2026 Forecasts for AI and Ed Tech: What Industry Leaders Are Stating
In an open call last month, we asked education-serving industry leaders to weigh in on how developments in AI and ed tech will impact colleges and universities in the coming year. Many of their reactions fixated artificial intelligence and education innovation. Here’s what they informed us.
AI Will Effect Registration, Ease Of Access, Student Support, and More
“In 2026, forward-thinking institution of higher learnings will make the information they currently have work much better for them, and for their students. For years, organizations have actually gathered rich signals about student readiness through assessments, transcripts, and applications. Frequently, that info is siloed once a student enrolls. As many colleges continue to deal with registration headwinds, smart leaders will put their data to work, to ensure they can retain students from the first day. Rather than waiting on failure signals several weeks– or semesters– in, organizations will utilize AI to ingest admissions data along other important inputs to construct a day-one strategy. Trainees will show up on school with a customized academic strategy that includes awaited support, course sequencing, and career-relevant insights to guarantee success. In 2026, the institutions that stabilize registration will be those that deal with admissions information not as a static photo, but as a living structure for trainee success– utilizing relied on evaluations and AI together to move from access to completion, and from intent to results.”– Steve Tapp, CEO, ACT
“By 2026, AI will start to vacate the margins of college, and the first examples of what the next ‘operating model’ for AI in higher ed will look like. Instead of existing as chatbots or pilot tools, AI will begin to show up as more deeply integrated facilities at a small– however growing– variety of institutions. In these early cases, AI will be ingrained across advising, profession navigation, and trainee services, enabling personalization at a scale human-only systems can’t reach. Effective institutions won’t be those attempting to replace faculty or consultants, but those utilizing AI to extend their reach, leveraging it to handle routine, high-volume interactions so staff can focus on complex, high-touch trainee needs. At the very same time, institutions must anticipate more pressure to show real-world outcomes from their AI usage. Early adopters will highlight how AI systems that link learning to labor market information, employer expectations, and profession pathways can strengthen trainee success and institutional relevance. The real divide in 2026 will not simply be in between AI adopters and non-adopters, but between organizations try out isolated tools and those starting to incorporate AI attentively into their mission.”– Jared Chung, founder and executive director, CareerVillage