Sold by: Green Custard
Generative AI offers huge potential, but many organisations struggle to translate ambition into competitive advantage. Siloed systems, unclear use cases, and governance concerns can stall progress before value is realised. Our Gen AI Strategic Assessment provides a structured, four-week engagement that evaluates your current data and AI maturity, identifies high-impact opportunities across the business, and delivers an exec-ready roadmap. The result is a clear strategy for Gen AI adoption that aligns with your goals, prioritises implementation, and manages risk with confidence.
Overview
The Gen AI Strategic Assessment gives organisations a structured way to unlock the potential of Generative AI. Delivered as a focused four-week engagement, the service assesses your current systems, data, and AI maturity before mapping out high-impact use cases across business functions. This ensures your Generative AI roadmap is both practical and aligned with long-term business objectives.
Customers gain a clear strategy for Gen AI adoption that balances innovation with governance, compliance, and risk management. By aligning AI investments with core business goals, the assessment accelerates competitive advantage while reducing uncertainty around scaling AI initiatives. The outcome is an exec-ready AI roadmap with prioritised implementation steps and supporting risk frameworks.
This solution leverages AWS AI/ML Services, including Amazon Bedrock, Amazon SageMaker, and AWS Lambda, as well as data services such as Amazon S3 and AWS Glue to support scalable AI integration. By combining domain expertise with the AWS cloud, the Gen AI Strategic Assessment provides a secure, future-ready foundation for Generative AI adoption at enterprise scale.
Highlights
- Exec-ready roadmap – Clear, prioritised plan for Gen AI adoption at scale
- Business-aligned use cases – Identify high-impact opportunities across departments
- Governance-first approach – Reduce risk with compliance and security built in
Details
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Delivery method
Deployed on AWS
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