Process, not state
AI-forward signals directional orientation and strategic prioritisation rather than mere tool adoption. It describes institutions committed to evaluating emerging AI capabilities and iterating infrastructure as tools develop—a continuous process, not a destination.
Definition
AI-forward (adj.): Describing institutions or organizations treating AI integration as ongoing strategic practice requiring active engagement with evolving technologies, rather than fixed deployment of finished solutions. AI-forward entities commit to evaluating emerging AI capabilities, making informed technology choices aligned with institutional values, and iterating infrastructure as tools develop.
The “-forward” suffix in technology contexts signals directional orientation and strategic prioritization rather than mere tool adoption. Part of the “X-forward” pattern (data-forward, digital-forward, cloud-forward) that emerged in technology strategy discourse c. 2015-2020. The “X-forward” pattern universally indicates:
- Strategic prioritisation (X at centre of decision-making)
- Organisational transformation (cultural shift, not technical implementation)
- Continuous engagement (process, not state)
- Leadership commitment (C-suite fluency required)
Alternative vocabulary in higher education
AI maturity (JISC, Gartner, EAB): Staged development model from initial understanding to optimization. Emphasizes progression through defined levels. Most established term in sector.
AI readiness (EDUCAUSE, Digital Education Council): Preparedness and capability assessment. Suited for institutional self-evaluation. Emphasizes current state over ongoing engagement.
AI transformation (EDUCAUSE, Digital Education Council): Process of fundamental organizational change through AI integration. Emphasizes magnitude of change over strategic orientation.
AI fluency (Ohio State): Capability to apply AI effectively within a domain. Emphasizes individual/organizational competence rather than strategic posture.
Distinctive characteristics
AI-forward occupies a unique position in the semantic hierarchy:
- AI-native: Built from ground up (structural)
- AI-first: Primary priority (strategic dominance)
- AI-forward: Active integration (directional/mindset)
- AI-enabled: Tool addition (implementation)
The term’s utility for higher education derives from applicability to institutions in transformation—neither claiming to be AI-native nor positioning AI as superseding educational mission, but signalling proactive engagement.
References