- The pace set by rapid advancements in technology, and the increased prevalence of AI forces IT and business leaders to engage in a state of constant evolution.
- Simultaneously, data privacy regulations have become increasingly stringent in an attempt to safeguard personal information from manipulation.
- AI relies on analysis of large quantities of data, and more often than not involves personal data within the data set, posing an ethical and operational dilemma when considered alongside data privacy law.
Data privacy first, AI second. Your organization’s internal and external environment impact not only the integration of AI-based technology but govern the approach to data privacy. By understanding your data privacy environment, you lay the foundation for a streamlined AI implementation.
Impact and Result
- Perspective from a privacy lens on mitigating data privacy risk through IT best practices.
- Guidance on completion of impact assessments that validate the integration of AI technology within the organization’s environment.
- Knowledge around core AI vendor solutions that maintain a privacy-first approach based on integration of explainability.
- Data privacy best practices and how AI technology can support a privacy-proof environment.
- Understanding of the scope of data privacy regulations within the context of the organization.
- Comprehensive outlook around data privacy best-practices that enable effective AI integration.
This guided implementation is a five call advisory process.
Guided Implementation #1 - Evaluate AI through a data privacy lens
Call #1 - Scope requirements, objectives, and your specific challenges.
Call #2 - Discuss AI project pipeline.
Call #3 - Review organization’s privacy and AI drivers.
Guided Implementation #2 - Identify the data privacy posture