Where Education Ranks in Technology Adoption

By Tom Nault, CEO, Hudson Cloud

When Behan and his original partner came to me to talk about entrepreneurial opportunities, we talked about what industries needed an update and why. Around 2003, when I started Dashlight, the company that acquired Open Interface North America, we knew that the industries that badly needed modernization were from the bottom up, farming, construction and education.

Education sits in the bottom quartile of every credible digitization index, and has for over a decade. McKinsey's MGI Industry Digitization Index, the canonical benchmark since 2015, puts tech, media, finance, and professional services in their own tier. Education has never been near that tier. The Whatfix 2026 update gives higher ed a 2.375 score against a cross-industry average of 3.025.

The only sectors behind education are construction, agriculture, hospitality, and government. Healthcare is roughly tied with education at 1.875 on the same scale. Farming is below it, which contradicts the common assumption that universities are at least more sophisticated than the people growing food. Education is so bad that few VCs will fund in that segment because it takes far too much time to make the sale and see a return on that investment. For that reason fewer technologies are created to meet that market.

Manufacturing has quietly lapped education. 77% of manufacturers are now running AI in production, up from 70% the prior year. The factory floor in 2026 is more digitally mature than the average teaching clinic. Worth sitting with for a moment.

The leadership inside higher ed knows it. 89% of higher-ed leaders say their institutions need to be more digital. 69% cite digital transformation as their single biggest challenge and now we have an inside view.

Adoption is not the same as maturity, and healthcare proves it. 96% of hospitals had adopted EHRs by 2021, up from 28% a decade earlier. Yet healthcare still scores at the bottom of the digitization tables. Many academic and clinical institutions have been running the same core platforms for twenty years and have nothing to show for it but a longer login screen.

McKinsey's data shows a winner-take-all dynamic in digitized sectors. Margin spreads between the top and bottom performers in highly digitized industries are two to four times the spread in laggard industries. Translation: once a sector starts to digitize seriously, the early movers compound their advantage and the rest fall further behind. Education is on the cusp of this curve, but it’s not past it yet.

The intersection problem is the real story. Academic clinical and research institutions sit at the overlap of two of the least digitized sectors in the economy. Education and healthcare. They inherit the worst of both: education's procurement cycles, healthcare's compliance overhead, neither sector's urgency around workflow continuity.

The gap between technology owned and technology used is the widest in these two sectors. A modern teaching clinic, research lab, or training facility has imaging systems, EHRs, simulation environments, sensor arrays, clinical software, identity infrastructure, and cloud backups. What it does not have is the connective tissue between any of them. Practitioners still re-authenticate manually every time they move stations. This is in part where we saw a gap.

Pick any facility, any day, and count the minutes lost to logins, re-authentications, lost sessions, and workstation hand-offs. Multiply by staff, students, and stations. Multiply by the academic year. The answer is not small. It is a curriculum's worth of working time, evaporating in plain sight, billed to nobody, fixed by no one. That is what being a tech laggard actually costs. It costs hours.

Every sector that climbed out of the bottom quartile did it the same way. They did it by making the workflow work. Manufacturing did it. Financial services did it. Logistics did it. Education and healthcare are next because the cost of not doing it is finally larger than the cost of doing it. The institutions that recognize that first will run the table. The ones that wait will spend the next decade explaining why they fell behind.

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Sources: McKinsey Global Institute Industry Digitization Index (2015, updated subsequently); Whatfix Digital Transformation by Sector 2026; WEF Future of Jobs sector technology adoption data