Postingpad - Abhay's portfolio and blogs

The third P of my inbound product management framework (Problem > Persona > Purpose > Product) is quintessential. Most often than not, I...

While this series of posts will be themed around ‘productizing’ AI, I will not be surprised if they apply to productizing any idea or...

I have often been asked for an easy way to identify use cases for AI. Of the many perspectives possible, one is ”use AI where humans...

Once you understand the role of AI in meeting the prime metric(s) and purpose of your organization, the next logical step would be to...

My previous post was about understand and aligning with organizational purpose before defining your AI use cases. Another thing to...

I have seen a tendency in business users to make a list of use cases that could benefit from AI. This typically happens because of...

This category of blog posts will focus on planning AI use cases for your organization. As you read through multiple use cases and...

We have discussed a few aspects of defining a prediction end point. Here is one more. Always work with your business users to understand...

While defining the prediction rule end point, I have often seen the spec designed such that the data science behind it becomes logic...

The end result of a requirement gathering exercise for AI is often the end point definition for the desired prediction rule. Defining the...

A question I have been asked often, “Should we aim for 70% or 80% or 90% accuracy with our prediction rule?” Like most questions in life,...

So you have the prediction rule available. The model has been trained, and you have reasonable amount of confidence in it’s estimated...

Often AI is a high compute environment. At prediction time, the need for computational horsepower might be high, specially for...

So the data science is done, programming completed and the prediction API ready. It might also give you an estimate of expected accuracy...

Supervised learning needs a training dataset to learn from. It is important to understand the nuances though. A meaningful training...

So how will you measure success of AI? As you start planning your AI implementation, ensure that there is enough thought given to it’s...

If Business Process Re-engineering (BPR) is new to you, here is a quick summary. Michael Hammer and James Champy were proponents of BPR...

He who never had a destination in mind often wandered. It is important to have a highly desired “to-be” state of AI. This state would be...

Implementing AI brings in change. I would broadly classify AI related changes into three types. The most obvious relates to processes....

As AI becomes mainstream, you can expect a lot of uptake of AI across multiple use cases in your organization. It is not unusual to find...