Digital Leaders in Higher Education 2026

Digital Leaders
in Higher Education 2026

AI & Tech Careers Edition
Methodology — How we identify the universities whose graduates are shaping the AI, technology and digital economy.
Embargo
These documents are provided for preparatory purposes only. They must not be published, shared or distributed before the official release on July 8, 2026 by Times Higher Education.
Purpose
Digital Leaders is a career-outcomes ranking designed to identify the universities and schools whose graduates are shaping the AI, technology and digital economy. It measures career outcomes and economic contribution rather than educational inputs or institutional reputation.
The ranking is built on the career trajectories of graduates — the positions they reach, the companies they found, and the leadership roles they hold — not on institutional prestige. The unit of analysis is the graduate career trajectory, not the institution itself. Its objective is to understand how institutions contribute to the development of talent, careers, skills and innovation ecosystems, and how these contributions translate into economic impact.
Guiding question: "Would a prospective student, recruiter, employer or policymaker consider this indicator meaningful when assessing an institution's contribution to the AI & Tech economy?"
The three modules Core framework
The ranking is organised around three modules — POWER, CREATE and TRANSFORM — each capturing a distinct form of contribution to the AI & Tech economy. They are scored separately and combined into a single overall Digital Leaders ranking, while remaining readable on their own.
POWER
AI & Technology Builders
Graduates who build the underlying technology. Assessed through two sub-rankings: AI & Data and Computer Science.
CREATE
Entrepreneurs & Innovators
Graduates who found and grow companies and bring new products to market.
TRANSFORM
Digital Leaders & Change Makers
Graduates who lead digital transformation and reach decision-making positions across the economy.
Four sub-rankings overall:
  • POWER — AI & Data
  • POWER — Computer Science
  • CREATE
  • TRANSFORM
Core ranking dimension: AI & Tech career outcomes
The ranking identifies the institutions whose graduates achieve the strongest career outcomes across the AI & Tech economy. Outcomes are read through forms of contribution including positions reached, leadership attained, entrepreneurial outcomes, economic contribution, presence in strategic organisations, and contribution to AI & Tech ecosystems.
Accounting for institution size. To ensure the ranking does not simply reward the largest institutions, results are assessed relative to the number of graduates rather than in raw volume alone. This allows smaller and more specialised institutions to be recognised for the strength of their outcomes rather than their scale.
Data sources. The ranking draws on large-scale professional and company data: career-trajectory data (Coresignal) and company and funding data (Crunchbase), combined with institutional graduate-count references. Grounding the analysis in recognised external sources supports both the credibility and the reproducibility of the results.
Supporting analytical dimensions
Beyond the scored outcome dimension, three analytical layers enrich the reading of the results:
1. Professional Pathways
How AI & Tech careers evolve over time: career progression, professional mobility, lifelong learning, upskilling and reskilling, cross-sector transitions, leadership development, entrepreneurial journeys.
2. Skills Intelligence
The capabilities associated with successful AI & Tech careers: technical, AI & data, leadership, entrepreneurial, transformation and emerging skills.
3. Ecosystem Intelligence
Where graduates create value and how institutions connect to innovation ecosystems: companies, industries, startup ecosystems, innovation hubs, strategic sectors, and regional and global ecosystems.
Ranking Methodology 6 steps
The methodology proceeds in two phases: the construction of one ranking per category (sub-rankings), then their consolidation into the global ranking. All steps are applied identically across the four sub-rankings.
  1. Profile selection (scope definition) The target population is defined by filtering professional profiles on a combination of criteria related to the company and sector, graduation and job title, selected to isolate the relevant field for each category. Country quotas are set at this stage to control the geographic composition of the sample. The exact filter logic and country quotas per category can be provided on request.
  2. Institution normalization and count Raw free-text "university" values are resolved against a canonical reference list of institutions (entity reconciliation). Each of the reconciled institutions is then enriched with two metadata attributes: country and institution type.
  3. Efficiency adjustment Counts are normalized against each institution's total graduate volume, converting absolute counts into an efficiency-weighted measure. This is the mechanism that prevents the ranking from rewarding scale alone, and that lets smaller specialised institutions surface.
  4. Temporal smoothing and new entrants Each sub-ranking is smoothed using a weighted average of the 2025 and 2026 rankings. The strongest-performing institutions absent from the 2025 ranking are inserted into the 2026 ranking, and underperforming ones removed. One ranking is built per category (POWER / AI & Data, POWER / Computer Science, CREATE, TRANSFORM).
  5. Score transformation and dimensional weighting Once the four sub-rankings are finalized, each institution's rank is converted into a score. A weighted average of these scores is then computed using the dimension weights below.
  6. Grouping and meta-ranking Institutions are consolidated into groups (e.g. a university combined with its affiliated business school). The aggregated group scores are used to construct the 2026 GLOBAL ranking.
Dimension weights
Module Sub-ranking Weight
POWER Computer Science 25%
POWER AI & Data 25%
CREATE Entrepreneurs & Innovators 25%
TRANSFORM Digital Leaders & Change Makers 25%
Total 100%
Our partners
Coresignal
Career-trajectory and professional data — public web data collection specialising in publicly available information from approximately 20 online data sources.
www.coresignal.com
Crunchbase
Company and funding data.
Pollup Data Services UG
Research and data analysis — uncovering human needs and societal trends through advanced data analysis, including artificial intelligence and large language models, to deliver solutions in business strategy, customer experience, and organisational excellence.
www.pollup.ai
Trendence Institut GmbH
Employer's insights and results validation.
Back to your ranking
Emerging – The experts in graduate employability
57 Rue de l'Abbé Groult, 75015 Paris – communications@emerging.fr
© 2026 Emerging – All rights reserved. Confidential documents.