Adobe State of
Higher Education 2026

The shift from digital transformation to AI orchestration marks a fundamental change in how universities are discovered, evaluated, and experienced. What once differentiated institutions at the margins now determines whether they are surfaced at all.

The challenge is not a lack of ambition, effort, or digital capability, but rather a problem of alignment. Universities have invested heavily in digital experience, marketing, platforms, and service improvement, yet the outcomes that matter remain uneven. The gap is not at the beginning of the journey where brand-building and reputation work hardest, but at the moments where intent peaks and decisions are made.

This is the current state of play. Universities perform more strongly when presenting information and establishing credibility, but even on these measures they have gone backwards from two years earlier. The struggles to sustain momentum then continues across the rest of the journey. Experiences fragment, context is lost, and responsibility shifts between systems and teams. In a more predictable environment, this friction was tolerable. In a world where AI is playing a more significant role, it can be exposed and amplified.

This reframes the problem for university leaders. The question moves from how to optimise individual channels, touchpoints, or technologies, to how to ensure the institution operates as a coherent system — one that holds together across discovery, decision, and delivery, regardless of where a student starts their journey or how they engage. AI readiness then becomes crucial precisely because it acts as a multiplier, strengthening connected capability or magnifying disconnection where it exists.

The leadership task then is orchestration — aligning experience design, personalisation, data, and service workflows into a single operating state. Universities that can make this shift will reduce friction, protect conversion, and scale support with confidence. Those that cannot adapt risk doing more and investing time and resources while achieving less where it counts most.

The Digital Student Experience Index (DSX) assesses how effectively universities support students throughout their journey, from initial interaction through to enrolment, census, and ongoing engagement. As students’ expectations for ease of access, convenience, and digital support heighten, the quality of their experiences shapes their choices, ongoing commitment, and advocacy for their university.

The DSX Index represents the industry average, based on user testing scores across 32 Australian and New Zealand university websites. The industry recorded an average overall index score of 77 out of 100, which declined almost 6% from the 2024 score of 82 out of 100.

However, looking at the student journey rather than the overall average provides a more useful perspective. A closer examination of key journey stages shows that performance is stronger early in the experience and moderately lower at the points that determine prospective student conversion and long-term outcomes. Yet even the higher-performing areas have seen a decline, whereas only the Enrol stage has improved.

As students progress through the journey, their support and learning needs become more specific and their expectations for relevant guidance rise. Digital experiences that harness the power of connected data, recognise student intent, and adapt content accordingly improve relevance, convenience, and time savings.

Personalisation performance across the student journey is the area where university scores varied the most widely. Overall, early discovery and engagement stages are more likely to be personalised, but interest-driven homepage personalisation and user journey personalisation are notably low. Put simply, universities are good at helping students find information but less mature when it comes to tailoring journeys once intent is expressed.

Conversational AI interfaces such as ChatGPT, Gemini, and other large language models (LLMs) are increasingly shaping how prospective students research universities and make enrolment decisions.

As these systems generate answers and perform tasks, universities must consider how experiences perform for human audiences and how offerings, pathways, and value propositions are surfaced, interpreted, and ranked within AI-assisted environments. While this can have an outsized impact on the Attract stage, where research is at its most vigorous, it also extends to each part of the student journey where general-purpose and university-issued tools are increasingly becoming part of the student experience.

To determine the current maturity among universities and unearth tactics to improve AI performance, Adobe developed the AI Readiness score (AiR). Measuring five core criteria, AiR ranks the digital and operational foundations that influence how effectively a university is discovered, interpreted, and recommended by AI systems.

The sector ranked highest on pillars that reflect foundational digital capabilities. The generative large language model optimisation (LLMO) pillar was scored at 72 out of 100 and AI Technical Context reached 71 out of 100, suggesting a positive impact from years of focusing on accessibility and site health. While still an emerging area, Agentic Interoperability, with 67 out of 100, is in the middle of the field, which may suggest a rising focus as universities seek to look ahead to a future where students more frequently use agents to seek information and complete enrolments.

The lowest scores among the AI Readiness pillars are AI Content and Citation and AI Channel and Device. Citation readiness assesses whether AI systems can accurately retrieve and provide information when queried by a student. Lower scores here raise the risk that answers are incomplete or inaccurate. Channel and device compatibility determines whether content and services perform consistently across AI-powered interfaces such as voice assistants and agentic systems. Again, lower scores here can mean variation or unintended information is conveyed as students move between modalities or devices.