AI Governance

Empowering Ethical AI Governance with Robust Frameworks and Metrics

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AI Governance

The AI Center of Excellence (CoE) setup focuses on establishing a robust framework and policy metrics for AI governance. This includes the measurement and monitoring of AI initiatives to ensure they align with organizational goals and ethical standards. The CoE also emphasizes the importance of responsible AI practices, ensuring that AI technologies are deployed in a manner that is ethical, transparent, and accountable.

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AI CoE setup

Support Organizations in establishing an AI Center of Excellence (CoE) by leveraging deep expertise in artificial intelligence and digital transformation. This includes setting up the right skills and governance frameworks necessary for success, such as identifying key talent, providing targeted training, and implementing robust governance structures

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Framework and Policy

Help organization establish AI frameworks and policies including data governance, Responsible & ethical AI policy and compliance to regulatory standards.

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Metrics, Measurement & Monitoring

Design and establish metrics for measuring adoption and success at an output and outcome level. Integrate continuous improvement and monitoring for enhancing the AI environment and ensuring ROI.

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Responsible AI

Design and establish metrics for measuring adoption and success at an output and outcome level. Integrate continuous improvement and monitoring for enhancing the AI environment and ensuring ROI.

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Case Studies & Success Stories

AI-Powered Acceleration in Biologic Research

Avasant developed a custom AI solution to streamline vaccine and biologic countermeasure development, supporting global efforts against epidemic and pandemic threats. The initiative has secured over $4 billion in contributions and pledges, reinforcing its impact on public health innovation.

Optimizing the Call for Proposal (CfP) Process

Avasant’s AI consulting services reimagined the CfP evaluation process, leveraging AI-driven insights to enhance proposal assessment, reduce manual effort, and improve decision-making.

Time Savings

Reduced evaluation time from 5 months to just 3 months, expediting critical funding decisions.

Process Efficiency

Streamlined proposal reviews, cutting time and effort by up to 21 months in cumulative cycles.

Quality Enhancement

Improved decision accuracy, minimized evaluation bias, and optimized funding allocation for high-impact projects.

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