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AI in the workplace, where to apply it and why

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Cutting through the hysteria around AI in the workplace and how to choose WHERE to apply automation, to create an environment where sanity and profit prevails.

Transcript:

I wanted to keep my promise from my last video and talk to you a little bit about applications for Artificial Intelligence in enterprise.  Recently, I was reading a HBR article that said there’s going to be 100 billion dollars spent by business on artificial intelligence and automation by 2025 and that’s a really big deal.

Why?

It essentially validates the acceleration of applying this type of tech within the context of business.  It’s never really a good idea to do AI for the sake of doing AI.  It must provide some value.

Where does it provide the most value?

There’s already a lot of mainstream, use cases for machine learning and neural networks.  For example, you can look at risk detection for insurance fraud, the personalisation of marketing messaging through chat bots and there’s a lot of other things in between.  Primarily, what you are looking at is where AI can provide the most value.

What we do a lot of is understanding where friction is greatest.  Where the distance between a customer putting money in your bank account exists.  Sometimes the friction isn’t within the relationship of the customer and the product.  Sometimes, it’s a process based friction.

Why does this happen?

As humans, we are not necessarily optimised to do everything we are supposed to do at the most efficient level. In many instances, the cost of human input or human behaviour, on a specific type of process is where we actually lose the most business.

What can we look for?

We need to find where in the value chain for the customer can we speed up the process, where friction is greatest. For instance, a software driven application (it doesn’t always have to be Artificial Intelligence), or we could use machine learning to shorten the distance between the customer’s money and your bank account.

The thing to remember is that this isn’t necessarily an attack on humans and the requirement for their labour.  There are lots of things that machines can’t yet do quite well, such as compassionate or creative logic. It’s going to happen eventually but it’s not in the short term. Right now, what we need to do is take people away from the repetitive tasks and processes that are mundane. I don’t know anybody who goes home to celebrate a manual labour input into a spreadsheet.

We are about to hit a point where we can really leverage and work with AI to optimise our own jobs and optimise our business models.  To advance business and allow humans to do what they are fundamentally better than machines at doing. That’s a really quick and sure fire way to ensure a profitable business in the long term.

Need a hand? This is where the GRONADE team come in.

GRONADE have worked on growth and data projects with enterprise across all industries: banking, finance, insurance, entertainment, gaming, infrastructure, social impact, medical and others, to build a true measure of success, with accountability flowing from customer discovery, through to product and process, and to revenue.

Want in? Hit GRONADE up at access [at] gronade [dot] com.

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