Artificial Intelligence, Machine Learning & The Potential Impact On Business

Every day we inch closer to a world where artificial intelligence (AI) and machine learning capabilities will overhaul our personal and professional lives. The impact will be inevitable, so we sat down to ask a selection of our technical braintrust to weigh in on the following question, from their unique vantage point:

From a technical perspective, what are some ways you foresee AI and machine learning being integrated into businesses within the next few years?

Jeremy Flores, Associate Technical Director | I don’t expect — or even necessarily want — decisions made for me by algorithms. What I do want, though, is the opportunity to leverage the learnings from data analysis and machine learning to help me make more informed decisions. For instance, sentiment analysis to assist in business communication — is that email I’m writing likely to strike the right chord with the recipient? AI isn’t likely to ever author my email for me, but it could advise me on how to tailor my language for a specific audience. That’s exciting to me.


Stephen Nguyen,  Developer | As AI and machine learning are continually evolving, it’s moving us past the ‘information age’ and will impact multiple parts of our daily lives. For example, as self-driving cars improve safety, companies can have a service that drives you to work. This will allow you to work in the car, meaning you can buy a lower priced home at a greater distance from work, without compromising productivity. A smart refrigerator will be able to identify what food you normally buy, monitor stock levels, and automatically do the shopping when you’re running low. Taking it a step further, advanced health technology might soon be able to scan your retina and tell you and your doctor what prescription is needed.


Martin Young, Associate Technical Director | From an evolutionary perspective, intelligence is the ability to learn from the past to predict the future. Artificial intelligence is just that, but done with a machine. Think of AlphaGo, it makes moves that it thinks will make it most likely to win. We can apply that kind of thinking to all sorts of domains.

It’s difficult for me to predict the specific ways this will be applied, but we’re definitely going to be using this intelligence to learn more about ourselves and our own behavior. Perhaps we’ll start seeing AI doing more than statistical calculation and move into statistical analysis, with artificial actuaries coming into existence.

Then there are virtual assistants like Amazon’s Alexa, which is cool, but like most technology, I think machine learning will be mostly hidden from the end user. For example, advanced AI could be used to direct web traffic, thereby reducing internet load times. To the user, things might just seem to be getting better, but the behind the scenes machine learning could power dramatic progress.

Businesses are always trying to better serve their customer. Privacy issues aside — and that’s a big aside — machine learning could be instrumental in serving customers what they want even before they know they want it.

An area right on the cusp of revolution is transportation. Driving requires advanced pattern recognition and prediction, which was previously only reserved for humans. Once self-driving vehicles are available and reliable, any business that employs drivers will be greatly impacted. There will be a ripple effect that will disrupt supporting industries and raise interesting and difficult questions around insurance and liability.


Kevin Carroll, Developer | Most people tend to focus on the highly visible way that AI and machine learning will be integrated into businesses, such as consumer products like Alexis where the user directly engages with the technology. However, I think the biggest impact that AI and machine learning will have is going to happen behind the scenes. As Jeff Bezos mentioned recently in his annual letter to shareholders: “Much of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type – quietly but meaningfully improving core operations.”

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