With over 75 percent of business investing in Big Data, machine learning and artificial intelligence are set to take off in the coming years. But, is this true or all just hype?

More and more companies are investing their IT budgets towards machine learning and artificial intelligence capabilities and it’s clear why, as these technologies are taking off in massive proportions. Below are just a few of the many samples that we have seen of recent:

The Hype of the Self-Driving Car

The self-driving car seems to be the most heavily hyped application of machine learning and artificial intelligence, but is it giving the industries a bad name? These critical technologies may just be the way of the future, but they also have a lot of hype surrounding them.

Online Recommendations

Think Netflix or Amazon, these machine learning applications appear through online recommendations in our daily lives.

Fraud Detection

Due to the expansion of payment channels fraud is on the rise, and fraud detection services are in high demand within the banking and commerce industry. The use of machine learning allows automated fraud screening and detection as machines can process large data sets much faster than humans.

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Machine learning is a form of artificial intelligence in which software makes decisions based on its programmed algorithms. It’s useful for various types of automation, especially when it comes to network monitoring. Although the technology is nowhere near computers making 100 percent accurate decisions, the technology continues to improve every year. Here are the reasons why businesses will need both humans and machine learning in the future.

Society’s Transition to AI

One thing business leaders must be cautious of in the transition to AI is to avoid overspending on new technology, which might become outdated more quickly than in the past. Technological development is now moving at a rapid pace, which leads to improved network solutions but also drained budgets. Another factor is that consumers are much slower at adopting AI solutions than businesses.

In order for machine learning to become more powerful, it must be embraced by consumers. Health patients using wearable medical devices are already on board, while the masses are skeptical of machine learning technology. At present, a majority of people don’t trust AI and believe it’s biased, according to recent studies by Savanta. Many people are worried about machines replacing humans in the workforce.

Disappearing Jobs

A major social consequence of automation is that it can do the work of several people, saving companies time and money. Various industries, particularly radio, are moving in the direction of more automation, and fewer humans. This shift is very appealing to shareholders, but not workers who only planned for one long career in a specific field. Machine learning can potentially wipe out many jobs across various industries, which has already been happening at a steady pace this century.

Automated Solutions

At one time, a business depended on an in-house staff of technicians to monitor its network for fixing issues related to performance, congestion, and security. Machine learning tools can now monitor network activity to make bandwidth adjustments and block suspicious visitors. Big data and cybercrime are growing, so companies need to plan ahead for improving transmission, storage, and security by studying machine learning as a viable and game-changing solution.

Even though AI is rapidly advancing, an enterprise still needs humans to do what machines cannot do yet, which includes closing sales deals. Humans are also still needed for quality control purposes and ensuring positive customer service.

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