machine-learning

While 16% of U.S. jobs will be lost over the next decade as the result of artificial intelligence and technology, 13.6 million jobs will be created during that time due to the trend.” Artificial Intelligence is truly conquering the world. AI and machine learning are changing onboarding for the better by offering customized, engaging employee training solutions.

Artificial intelligence and machine learning are making their way into all aspects of our lives and businesses. Every time you ask Alexa for the weather forecast you’re benefitting from the power of AI.

AI and machine learning in education

With machine learning entering schools, teachers will no longer have to worry about the logs they keep on each student. No more need to spend hours on delivering concepts and establishing goals for each student. The machine will be able to do it on its own.

Some companies have started developing software that can actually predict how well a student will do at school and what are their chances of dropping out. Based on the repetitive actions of a student, the program identifies their weaknesses and analyzes whether they can lead to expulsion.
So, if a student has issues with writing and with time this problem only gets worse, the program can analyze whether or not it is a kind of situation where one should be worried and start taking measures.

AI and machine learning in financial services

The transformative potential of machine learning is the driving force behind its popularity in the financial services industry. Machine learning can help banks, insurers, and investors make smarter decisions in a number of different areas:

Customer and client satisfaction: Machine learning helps financial services firms track customer happiness. By analysing user activity, smart machines can spot a potential account closure before it occurs. They can also track spending patterns and customer behaviour to offer tailored financial advice.

Reacting to market trends: Another application of machine learning is market analysis. Smart machines can be trained to track trading volatility or manage wealth and assets on behalf of an investor.

Calculating risk: Smart machines can analyse a large number of disparate datasets (credit scores, spending patterns, financial data etc.) to accurately assess risk in both insurance underwriting and loan assessments, tailoring them to a specific customer profile.

Remaining competitive:This example of machine learning is perhaps the most relatable to management level execs, giving firms a clinical edge in a fierce industry, by helping them remain innovative.

AI and machine learning in Retail

Online recommendations: Machine learning allows retailers to offer personalised recommendations based on your previous purchases or activity.

Better customer service and delivery systems: In large companies where response time is limited by staff resources, machine learning can help ease some of the burden.

Tracking price changes: The price of retail items tends to fluctuate over a certain period of time. Machine learning is helping ecommerce companies track patterns in these fluctuations and set their prices according to demand.

AI and machine learning in healthcare

Here, organisations can capitalise on the intersection between IoT (Internet of Things) and data analysis to enable smarter healthcare solutions.

Personalised health monitoring: Smart watches and other wearable devices have made health telemetry a reality. But machine learning is taking things one step further, allowing doctors and relatives to monitor the health of elderly family members. The more personal data these algorithms are fed, the better they understand a user’s profile, enabling healthcare professionals to spot potential anomalies earlier on.

Real-World Examples of Machine Learning

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