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Five drivers of AI readiness
Business strategy
Technology and data strategy
Technology and data strategy
- The first step in any AI business strategy is to determine what you’re solving for.
- Clear business goals for AI promote alignment of AI projects to strategic objectives—such as efficiency and revenue generation.
Technology and data strategy
Technology and data strategy
Technology and data strategy
- The data & infrastructure needed to deploy AI at scale.
- While aligning AI projects with organizational objectives is key to building a business case for AI, technology and data strategy makes it possible to progress from proof of concept to production and, eventually, scale.
AI strategy and experience
Technology and data strategy
AI strategy and experience
- The organization’s understanding of, experience with, and processes to support AI at scale.
- It’s (mostly) about the use cases
- AI expertise and repeatable processes to create sustainable value
Organization and culture
Organization and culture
AI strategy and experience
- Leadership vision, operating model, skills, resources, and culture
AI governance
Organization and culture
AI governance
- Processes, controls, and accountability structures to govern data privacy, security, and responsible use of AI
Deployment
Build personal agents
Cross-organizational agents
Business process agents
Business process agents
Cross-organizational agents
Business process agents
Organizational agents
Cross-organizational agents
Cross-organizational agents
Cross-organizational agents
Cross-organizational agents
Cross-organizational agents
Enrich employee experiences
Reinvent customer engagement
Reinvent customer engagement
Reinvent customer engagement
Reinvent customer engagement
Reinvent customer engagement
Reshape business processes
Reinvent customer engagement
Bend the curve on innovation
Bend the curve on innovation
Reinvent customer engagement
Bend the curve on innovation
AI is shifting business for our customers
Enable customer transformation, increase revenue, and manage costs
Responsible AI Principles
Fairness
AI systems must be developed to treat all people fairly.
Reliability and safety
AI systems must be designed to perform reliably and safely.
Privacy and security
AI systems must comply with privacy laws.
Inclusiveness
AI systems must be designed to address a broad range of human needs and experiences.
Transparency
AI system behavior and functional components should be understood so that people can identify potential issues or unintended outcomes.
Accountability
People who design and deploy AI systems must be accountable for how their systems operate.