Today I would like to draw your attention to the report “AI Scenarios 2030: Helping policy makers plan for the future of AI”, published by the Government Office for Science, last month.
As the title suggests, this report presents five scenarios for what AI systems might look like in 2030. The scenarios were developed to help policymakers visualise how AI technology might evolve, to stress test how different policies might perform for alternative scenarios, and to develop long-term plans for their departments based on those tests.
To develop the scenarios, the team behind the report started by identifying the 6 factors that they think will determine the future of AI technology:
Then, the experts combined these factors in “a set of internally coherent, contrasting futures, which we developed into five scenario narratives” (page 5):
These scenarios are meant to be used by other decision-makers, not just policy-makers. So, I spent some time thinking about what each of these 5 scenarios would mean for Universities, in England. Here is an overview:
| Scenario | Impact on teaching |
| 1: Slow Burn | Unequal student experiences and expectations across subject areas. International students may require training for different AI regulatory environments. |
| 2: Open Frontier | Less emphasis on knowledge production and more on judgement, problem solving and AI-collaboration. |
| 3: Augmented Growth | Graduates become orchestrators of AI workflows. Emphasis on leadership, ethics and complex problem formulation. |
| 4: Transformation Economy | Universities must re-engineer courses, focusing on irreplaceable roles and skills. |
| 5: Take-Off | Emphasis on entrepreneurship, professional experience during the degree, and lifelong learning, to prepare graduates for decline in traditional entry-level roles. |
The common thread among these scenarios is a shift away from routine knowledge production and towards adaptability, judgment, and orchestration.
How do these scenarios impact your industry, and your strategy?
Ana Canhoto 