compliance: Assign risk ratings across various categories to facilitate triage and review of contentious projects.
6. Providing visibility and monitoring throughout the AI use case lifecycle: Enable CIOs, CDOs, and legal teams to understand data provenance, model trustworthiness, track ROI, and monitor business value.
Dan Yu, SVP of Marketing and Solutions, Data and Analytics at SAP SE, highlighted Collibra AI Governance as a critical component in ensuring the ethical and responsible use of AI across organizations’ data landscapes. The ultimate goal is to promote trusted data and drive trustworthy AI, positioning Collibra as an integral part of the business data fabric architecture.