Many AI initiatives fail because there’s no plan for scale and maintenance. Has your organization already deployed AI/ML models and you’re looking for proven ways to maintain it? Working with some of the world’s largest and most complex organizations, EK has helped stand up dozens of AI Centers of Excellence (CoE). As a result, we have developed an AI/ML Model Quality Evaluation Matrix to help organizations with large AI initiatives and transformation applications to assess model performance, drift, scalability, safety, and security. EK’s AI quality and governance experts will work with your organization to ensure that your AI solutions will evolve and scale to fit your needs, developing robust processes to ensure data integrity, security, and evolution over time.
Approach
EK will begin by conducting a model assessment and gap analysis, inventorying and evaluating existing AI solutions, performance, and applications in alignment with your organization’s strategic objectives. This will result in recommendations for more effective model alignment, monitoring, and operations. EK will assess the current quality of your organization’s AI/ML models across six dimensions:
- Accuracy/Reliability
- Usability
- Performance
- Drift
- Sustainability
- Security
EK will then leverage our library of AI and data governance templates to develop an integrated governance model in close partnership with your subject matter experts (SMEs), existing technical processes, and training mechanisms to guide ongoing AI model and data quality efforts. These efforts will be driven by the supporting metrics, policies and procedures, and roles and responsibilities necessary to grow with your evolving needs over time.
As an additional value-add, EK will develop and deliver standard and role-based training and learning paths for all levels of users and support staff based on identified skills and knowledge gaps.
Engagement Outcomes
By the end of the AI Model Quality Assessment & Governance Framework engagement, your organization will have:
- Inventory and understanding of the current AI initiatives and performance deployed or in use within the pockets of your organization.
- A roadmap outlining short-term, mid-term, and long-term tasks targeted towards improving your AI practices and model quality.
- Insight into best practices for maintaining a more sustainable and performant model, as well as governance and alignment with the business, over time.