Can Versus Should in AI Product Delivery, with David Pereira

Yes, and there's one thing.

Direction is more important than speed because if you are going ultra fast in the wrong direction, we're going to get farther from where it should be.

And today what is happening is something quite interesting, I would say.

I am reading a lot of posts about the AI transformation and people are saying why the AI transformation failed.

And most of the time they attribute to data.

And I was saying like, there's another question you should be asking.

Why do we need an AI transformation when we have a lack of strategy? We don't know where we are going.

We don't know who we serve, who we don't serve.

What is our differentiation strategy in comparison to our competitors? If we can't answer these questions, you can plug AI, but you are going to amplify the confusion you already have.

You don't make it better.

You are going to make more or less of what you have faster.

So I keep looking at this and now, of course, a lot of people are just doing the bandwagon effect.

They're jumping and...

Okay, I need to do this and so on and so on.

But I do think we have a lot of opportunities if we look within a strategic mindset and we can apply critical thinking, judgment, and one thing that AI doesn't have, taste.

We need to bring that to the table.

Yes, and all those things are very human in judgment, taste, et cetera.

Well, at the moment, who knows in five years? We have no idea where the future is going to take us.

It's interesting.

I've seen a lot, and I read a lot, I've seen a lot of organizations and ask them the question about their AI transformation, and there's definitely a growing, I don't want to say backlash, but a growing sentiment that it's not going as well as they thought it could.

And, you know, one of those things is data.

And it's interesting.

I just want to pull on the thread that you brought up.

Often they say, well, it's because our data isn't uniform.

It's because our data is segmented.

Yes, and there's one thing.

Direction is more important than speed because if you are going ultra fast in the wrong direction, we're going to get farther from where it should be.

And today what is happening is something quite interesting, I would say.

I am reading a lot of posts about the AI transformation and people are saying why the AI transformation failed.

And most of the time they attribute to data.

And I was saying like, there's another question you should be asking.

Why do we need an AI transformation when we have a lack of strategy? We don't know where we are going.

We don't know who we serve, who we don't serve.

What is our differentiation strategy in comparison to our competitors? If we can't answer these questions, you can plug AI, but you are going to amplify the confusion you already have.

You don't make it better.

You are going to make more or less of what you have faster.

So I keep looking at this and now, of course, a lot of people are just doing the bandwagon effect.

They're jumping and...

Okay, I need to do this and so on and so on.

But I do think we have a lot of opportunities if we look within a strategic mindset and we can apply critical thinking, judgment, and one thing that AI doesn't have, taste.

We need to bring that to the table.

Yes, and all those things are very human in judgment, taste, et cetera.

Well, at the moment, who knows in five years? We have no idea where the future is going to take us.

It's interesting.

I've seen a lot, and I read a lot, I've seen a lot of organizations and ask them the question about their AI transformation, and there's definitely a growing, I don't want to say backlash, but a growing sentiment that it's not going as well as they thought it could.

And, you know, one of those things is data.

And it's interesting.

I just want to pull on the thread that you brought up.

Often they say, well, it's because our data isn't uniform.

It's because our data is segmented.