The rapid integration of artificial intelligence (AI) is driving a transformation in higher education, creating an urgent need to evolve from general digital literacy to a more specialized AI literacy. While AI literacy is essential for all members of the academic community, this paper argues for a further, crucial specialization: Faculty AI Literacy. University faculty are not merely end-users of AI tools; they are the architects of pedagogy, mentors of student research, and custodians of academic integrity. They face unique challenges and opportunities, from redesigning curricula and assessment methods to guiding students in the ethical use of AI and leveraging it to advance research methodologies. Therefore, developing a conceptualization of AI literacy tailored specifically to the faculty role is paramount for navigating this new landscape effectively, ethically, and innovatively. This paper addresses this imperative by proposing a comprehensive framework for Faculty AI Literacy and a practical roadmap for its implementation.

Drawing from a synthesis of academic literature and binding policy directives, such as the EU's AI Act, we define Faculty AI Literacy as a multifaceted competency that combines awareness, knowledge, skills, and a critical mindset. This framework moves beyond conceptualization to detail five core, interconnected dimensions. These include:
1) an understanding of AI's core concepts, capabilities, and limitations as they apply to higher education;
2) practical skills to apply AI tools effectively and appropriately to enhance teaching;
3) critical capacity to evaluate AI systems and their outputs for accuracy, reliability, potential biases, and manipulative uses;
4) a deep engagement with the ethical dimensions of AI, promoting fairness, transparency, and accountability;
5) the ability to foster academic integrity and prepare students for an AI-infused world, in alignment with both academic best practices and regulatory principles.

To translate this conceptual framework into tangible practice, the paper presents a structured, multi-phased implementation roadmap. The initial phase focuses on building foundational awareness and understanding through introductory workshops, individual consultations, and the creation of a central online resource hub. The second phase emphasizes practical application and skill development via hands-on training in specific pedagogical applications, including effective prompt engineering, and showcases of best practices from early adopters. Subsequent phases advance to critical evaluation and ethical integration, with forums on identifying bias, navigating data privacy, and developing new assessment strategies. The roadmap culminates in fostering a sustainable community of practice for continuous learning, collaboration, and dissemination of new developments.

Ultimately, developing Faculty AI literacy is not merely a technical upskilling exercise; it is a strategic imperative fundamental to the future of our teaching and a response to evolving regulatory landscapes like the EU AI Act. By systematically building these specific competencies, higher education institutions can empower their faculty to lead the way in harnessing the transformative potential of AI. This ensures the responsible, innovative, and effective integration of these technologies for the benefit of their students, their disciplines, and society at large, safeguarding the core values of academia.

Keywords: AI literacy, AI in education.