How AI can make us superhuman

Richard Potter, CEO, Peak, talks about Artificial Intelligence in the post-pandemic world and how it can make us superhuman. He highlights the importance of data and looks at the industries that are benefiting from all of this. Edited excerpts from a video interview…

Changes taking place in the post-pandemic era…

Because AI is such a horizontal technology, I almost view it in a sense as a data technology. The only thing that makes AI work is data. We can use that in different ways. I think the next frontier for AI in business is getting into the nuts and bolts of how companies run themselves and we see the businesses as the output of the sum total of all of their decisions. That’s where we are trying to enable companies to enhance that decision making, using the predictive and categorical capabilities of algorithms and AI.

The last couple of years have seen an acceleration in technology adoption largely driven by the pandemic because lots of things moved online and people started working remotely. A lot more of our lives are digital and we are creating a lot of data. We are able to understand our businesses better because of that data. We can use that understanding to create AI and decision intelligence applications to help run our businesses better.

Data and the role of AI-ML…

Just having a mobile phone in itself produces a huge amount of data constantly: Event based data, logs of all the actions that you take, every movement of interactions with applications and things like that. That quantity of data requires technologies to help people process it and draw meaning from it. That’s where you see Machine Learning often used to extract insight from those huge data sets.

For Peak we focus a lot more on the practical application of data and AI in the enterprise for what we would call those decisions that make up the value chain of companies. It tends not necessarily to be processing that type of data for what Peak does and that draws the link to how we can make workers and businesses in their day jobs become superhumans. It's simply taking the data that we use every day to make our decisions anyway. Let’s take an obvious example.

Imagine we are a retailer selling clothes. We’ve got physical and digital stores. I need to decide where to put my products. I need to think about what the demand for my product would be. How fast is it going to sell? What should I price it at? What amount of shelf space should it take? All of these will impact my business numbers: sales, profit margins and capital efficiency.

As humans we are good at making those decisions. We take a lot of data intuitively through our experience and we can use that data to make forecast decisions. We can understand demand, we can set price points and have a feel for how much someone might pay for a product. But in today’s world those decisions are increasingly complicated because as we have in the case of retail, there are lots of different ways I can sell my products, lots of different ways people can find my product and lots of different ways that I can fulfil the demand for that product.

Making us superhuman…

Where decision intelligence and AI can help you become superhuman in that case is processing those transactional data sets, understanding the consumer behaviour and giving us precise real time views of what demand and price sensitivity is going to be and with that optimizing, say product allocation and pricing.

The fascinating thing for me is the interaction between the human and machine changes a little bit in this world. We are moving away from a world where, in this case, a merchandiser and a retail company would work with a spreadsheet to figure it out and then distribute those products and price them all. We’ll take suggestions from the machine as to what the optimal allocation of those products and pricing would be and approve them.

What it means, and why I say superhuman, is that we can now do those tasks continuously in real time if we want to, across the entire product range. We can optimize the entire decision set for growth and revenue, or profit or customer service, making sure we never stock out of an important product. We can set those goals and the AI can help us achieve them. We become even better at doing our jobs.

I would categorize it in two different ways. As to the data explosion, we need technologies to help us compute and understand that data and what it’s telling us. That’s beyond human cognition. But the practical applications of AI, these are things we do every day as businesspeople or users in our jobs.

The next frontier…

This technology is amplifying our ability to do that even better. That I think is the next frontier. That’s the thing that we are seeing with our customer base, getting these meaningful gains in performance because business teams can make these consistently great highly optimized decision sets.

Imagination, creativity, and that real intuition is what people want to do. That all comes from us as humans. We are talking about technology that helps us process things and take way all those things that we don’t want to do. Gathering data and getting in a place to make a decision: Here’s a machine that’s going to help me optimize my decisions all the time and be great at my job. End users love our products for that reason.

Industries benefiting from AI…

Looking at it through Peak’s worldview, what we see is that AI is very well suited to those companies that have a relatively high frequency of transactional data. It could be like a transaction like you sold a product or an event-based things like a product movement, logistics etc.

You saw online retailers adopt these technologies earlier than physical world companies because the data sets are more structured, easier to gather, and they produce more data because of their nature of being digital businesses. Prior to that you saw AI-ML used a lot in financial services and the reason for that is high frequency transaction businesses.

You need that data velocity and quantity to train the algorithms to build these applications in the first place. Those are the sorts of industries that benefited. And digital native companies like Google and Facebook. They are just huge data companies.

(Catch the complete video interview at the PCQuest YouTube Channel)

Richard Potter, CEO, Peak

By Sunil Rajguru

sunilr@cybermedia.co.in