At the heart of AI governance is the AI model. At the heart of the AI model is trusted data. To be successful with AI governance, organizations must build from a strong data governance foundation.
First San Francisco Partners (FSFP) views artificial intelligence governance and data governance as two sides of the same coin. Therefore, AI governance is an evolution — not a revolution — from data governance and should not be built in a silo.
FSFP’s approach to AI governance focuses not just on designing the future-state framework, but also on the space between — building pathways to mature an organization’s current-state data governance program for AI and AI governance enablement.
AI governance is the organizing framework for establishing the strategy, objectives and policies for responsibly managing AI tools, technologies and models while ensuring proper velocity and controls in support of organizational goals.
As AI lives and dies by the data, the two must be united under a holistic framework to drive transformational change at the value chain level.
FSFP helps organizations to:
- Establish an AI governance strategy with line-of-sight to organizational goals
- Design operating models that break down organizational silos and facilitate mutually beneficial decision-making for data and AI
- Identify and define core skillsets, roles and responsibilities required for ethical AI success
- Create and deliver executive literacy programs and define AI governance training plans focused on employee development, reskilling and upskilling
- Build a principled approach to policy development that guides responsible AI efforts
- Establish human-in-the-loop controls to ensure technological alignment with business expectations, desired outcomes, and regulatory considerations
- Embed data and AI into risk management frameworks to reflect its value as a strategic asset
- Evolve the focus of governance from critical data elements to digital and data products
- Plan for the enterprise-wide change required to drive large-scale transformations
- Design KPIs and reporting mechanisms to track delivered business value, cost containment, operational efficiency, technical debt and risk exposure
- Define business value cases and develop proof-of-concepts for AI projects
- Uncover business requirements for data to drive self-service across the enterprise and build extensible data models and blueprints that support an interconnected technology ecosystem
- Identify prescriptive metadata requirements for governing AI and delivering trusted, transparent outcomes
- Define a new paradigm for the quality measurement of unstructured data for AI models
Guiding Business Leaders to AI Success
Trusted data is the intersection of data governance and AI governance — the result of one and the input to the other. FSFP’s Modern Data and AI Enablement Framework allows organizations to leverage their existing data governance capabilities to jumpstart AI success.
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