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How AI Is Linked To Business Analytics

AI Business Analytics

Though not an alternative to human knowledge and ingenuity, AI is considered a supporting tool to help humans. Though Al presently has a tough time completing different tasks involving common sense in the real world, it is able to process large amounts of data faster compared to a human brain.

Artificial intelligence systems play a vital role when unstructured data like images, social media or open-ended surveys are needed to make a decision. Amazon, for instance, recommends products to buyers before even they search for that particular product. Amazon has made this possible using machine learning techniques and now layer in unstructured data on top of its powerful, integrated collection of structured analytics such as product histories, addresses, and payment details of customers.

Amir Husain, CEO of machine-learning company, SparkCognition, said: “AI is like the second coming of software. It is an innovative software capable of making potential decisions on its own and is adept at acting in situations that programmers could not even think of. Unlike traditional software, it has a broader latitude of decision making.“

Those skills make immensely valuable across many industries, whether it’s just enabling visitors and team easily pave their way around a corporate campus or doing a complex task of monitoring the working of a wind turbine to estimate when it needs repairs before it breaks down.

AI has improved customer relationship management (CRM) systems to a great extent. Software, for instance, Salesforce or Zoho needs a great human intervention to stay up to date. By using AI, a normal CRM system can be transformed into an automated, self-updating platform that keeps up your relationship management.

Directly or indirectly, AI helps different sectors, and organisations are embracing AI in an effort to improve their business analytics methods. These companies use artificial intelligence courses to train their employees on the job and improve their approach to AI.

Banking & Finance Investing In AI

Today, the BA role has been completely automated across the industries like finance, investment banking, or portfolio management. Thanks to artificial intelligence, a new dimension of human thought and work processes are now possible. With so many benefits of AI, we still can not say that advanced machines will take over business analysis. However, there are many tasks have been taken over by robots, automated apps, and digital assistants.

AI has made leaps and bounds in cognitive computing, and the day may come when machines will understand and act according to changing parameter just like humans do. Today, most financial institutions and banks leverage AI to stop money laundering and other frauds. Many customer-facing units across the world use robot customer service and chatbots to manage the regular customer-related tasks. In order to make relevant product and service recommendations to insurance and financial industry customers, companies use recommendations engines to ease the process.

AI Relieving Human Resources

Generally, the entire process of hiring, interviewing, and onboarding becomes cumbersome to most HR representatives. The aim of applying analytics and AI to HR has excited many professionals in the field. Now, intelligent machines take care of regular tasks that particularly lower efficiency and HR professionals can save time to invest in other primary objectives, for instance, catering the needs of clients and existing employees.

Simply put, AI plays a major role in putting the human back in human resources. HR departments can make the most of AI in many ways. For example, Restless Bandit is an effective SaaS product. It automates the tasks of screening applications, maps out matches, reaching out, and schedules face-to-face interviews. In short, the pressure and time required to bring a potential candidate into the office are reduced extensively.

AI In Oil & Gas Industries

Ryan Benoit is the CTO of Ambyint, a Calgary-based steward in artificial lift optimisation solutions for the oil and gas industry is using big data to operate oil wells autonomously. According to Benoit: “Eliminating the manual component of data analytics lowers labour charges and provides our customers a way to track their wells throughout the day.” Ambyint has able to minimise the number of visits to the wells’ locations by augmenting remote capabilities and automating pump optimisation. This has resulted in improved efficiency and higher production.

Facial Recognition Features

Many well-known companies, such as Facebook, Nest, and Microsoft have developed facial recognizing tools. Though machine learning can not discover the person in photos, it can explain that a person in a particular photo is the same in another video or photo. You just need to link a limited field of people’s name to it, and in return, you get a system that can find out the people in a home setting or videos, photographs over a social media. The computer vision research involves this facial recognition feature and self-driving cars are now leveraging that research.

Bottom Line

At its core, machine learning makes sense of the bulk of digital data humans are generating. Allowing computers to perform the tasks they are capable of doing faster than humans is vital for businesses, so they can channel human resources on more important tasks.

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Danish Wadhwa is a strategic thinker and an IT Pro. With more than 6 years of experience in the digital marketing industry, he is more than a results-driven individual. He is well-versed in providing high-end technical support, optimising sales and automating tools to stimulate productivity for businesses.