Is it time to introduce A.I into your company?

Updated! This is an updated version of the original article. Last Update: May 14, 2021

AI (Artificial Intelligence) is a hot topic in the Tech World. IT websites for jobs scream for Data Scientists, Senior Python Devs, or just anyone well versed in the secrets of Machine Learning.

How AI-ready is your company?

For non-tech mere mortals, the thought of AI in a company can bring about a climate of fear and mistrust. “They’re going to replace everyone with robots!” screams my partner. “AI is seriously dangerous,” once complained Mr. Elon Musk. Thanks to the likes of Amazon, we also have the mental image of a robot army moving around the office, laying off employees, and doing a spring clean-up.
So, with that in mind, could a move towards AI-driven solutions send the wrong signals to employees? Not so, I argue. 

Machine Learning: the hidden power of AI

When you start learning about Artificial Intelligence seriously, Machine Learning, in particular, there is somewhat of an anti-climax. Gone are the hopes of building the next Terminator. If I had to summarize Machine Learning in six words, they would be “clever statistical use of your data.”
Every company relies on data — data about customers, products, sales history. Office managers stare at Excel spreadsheets every day, trying to make sense of it all. In the organization I worked for in a previous life, fellow employees referred to them as “Professional Excel Viewers.”
AI’s statistical power is maybe best represented by a subset category called Machine Learning (ML). ML resides under the umbrella of Computer Science, just like AI, but it does involve machines’ independent learning ability. While AI generally follows simple logic cues, ML agents utilize standalone decisions.

The term ‘machine learning’ is about sixty years old and nudged into the notion that a great decision can be the product of detailed categorization of voluminous data. What’s more important about this decision is the prediction based on it. Although we humans are used to learning and making estimations, our cognitive power is fundamentally different from any artificial intelligence agent.
Whether accurate predictions about the stock market or detailed personalization of your services, machine learning comes to the rescue.

eCommerce is in a constant state of reinvention. If the local shop owner can engage each customer in direct conversation, this opportunity is missing in online shopping. eCommerce owners don’t have the immediate attention of their customers, so they have to rely on a copious amount of data and use a machine to help them make sense of it all.

Deep Learning: an upgraded source for analysis

If Machine Learning is AI trying to be more human-like, Deep Learning (DL) is taking it a step further down the same path.

Deep Learning is ML on a finer scale.

It is the effort to bring machines closer to the neural network of the human brain. Layers of processing power working together in unison, intelligently sorting data, bouncing micro-decisions off each other, learning, improving.
Deep Learning is central in new methods in fraud detection, supercomputing, investment modeling and prediction, big data analytics, facial recognition software. With DL’s capacity to gather, reprocess, and model data, its practical value is left to the imagination. You could turn the collective input of your clients into meaningful counteractions.

Machine Learning takes your data to the next level of understanding. It can see what human eyes can’t. You want to know which products are “risky” for specific markets, then use supervised learning. Which are the most asked questions on your corporate website? The Natural Language Processing power can bring some answers. Do sales trends change for certain products? Use unsupervised learning and find out why.
The present job market suggests that AI is a sought-out feature wanted by many companies, all different in size and purpose. Those who embrace AI understand their data better, and in turn, understand their market better. Strong data management makes them prevail over competitors.
With every AI Product released by CodeCoda, we are making the job of our client’s employees more secure, not less.

AI’s footprint in the current job market

Machines are great and shine bright, especially at times when humans fail. During the pandemic, scientists used AI to determine Corona’s presence by measuring various diagnostic imagery disturbances. Due to the aggressive nature of the virus, AI-aided analysis seems to make accurate predictions on its progression.
Vast quantities of data are perplexing to the average human mind, but machines can use it and transform it into meaningful analytical material sources. A particular company called BlueDot even used AI and predictedCOVID-19 before it happened. Controlling and predicting a complex process like an epidemic becomes a comfortable process thanks to the processing power of machines.

In businesses where volume is critical, machines are often a top solution – heavily outclassing humans by a huge factor. No person can work without breaks or match the speed of mechanical automation. High volume output makes humans look like a hard maintenance factor, and more companies recognize the massive advantages of AI and quickly adapt them to their strategies.
In the coming decades, the global job market share for AI-driven solutions will soar. And rightfully so. Amazon would have never gotten the infamous ‘same-day delivery’ milestone without the help of millions of robots, each with soldier-like resilience and guaranteed productive output.
But this is just the beginning, and present AI technologies are only but a stepping stone to the greatness ahead. Indeed, you can’t replace your drivers with self-driving cars yet. But you can add an army of AI warriors to do wonders. Valuable industry insights, previously deeply hidden in data bulks, suddenly start to make sense when interpreted by smart AIs. We come to realize that with the acute touch of artificial intelligence, most businesses can quickly become a better version of themselves. 

To find out how compatible your business is with AI-driven solutions, please drop us a line, or call us. We never miss an opportunity to talk about using tech to improve businesses.

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David Dorr, Head of eCommerce

David is the Head of e-Commerce at CodeCoda where he is responsible to lead several teams of eCommerce specialists. In his previous role as a data scientist for London Metropolitan Police, he was developing deep learning NLP algorithms as part of the Crime Prediction initiative. He then switched over to combine AI with e-Commerce.
He received a B.Sc in Physics from the University of Surrey, Guildford in 1996. With this scientific background, he switched relatively early in his life towards Neural Networks and e-Commerce and has ever since been fascinated with what AI and Machine Learning can do for Online Commerce.