How Galileo used the QS AI Capability Self-Assessment to transform scattered AI initiatives into a strategic roadmap

Like many higher education institutions, Galileo Global Education Italia had embraced AI as a strategic priority. However, despite having an AI strategy in place, the institution faced a common problem: AI initiatives were emerging across departments without coordination.

"At the beginning, we did have an AI strategy, but we realised that many initiatives were emerging across departments without a coordinated approach," explains Fabio Siddu, Chief Transformation Officer.

Without a structured framework, the institution lacked visibility into:  

• Which AI tools were already being used across the organisation

• The maturity level of existing AI efforts

• Untapped opportunities for AI application

• A clear roadmap for prioritising AI investments

How the QS AI Capability Self-Assessment brought structure

Galileo turned to the QS AI Capability Self-Assessment to bring structure to their AI journey. The process provided a systematic approach to evaluate AI readiness across the institution.

"The framework helped us to focus on the state of our AI initiatives, giving us a structured way to navigate a complex topic and focus on what really mattered. Through the self-assessment process, we mapped our existing AI powered tools identifying processes that could benefit from AI, collected documentation to formalise and promote the adoption of these tools. "

Other key activities during the assessment included:

1. Process Identification: Pinpointed processes that could benefit from AI integration

2. Documentation: Formalised and promoted adoption of existing AI tools

3. Maturity Assessment: Evaluated the development stage of each AI initiative

4. Gap Analysis: Uncovered new application areas not previously considered

5. Roadmap Development: Defined short- and medium-term AI priorities

Building responsible AI governance

A critical outcome of the QS AI Self-Assessment was the establishment of a robust AI governance framework. Galileo recognised that responsible AI adoption demands clear policies and stakeholder accountability, an opinion echoed by global academics and students.

The institution developed:

• Regulatory Framework: Clear policies aligned with compliance requirements

• Code of Conduct: Ethical guidelines for AI use

• Data Security Protocols: Data classification and protection measures

• Role-Based Responsibilities: Defined rules for students, faculty, and staff

• Risk Assessment Processes: Structured evaluation of AI-related risks

• Audit & Compliance: Ongoing processes to ensure transparency and accountability

"To foster responsible AI experimentation and adoption, we focused first on putting a solid governance framework in place," notes Siddu.

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