Overview

In May 2026, the Digital Education Council (DEC) released the AI Skills Opportunity Map. This report explores how the advent of artificial intelligence (AI) is transforming work across different job sectors. Developed in partnership with Google.org, the AI Skills Opportunity Map includes both a research component and four separate action guides aimed at different usage groups: students, higher education leaders, higher education administrators, and faculty.

The report organizes findings into eight key takeaways:

• Stable Task Structures Make AI Impact Predictable Despite Rapid Change
  • AI may be evolving each year, but the core structure of AI tasks remains consistent.
  • This consistency helps predict how AI can and will be utilized in work tasks.
• Automation Is Densest Where Work Is Most Structured
  • Sales, administrative, and computer roles face the highest share of tasks that can be automated.
  • This is due to the structured and sometimes repetitive nature of these jobs.
• Where Accountability Is High, AI Adoption Hits a Hard Limit
  • Banking and healthcare have the highest share of human-led tasks.
  • The need for accountability and authority in these roles limits how much AI can be used day-to-day.
• AI Could Support the Majority of Work in Education, Business, and Management
  • AI was found capable of supporting the majority of daily tasks in these jobs.
  • For education and teaching, the AI skills embeddedness was calculated at 79%.
• AI Increases the Value of Expertise While Making It Harder to Build
  • Professionals with deep expertise are best equipped to judge when AI should be applied.
  • However, the ability to reach that level of expertise may be narrowing as AI absorbs entry-level work.
• Management Skill Is Moving down the Hierarchy
  • Coordination, oversight, and evaluation are becoming foundational skills for early-career professionals due to the rise of AI.
  • Typically, these tasks were reserved primarily for senior leaders.
• AI Often Reduces Productivity Before It Improves It
  • Workplaces often find a productivity dip once AI is introduced.
  • This often happens as AI output outpaces humans' ability to review that output, AI is applied to the wrong tasks, or task complexity exceeds a user's expertise.
• Long-Term AI Productivity Depends More on Human Capabilities than on AI Skills
  • Enduring human capabilities sustain productive and effective AI use over time.

DEC measured the effectiveness of AI in certain job categories by reviewing job taxonomies from more than  12 countries to synthesize what is required of each role. It then defined the relationship between how much a task lends itself to automation and to what extent AI can perform that task to an acceptable measure. This broke down into three applicability tiers: predominantly automatable, predominantly augmented, and predominantly human-led.

Background

The Digital Education Council is a Singapore-based global community of practice for higher education institutions, focused on helping institutions navigate digital transformation and the adoption of AI. DEC produces research, convenes working groups, and publishes benchmarking tools used by colleges and universities across more than 80 countries.

The AI Skills Opportunity Map reflects a broader challenge facing both higher education and employers: While AI tools are being widely adopted, workforce leaders have not yet developed the ability to assess whether AI outputs are appropriate, accurate, and well-applied. The report frames skills development as both requiring the skills to use AI effectively and the skills of human expertise to maximize someone's effectiveness in a given role.

Partners

• Digital Education Council (DEC)
• Google.org

Resources