Virginia Tech Professor Urges AI Proficiency Framework Built on Technology, Domain Knowledge, and Partnerships

The increasing integration of artificial intelligence (AI) into daily life and professional fields highlights a growing demand for widespread AI proficiency. Data indicates that engineering and computer science students engage with AI in their coursework significantly more than those in humanities and social sciences. This disparity points to a developing AI proficiency gap among university graduates.

This new framework for AI readiness draws inspiration from a major technology gathering held in Las Vegas in January 2026, which attracted 148,000 attendees and over 4,000 companies. At this event, Roland Busch, President and CEO of Siemens AG, outlined three essential components for success in the AI era: technology, domain expertise, and partnerships.

The first component, technology, focuses on understanding AI systems' capabilities and limitations, along with familiarity with tools like generative AI models and data pipelines. The second, domain expertise, stresses that technical AI knowledge alone is insufficient; deep understanding within a specific field—such as urban planning or environmental science—is crucial for effective AI application and problem-solving. This includes recognizing potential biases or limitations of AI models within specific contexts. The third, partnerships, promotes interdisciplinary and external collaborations, using AI to facilitate communication and collective problem-solving across diverse fields and with industry.

This model shifts the definition of AI readiness beyond mere tool use, positioning it as a blend of technical skill, contextual understanding, and collaborative engagement. Universities must consider integrating this comprehensive proficiency across all majors, not just technical ones, to ensure every graduate is prepared for an AI-infused workforce. Future discussions will likely focus on how educational institutions can implement such a broad, interdisciplinary AI proficiency standard, including providing equitable access to advanced AI infrastructure.