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Where Will Machine Learning Have The Most Impact?

Scientists are looking at newer possibilities to amplify the positive change machine learning can bring to our everyday lives.

Where Will Machine Learning Have The Most Impact?

Machine Learning has been impacting the way we live. From product recommendations, improved customer service, to virtual personal assistants, machine learning is leaving its mark in every field. Scientists are looking at newer possibilities to amplify the positive change machine learning can bring to our everyday lives. Let’s look at some of the areas where we can expect machine learning to bring out a significant change:


  1. Accounts: The finance industry has vast amounts of information ranging from various bills, invoices, and transaction data to other client data. And this volume is going to keep increasing in the future. By making use of machine learning in the field of finance, scientists aim to transfer the redundant, repeatable and time-consuming tasks to the machines so the complex tasks can be carried out by humans.
  2. Matching Invoice with Payments: In a case where an organization receives a lump-sum payment against multiple invoices, the details of which are not known, machine learning can be applied to correctly analyze the possible invoices and match them with the payments. Any short payments can be brought to the attention of an employee or be automatically generated in the form of an invoice.
  3. Risk Assessment before Taking up New Projects: Machine learning could analyze through the wealth of data of an organization and gauge the risks of a potential new project by comparing it with the past projects of the organization. The organization would not have to deploy a big team for this risk assessment and also save a lot of time.
  4. Bank Reconciliations: Bank reconciliation is an important function of any finance or accounting organization. In the future, machines could learn how to completely automate bank reconciliations and respond to various enquiries from team members about the balances on a given date.
  5. To Prevent Cyber Crimes: Cybercrime cells or cybersecurity operators must get a lot of alerts daily to report suspicious activities. It can be difficult to respond to and manage all the complaints. With the help of machine learning, it could be possible to detect the fake calls from the genuine ones using predictive and analytical techniques. It would save the resources of cybersecurity teams and they could only focus on real threats.
  6. Human Resource Automation: Machine learning can transform the ways companies hire and manage their workforce. ML-powered chatbots could be used to store personalized information on all the current employees and make use of accumulated data to streamline the hiring process of new potential candidates. The recruitment procedure can be made simpler by picking out the finest candidates suitable for the job from the pool of talent eliminating the need for human employees to painstakingly go through numerous resumes.
  7. Transportation: Driverless cars will perhaps be the most popular application of machine learning in the field of transportation. Many of these cars are in their testing phase and many other prototypes are being developed currently. Whenever these cars get on the road, they could prove to be very useful in preventing accidents that happen due to drunk-driving, fatigue, and cell phone distractions. Multiple cameras and sensors are placed on these cars and predictive analytics are fed into the system so that they can achieve route optimization and function without human supervision. These self-driving cars could also prove to be a boon for the physically handicapped people who would not have to depend on anyone else anymore to go from one place to the other.
  8. Healthcare: Identification of diseases and early diagnosis of ailments is at the forefront of machine learning research in the field of medicine. The World Health Organization has estimated a global shortage of healthcare workers of over 14 million in 2030. With such projections, it goes without saying that machine learning could help tremendously to ease the strain on the overworked healthcare workers and prepare against the shortage in the future. For example, artificial intelligence assistance like Siri could be used to interact with patients and detect conditions like depression by analyzing their vocal tones.
  9. Help Our Governments: Machine learning can significantly help our governments to reduce its expenses on public sector agencies. For example, the US postal service makes use of handwriting recognition to sort out its mail based on the zip codes. Some machines can process almost 18,000 mails per hour. This saves a lot of human labor and also the salaries and other expenses that would have to be spent per person. Another case is how US Customs and Immigration Services use chatbots to reply to different inquiries of people at large, where only the complicated questions are left for human interventions.


It is evident that machine learning promises possibilities for various industries which can be truly transformative. It is only a matter of time before we see them become the next reality.