EY’s enterprise AI advisory warns that adoption is not the core obstacle; instead, organizations may be facing a “tempo gap,” where AI system speed outruns human comprehension and decision-making. The report describes how AI embedded in customer and employee workflows can interpret intent, generate recommendations, and move interactions forward before users fully process trade-offs. The analysis highlights examples in real-world experiences such as auto-rebooking when travelers still need to compare options, rapid acceptance of material terms in financial applications, and sensitive data auto-population in medical forms before individuals fully understand downstream use. EY argues the system may be working as designed, but the user experience can still feel “off,” leading to hesitation and double-checking. The key concern is that faster does not always mean better—especially where understanding and consent matter. For universities deploying AI in advising, admissions processes, student support workflows, and administrative systems, the editorial implication is straightforward: campuses may need to measure not just model accuracy, but user comprehension time, review steps, and transparency in high-stakes decision moments.