Artificial intelligence has made incredible strides in solving some of the most critical challenges in fields like healthcare, finance, and logistics. But while AI researchers often concentrate on automating high-stakes, essential tasks, they may be overlooking a vast landscape of opportunities—tasks that fall into the Should, Could, and Won’t categories.

The MoSCoW Method: A Framework for Prioritization

Before diving into why AI should expand its focus, let’s first understand how tasks are typically prioritized. One of the most well-established methods for ranking tasks—borrowed from project management—is the MoSCoW method. This framework categorizes tasks into four buckets:

1. Must – Essential tasks that must be completed for success.
2. Should – Important but not critical tasks that add significant value.
3. Could – Desirable tasks that are nice to have if resources allow.
4. Won’t – Tasks deemed out of scope or not worth pursuing.

In AI development, the lion’s share of research and investment goes into solving Must tasks—think medical diagnostics, fraud detection, or autonomous vehicle decision-making. These are undeniably important, but what about everything else?

The Overlooked Potential of “Should, Could, and Won’t” Tasks

While AI races to automate the most vital functions, humans are still left handling the vast majority of daily responsibilities—many of which fall into the Should, Could, and Won’t categories.

Why This Is a Problem:

1. Human Bandwidth is Limited – Even if AI masters critical tasks, humans still spend enormous amounts of time on Should and Could tasks—scheduling, minor optimizations, repetitive but non-urgent decisions. Automating these could free up cognitive load for more meaningful work.
2. Hidden Value in “Could” and “Won’t” Tasks – Some tasks are labeled low-priority simply because they’re tedious, not because they lack impact. Automating them could lead to unexpected efficiencies.
3. AI’s Full Potential Remains Untapped – If AI only handles Must tasks, we’re missing opportunities to enhance productivity, creativity, and quality of life in smaller but meaningful ways.

Where AI Could Make a Difference Beyond “Must”

Imagine AI that:

• Automatically organizes your inbox based on Should priorities (e.g., “This email isn’t urgent but would be good to respond to this week”).
• Handles Could tasks like suggesting minor workflow optimizations you’ve never had time to explore.
• Takes over Won’t tasks—like declining low-priority meeting invites—so you don’t have to.

These may not be life-or-death functions, but they compound into significant time savings and mental relief.

The Future of AI: Balancing “Must” with the Rest

AI shouldn’t just be about solving the biggest problems—it should also be about making daily life smoother, easier, and more efficient. As the technology evolves, researchers and developers should consider:

• Expanding AI’s role in non-critical but high-frequency tasks.
• Re-evaluating what’s considered “low priority”—could automation make these tasks worthwhile?
• Ensuring AI augments human productivity holistically, not just in high-stakes scenarios.

Final Thoughts

While solving Must tasks will always be crucial, the next wave of AI innovation could lie in tackling the Should, Could, and even Won’t tasks that dominate our daily grind. By broadening its focus, AI can truly transform not just industries, but the way we live and work every day.

What Should or Could tasks would you like to see AI handle? Let me know in the comments!