AI Planning and Decision Making

- AI and Planning

Artificial intelligence (AI) is an important technology of the future. Whether it’s smart robots, self-driving cars, or smart cities, different aspects of artificial intelligence are used! ! ! But planning is very important in making any such AI project.

Even planning is an important part of AI, dealing with problem-specific tasks and domains. Planning is considered the logical aspect of action. 

Everything we humans do is done with a clear purpose, and all of our actions are aimed at achieving our purpose. Likewise, planning also applies to AI. 

For example, planning is required to reach a specific destination. Finding the best route in Planning is essential, but it's also important to know what to do at a particular time and why.

- AI and Decision Making

AI has greatly increased decision making. It makes the process clearer, faster and more data-driven. With AI, you can make small (micro) decisions, solve complex problems, initiate strategic change, assess risk, and assess overall business performance anytime, anywhere.

The nature of micro-decisions requires some degree of automation, especially for real-time and high-volume decisions. Automation is enabled by algorithms (rules, predictions, constraints, and logic that determine how to make micro-decisions). And these decision-making algorithms are often described as artificial intelligence (AI). The key question is how human managers manage these types of algorithm-driven systems. 

Autonomous systems are very simple in concept. Imagine a driverless car without a steering wheel. The driver just tells the car where to go and hopes for the best. But once you have the steering wheel, you have a problem. You must inform drivers when they may want to intervene, how they can intervene, and how much notice you will give them if intervention is required. You must carefully consider the information you will provide your driver to help them make appropriate interventions.

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- AI and Micro-Decisions

Your business's use of AI is only going to increase, and that's a good thing. Digitization enables businesses to operate at the atomic level and make millions of decisions every day about a single customer, product, supplier, asset or transaction. But those decisions can't be made by people working in spreadsheets. 

We call these AI-driven fine-grained decisions "micro-decisions." They need a complete paradigm shift, from making decisions to making "decisions about decisions." You have to manage at a new level of abstraction with rules, parameters, and algorithms. This shift is happening in every industry and in every kind of decision-making. In this article, we present a framework for how to think about these decisions and how to determine the best management style.

- AI at Scale

Accelerating AI integration across the enterprise can lead to positive business growth. 90% of enterprise AI initiatives are struggling to break out of beta. 

Organizations are maturing in data science, but still unable to integrate and scale advanced analytics and AI/ML into day-to-day, real-time decision-making, so they fail to capture the value of AI. The new world of remote work requires accelerated digital transformation, and AI/ML can be used to achieve this faster. They can lead to more efficient business operations, more compelling customer experiences and more insightful decision-making. 

Businesses can leverage AI to reap significant benefits across the value chain, but organizations must get it right from the start or risk fines, penalties, errors, corrupted results, and general distrust from business users and the marketplace.

[More to come ...]