IMHO, a "modest proposal" for the the CMU CS AI degree, CMU CS, and much of STEM field academics: Have much of the department and program borrow from
clinical medicine. So, have the department be in part a
clinic for solving problems from outside academics via STEM material, information technology, CS, AI, etc.
E.g., yes, continue to have seminars with graduate students and professors with, call it, solutions looking for problems but also have people from outside academics with problems looking for solutions.
In the halls, should find, yes, students and professors but also eager, determined people from outside academics with problems looking for solutions. So, in part the halls should look like the ER of a major research-teaching hospital, like a cardiac center, stroke center, trauma center, birthing center, oncology ward, etc. working on important real problems from outside academics.
So, some problems will yield to data collection, filtering, exploratory data analysis (J. Tukey), graphing, descriptive statistics, cross tabulation, some simple hypotheses tests, etc.
Some problems will yield to optimization -- differentiate, set to zero and solve; linear programming, multi-objective linear programming, network linear programming, integer programming, quadratic programming, non-linear programming, convex programming, etc. There can be approximations, Lagrangian relaxation, achieving necessary conditions for optimality, exploitation of particular problem special structure, heuristics.
There can be classic statistics, especially multi-variate statistics, regression, principal components and factor analysis, discriminate analysis, experimental design and analysis of variance, catagorical data analysis, time series analysis.
And there can be more advanced tools in deterministic and stochastic optimal control, more in probabilistic and stochastic model building, etc.
There can be work in natural language understanding, computer vision, and robotics.
Some of the work for routine solutions can be done by students as part of apprenticeship, meeting and working with people from outside academics, etc.
Then for the better stuff, some of the more serious problems from outside academics can be the start of research for students or faculty. Partly the justification for the research would be the importance of the real problem.
There is an old recipe for rabbit stew that starts out, "First catch a rabbit.". Well, a recipe for applied STEM field work could start out, "First find an application ..." or at least a good problem. Then, sure, look up, stir up lots of good theorems and proofs and algorithms and code but focused on the motivating real problem.
And then the research already has one good application. At that point, curiously, importantly, the chances of another application are relatively high, that is, higher than a first application for work with so far zero applications.
So, maybe CMU can develop some relatively broad expertise in, say, scheduling, logistics, supply chain optimization, facility location, monitoring, automation, etc.
When especially good results have been obtained for some business, sure, the Chair of CS, the Dean of the School of Engineering, the President of CMU, and various CMU Trustees might call the business CEO and mention that CMU has a fund .... That is, solicit donations!
When the program is established with good credibility, audit the financial benefits obtained and suggest that 10% back to CMU will get a seat a the Dean's Round Table, etc.
Research-teaching medical schools deal with real problems and also make progress in research.
Academic departments of engineering, etc. should do much the same.