Enterprise:
Enterprise AI Strategy and Target Architecture
- Define and maintain the enterprise AI target architecture, transition architectures, capability model, platform strategy, and multiyear architecture roadmap.
- Translate business strategy and operating priorities into executable AI capabilities, architecture investments, and delivery sequences.
- Establish the architectural direction for generative AI, agentic AI, machine learning, intelligent automation, AI-assisted decision-making, and AI-enabled business processes.
- Define clear boundaries and relationships between enterprise AI platforms, domain solutions, shared services, data platforms, enterprise applications, and external AI providers.
- Ensure that project-level AI decisions support enterprise scalability, interoperability, security, reuse, and long-term maintainability.
- Identify opportunities to consolidate overlapping technologies, eliminate duplicated capabilities, and prevent uncontrolled AI platform and vendor sprawl.
- Develop architecture options and recommendations that explicitly address business value, delivery speed, cost, risk, technical debt, vendor dependency, and operational complexity.
- Maintain a current enterprise view of AI capabilities, platforms, models, agents, integrations, data dependencies, vendors, risks, and strategic initiatives.