Spotlight
Best Practices in Developing and Governing Enterprise AI
Intelligence by Iteration – AI’s Software Path
As organizations invest in leveraging the capabilities of AI, establishing AI governance is an essential first step. It also involves acknowledging that long-standing best practices from enterprise software development—particularly the Software Development Life Cycle (SDLC)—can serve as a valuable foundation for AI development.
This white paper explores how organizations can shift from proof of concept to production by applying foundational software development principles to AI initiatives.
"Companies that have already implemented a good privacy program are probably well positioned to leverage AI effectively because they already understand their data landscape and so have a great opportunity to think even more critically about their data and where they can drive value for the organization."
"It may be beneficial for organizations to revisit their overall compliance program to ensure a solid, compliant, robust, and effective foundation for the further use of generative AI."
Related Resources
White Paper
AI Readiness Through Effective Information Governance in Microsoft Environments
In the rapidly evolving landscape of artificial intelligence, generative AI is becoming a disruptive force, reshaping how machines interact with and create content. Advancements in this space offer the potential to unlock unparalleled benefits ranging from speeding up content production to enhancing, streamlining and automating processes. Nevertheless, the rise of generative AI can also pose a significant risk if the underlying information and workflows are poorly governed. Insufficient AI governance can lead to an array of problems, such as biased outputs, data protection vulnerabilities and the potential for making inaccurate or incomplete decisions based upon on out-of-date information.
White Paper
Data Classification in Microsoft 365 and Pragmatic Copilot Adoption
As artificial intelligence transforms the use of enterprise technologies, a foundation of robust data governance has never been more critical. Establishing a data governance framework that is resilient against AI risks and flexible to ongoing technological change involves a series of steps, many of which were outlined in a previous FTI Technology white paper, “Getting AI Ready through Effective Information Governance.”
Blog Post
Q&A: Guardrails for Third-Party AI Tools
As organizations look to leverage the power of artificial intelligence across the enterprise, privacy and governance professionals are working to establish program guardrails. When implementing third-party software, unique considerations and controls are needed to uphold strong governance and risk management. In this Q&A, Dera Nevin, Managing Director, and Tracy Bordignon, Senior Director, in FTI Technology’s Information Governance, Privacy & Security practice, discuss approaches to assessing third-party AI risk and mitigation strategies.
Webinar
Bridging Legacy Data, Defensible Disposition, and AI-Driven Insights
Organizations face mounting challenges when it comes to managing legacy data across outdated platforms while meeting evolving legal and compliance demands.
Webinar
Beyond Cleanup: Turning Defensible Data into AI-Ready Insights
This webinar is a continuation of the discussion in Part 1 of this 2-part series on bridging legacy data, defensible disposition, and AI-driven insights and covers transforming legacy and unstructured data into AI-ready insights. The panel discusses the importance of data remediation, ethical AI application, and real-world use cases in legal and compliance contexts.