How does data and AI governance drive GenAI success?
Trusted outcomes with a secure and responsible approach
Govern your data to enable innovation and manage risk
While AI is tremendously appealing, it also has the potential to wreak havoc if not properly guided and managed. Appropriate guardrails and governance must be set from the start for AI to function as a trusted companion. It is critical that these guardrails appropriately strike the balance between managing risks and enabling sustained innovation and growth.
Kyndryl's experts offer a first-hand perspective on designing, implementing, and operating generative AI solutions while prioritizing data governance, integrity, and AI policies.
how kyndryl helps
We help you establish robust governance and oversight to ensure responsible development and deployment
You have questions. We have answers.
AI governance is a collection of best practices, policies, processes, tools, rules, and frameworks. These collective standards work as guardrails for AI technologies being developed, deployed, used and managed, and help ensure that the AI ensures safety, fairness, and respect for human rights, and otherwise minimizes potential risks and maximize benefits and harm prevention.
Data governance enables an organization to ensure that high data quality exists throughout the complete lifecycle of the data, and data controls are implemented that support business objectives. It provides all data management practices with the necessary foundation, strategy, and structure needed to ensure that data is managed as an asset and transformed into meaningful information.
Governance is a central tenet of data modernization, but many organizations lack the tools, structure, management commitment, and experience to establish, evolve, and enforce a formal data governance framework.
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