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Will AI revolutionize your life? Yes. How? It depends.

Productivity is the work you get done within a certain amount of time. Greater productivity means you get more done with less time or effort.

The US economy is soaring above the rest of the developed world due to long-term productivity growth. Also, the US is home to the Magnificent 7: Alphabet, Amazon, Apple, Meta Platforms, Microsoft, NVIDIA, and Tesla.

Coincidence? I beg to differ. The Magnificent 7 share the common theme of technology, and at the forefront of technology, lies AI.

AI helps us get things done faster without compromising quality, often even better than expected. The value of AI is in the eye of its beholder.

You will need to experiment with AI tools and see how they can benefit your work and productivity. To derive maximum value from AI, computational thinking is paramount.

The importance of computational thinking

AI can be used to help us solve problems. However, before a problem can be tackled, the problem itself and the ways in which it could be solved need to be understood. Computational thinking allows us to take a complex problem, understand what the problem is and develop potential solutions. We need to be able to present these solutions in a way that a computer, a human, or both can understand.

4 parts of computational thinking:

1. Decomposition - the ability to break down big and complex problems into smaller, more manageable problems
2. Pattern recognition - the ability to see similarities and trends within problems
3. Abstraction - the ability to focus on the key areas and ignore irrelevant details in problems
4. Algorithms - the ability to develop step-by-step methods to solve problems

A complex problem may be overwhelming, and we may not know how to solve it at first.

So, we break down the problem into smaller pieces (decomposition), look at these problems individually to see how similar problems have been solved previously (pattern recognition), keep the focus on the key details while ignoring irrelevant information (abstraction), and finally apply step-by-step approaches or rules to solve each of the smaller pieces of the problem (algorithms).

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Applying computational thinking in finance

In my role as a Fellow Chartered Accountant working in treasury, I am required to provide investment and financing advice. What should we invest in? How do we finance this investment? And how do we recoup our investment once it's profitable? To answer the billion-dollar question, you'd need to break it down into smaller pieces: facts, assumptions, forecasts, and options. Data-driven insights tend to lead to better decisions.

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Harnessing AI for productivity and innovation

AI has the potential to revolutionize our lives by enhancing productivity and solving complex problems. However, to fully harness its power, we must develop computational thinking skills. By breaking down problems, recognizing patterns, focusing on key details, and designing effective algorithms, we can leverage AI to make better decisions and drive innovation.

By developing computational thinking and experimenting with AI tools, you can unlock new levels of productivity and innovation.

The AI revolution is here… the question is, will you be a part of it?