7 Industries with Artificial Intelligence (AI) Examples

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It’s hard to avoid conversations on artificial intelligence (AI). However, the potential of AI beyond Apple’s Siri and Amazon’s Alexa is unclear to many. 

In the following years and decades, AI is predicted to revolutionize practically every industry through new and developing application cases. Smart businesses and their executives will reap the rewards.

What is Artificial Intelligence (AI)?

Artificial intelligence (AI) is a broad term for computer systems that can solve problems and make decisions in ways that are typically associated with human intelligence. If you are looking for the AI development services, you can get in touch with AI development company. It’s possible that these things include:

  • Identifying faces and voices
  • Taking a stand
  • Language translation
  • Advising on what should be done
  • In addition

Various Applications of AI in Various Fields

So, what exactly do we do using AI? 

Consumer-focused solutions (like chatbots) sit alongside complex industrial use cases (such predicting the need for maintenance on manufacturing equipment) in the vast landscape of AI’s potential uses. Seven different sectors’ worth of applications illustrate the scope and depth of AI’s potential.

1. Financial Services

Both retail banking and international finance can benefit greatly from the use of artificial intelligence. These are some applications of AI that have been seen in this field.

Fraud Identifying

Financial fraud attempts, whether on a global scale or through day-to-day crimes (such credit card skimming), continue to climb significantly in frequency and create major disruptions to both organisations and individuals. Business Insider reports that financial institutions including J.P. Morgan Chase employ proprietary AI algorithms to identify and flag transactions that don’t conform to established norms.

Algorithm trading

The days of yelling on the trading floor have long since passed. Most significant trades today are processed by computers, which can respond and make judgements far more quickly than humans. The market for algorithmic trading is projected to grow to $19 billion by 2024.

2. Coverage

When compared to other areas of the financial sector, insurance stands out due to its innovative use of AI. Among these are:

AI-Powered Underwriting

Manual methods and data inputs, as well as intrusive procedures like medical exams, have been used for decades to make underwriting judgements. Today’s insurance underwriters employ AI to analyse voluminous data sets that include everything from a client’s medical history to their pets. 

Claim Processing

The majority of the claims process for straightforward claims can now be handled by artificial intelligence. Machine vision can be used to evaluate vehicle damage, and chatbots like Progressive’s Flo can handle customer service. As machine vision and AI capabilities develop, human input will likely play less of a role in claims judgements. 

3. Healthcare

While healthcare has traditionally relied significantly on human labour and care, an increasing number of duties can now be outsourced to AI. Read on for two applications of AI in the medical field.

Algorithms and Precision Health Care

Numerous factors, such as one’s way of life and one’s genetic makeup, can have a profound impact on one’s health outcomes or even one’s response to a particular treatment. Human physicians have a hard time making sense of these variables. 

Artificial intelligence has the potential to process massive volumes of data, allowing it to pinpoint the most effective treatments for patients and even spot new health risks before they become obvious to humans.

Medical Imaging and Surgery Using Computer Vision

Computer vision and machine learning are becoming increasingly promising for a variety of medical applications, including the detection of skin cancer and the facilitation of complex surgical procedures. Artificial intelligence, for instance, can guarantee that surgeons follow all protocols precisely.

4. Life Sciences

Artificial intelligence has many possible uses in the life sciences because of the massive amounts of experimental data that are routinely collected. Some applications of AI in the life sciences are:

Finding New Drugs

Large-scale experiments and the verification of hypotheses are still necessary in the hunt for novel treatments. However, since the 1990s, machine learning has been utilised to significantly shorten the time required. A drug’s effectiveness against a target, as well as its interactions with other substances, can be predicted using this method.

Disease Outbreak Prediction

Throughout the COVID-19 pandemic, specialists have used AI and machine learning extensively to predict the spread and repercussions of the virus, particularly as it has evolved. Data from these models has allowed public health and healthcare authorities to develop policies and prepare resources to minimise spikes and lessen stress on the broader healthcare system.

5. Telecommunications

Despite the fact that the majority of us take constant access to the internet and other forms of communication for granted, the telecommunications sector is dependent on a number of intricate mechanisms that require constant fine-tuning. There are several ways in which AI can meet these requirements.

Optimisation of Networks

Networks require traffic adaptation and anomaly resolution speed to keep operations running well. The majority of telecom companies (63.5%) are already utilising AI to optimise network performance for their consumers.

Prognostic Upkeep

Hardware for telecommunications networks must be widely dispersed. Moreover, disruptions to this infrastructure can have far-reaching effects on the system as a whole. With the help of AI, telecoms businesses can anticipate when issues are likely to develop and prepare accordingly. 

6. Oil, Gas, Energy

There is limited space for error in the oil, gas, and energy industry due to concerns over worker and environmental safety. Artificial intelligence is allowing energy firms to boost their efficiency without increasing prices. Image processing for determining repair needs is one such use.

Image-Processing to Identify Maintenance Needs

Due to AI’s improved image processing and pattern recognition capabilities, it is now possible to employ drones and other image sources to monitor power grids for malfunctioning machinery or even downed lines. This strategy is already in use across the electrical grid in the United Kingdom. 

Anticipating Energy Demand

In order to make informed choices about storage and consumption as the shift to renewable energy proceeds, energy providers will require accurate forecasts of future energy demand and supply.  The amount of solar energy that must be stored for use at night or on cloudy days is one such consideration. With the help of AI, businesses will be able to dissect the variables that affect demand and plan accordingly.

7. Aviation

Aviation Using data carefully to optimise both individual flights and the broader aviation infrastructure is crucial for safe, efficient aviation, especially in light of growing fuel prices. Uses of artificial intelligence in this field include:

Traffic Flow Forecasting

When trying to maximize revenues while keeping customers happy, airlines must find the sweet spot between operating too many unnecessary routes and not flying enough between specified locations. Airline route selection can be improved with the use of AI models that consider things like web traffic, macroeconomic patterns, and seasonal tourism data. 

Servicing Clients in Need

Few airlines have the manpower during severe interruptions, as those caused by massive weather events, to answer individual consumer queries and requests. AI is being used by airlines with automated messaging systems to help them better understand customer needs and respond accordingly. A consumer asking about their bags could be directed to a lost-luggage report form, as an example.

The Prognosis for AI in Different Sectors

The depth and breadth of AI’s use demonstrates the far-reaching consequences of big data, machine learning, and other applications. While some of these uses are still in their infancy, they are likely just the beginning as this technology develops. Therefore, businesses should think about taking swift action to increase their internal ability to study and implement AI. 

 

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