Why Machine Learning Will Change Every Business Sector

Machine learning, along with artificial intelligence, is being used to disrupt many industries for the better. Whether we’re aware of it or not, the technology has been steadily growing over the last decade to become a major driving force behind some of the most advanced changes we’ve seen in several business sectors.

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What Is Machine Learning?

By definition, machine learning is the scientific study of algorithms and statistical models that computer systems can use to perform specific tasks. Being done automatically, this of course highly boosts productivity if applied to any form of processing-related task. Essentially, it means that computers are able to analyse large volumes of data before interpreting them into performable tasks. It’s also closely linked to artificial intelligence.

The Impact On Businesses

The impact of machine learning on businesses has been staggering. It has the potential to automate many aspects of the workplace. This means it can effectively completely change the way a business operates at its core. Previously, ‘robots’ in the work environment referred to automated self-scan checkouts in retail. Now, the technology can delve much deeper than simple pre-programmed automation. For example, in large warehouses, computers are being used to pick stock. The fact that a Python-coded algorithm currently fluctuates around 0ms in terms of processing power, this is very looked after by many business owners.

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What Business Sectors Could Feel The Benefits?

Education

Pressure on schools and more important teachers has become somewhat of a hot topic in recent years. Python and machine learning could definitely help teachers in their day-to-day tasks, leaving them more time to concentrate on topics and, generally, the “creative part” of teaching. Given the fact that such algorithms are able to create lessons and study plans automatically, this will also accordingly tailor grade papers and results, following afterwards.

Law

With data processing and big data, it’s no secret that law firms could benefit from machine learning. The majority of settlement agreement solicitors work relies on sifting through huge mounds of paperwork. A computer can potentially save legal team hours of work, much like the education sector.

Retail

In terms of everyday use, retail stands to gain the most from machine learning technology. Many supermarket chains have been using autonomous checkouts and cashiers, in order to boost their productivity drastically. However, machine learning can also help when it comes to customer service.Bots, especially when applied to this very sector, can provide better assistance if they properly understand what the client wants, leading to a much better customer service experience. Machine learning will greatly be used in this segment in the next couple of years.

Transport

Self-driving cars are quickly becoming a reality. In fact, they’ve already been tested in the States and China. The idea is the make the roads safer for everyone by preventing dangerous driving. Though the USA is focusing on driverless cars, China has set its sights on driverless buses. These small minibusses won’t need a driver, though they’ll still require an employee on board who can steer the bus in case of emergencies.

Healthcare

Perhaps one of the most important industries who may benefit from the technology is healthcare. It’s already been used to help with diagnosis, prescriptions and treatment. This can provide more accurate, reliable results for the surgeon to analyse. What’s more, in future it’s thought that machine learning will be able to detect tumours and scan the skin for mole cancer. Essentially, machine learning can help to save lives.


Nick Davis is a former computer science graduated at the University Of Manchester (UK). Matter of fact, I discovered that I didn’t like coding 24/7 in a cubical office, which is the reason why, in 2016, I decided to leave my country and move to Milan, Italy, where I do all sorts of freelance writing, a lot of workout plans and many digital-related things.

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