Saturday 4 November 2023

What Is Artificial Intelligence (AI) in Business? 10 Practical Examples

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 What Is Artificial Intelligence (AI) in Business? 10 Practical Examples

The term artificial intelligence (AI) describes a machine's capacity to learn, comprehend its environment, and make decisions in a manner akin to that of a human brain. Machine learning is making machines smarter every day.

This means that, according to common AI stereotypes, we won't be taken over by wicked machines very soon. AI is clearly changing the world in a very real and beneficial way when you cut through the sci-fi forecasts and "be afraid" hype, especially when it comes to AI in business.

You are probably already aware of some of the ways businesses are using AI:
  • Intelligent aides, such as Siri and Alexa
  • Chatbots for customer service or helpdesk
  • Face recognition software, such as that utilized by Facebook
  • personalized recommendations on websites like Netflix and Amazon
I will go over several other business applications of AI in this post, some of which you may not be familiar with. Generally speaking, the following instances can be divided into two categories:
  • enchanting clients with clever goods and services
  • enhancing corporate performance

Examples of smart, AI-enabled products and services

  • Roomba vacuum robots. Do you recall those adorable small vacuum cleaners that like enormous hockey pucks? AI is used to scan the space, identify obstructions, and determine how much vacuuming is required depending on the size of the area. Additionally, they pick up on and retain the fastest paths around the space.
  • Twitter use AI to distinguish between unlawful content, fake news, and hate speech. The company deleted around 300,000 terrorist accounts that AI had detected in a six-month timeframe.
  • Similarly, Instagram is utilizing AI to remove inflammatory comments and combat cyberbullying.
  • Enhancement virtual advisors. While many fintech companies now offer robo-advice, Betterment is the largest and one of the industry pioneers. Online financial advisors known as "robo-advisors" employ artificial intelligence (AI) to provide accessible, reasonably priced financial advice. The public will have access to financial planning thanks to this financial revolution. 
  • Smart thermostats from Nest. This device might be for you if you've ever been furious about the price of your energy bills. Your home's smart thermostat keeps an eye on activities and starts to recognize the behavioral patterns of its occupants. Then, without wasting energy, it dynamically modifies the temperature to keep the house comfortable depending on what it learns about how you and your loved ones use it.

Examples of smarter business operations

  • Businesses may repair, replace, or service machinery and parts at the best possible time—before it breaks down—with the aid of predictive maintenance. One example of this in operation is Siemens AG, one of the largest global providers of railway infrastructure. The company repairs assets before they break down, improves train reliability, and offers uptime guarantees to rail operators by utilizing IOT and AI technologies.
  • Artificial intelligence (AI) approaches are used by KenSci's risk prediction platform to help identify fraudulent healthcare claims, which raise the cost of healthcare for everyone. From a single dataset, the system was able to detect fraudulent claims worth over $1 million.
  • In Germany, Dominos is testing automated delivery robots from Starship Technology to deliver pizza. Compared to delivery trucks and cars, these small delivery vehicles—whose top speed is 10 mph—are proving to be more economical and effective for short-distance deliveries throughout town. The same technology is now being used by Just Eat to deliver takeout in London.
  • With the assistance of AI, IBM's Chef Watson technology assists chefs and restaurants in creating recipes and suggesting creative flavor combinations.
  • Burberry is utilizing AI to enhance customer satisfaction and fight fake goods. In order to give each consumer a better customized shopping experience, the company's reward and loyalty programs gather and analyze customer data.
These are just a few fascinating instances of how companies are using AI to enhance operations and please customers. In the upcoming years, there's no doubt that we'll witness a great deal larger applications of AI in business.

Applying AI strategically in the workplace

It's crucial to have a strategic strategy whether you want to use AI to pleasure your customers, enhance your business processes, or both. 

By that, what do I mean? One thing I mean is developing a specific AI strategy that outlines your goals for using AI and how you'll implement it, and keeping it outside from your data strategy. Furthermore, integrating AI into your overall business plan is essential to its strategic application. Stated differently, what are the goals of the organization and how may AI support the attainment of those strategic objectives?

This kind of strategic approach allows you to concentrate your AI efforts in the areas where they will have the biggest impact on the business. Please get in contact if you require assistance with any area of AI in your company. I've helped some of the biggest brands in the world develop their AI strategies, and I can help your company approach AI strategically as well.

Artificial intelligence in business

Artificial intelligence (AI) technology is being adopted by many companies in an effort to save operating costs, boost productivity, boost sales, and enhance customer satisfaction.

Businesses should consider integrating the complete spectrum of smart technologies, such as generative AI, machine learning, natural language processing, and more, into their operations and goods in order to reap the biggest rewards. But even companies that are new to AI can benefit greatly.

Impact of artificial intelligence in business

With the appropriate AI technology in place, your company could be able to:
  • automate and optimize repetitive procedures and processes to save time and money.
  • Boost output and efficiency in operations
  • decide on commercial matters more quickly by using the results of cognitive technologies.
  • prevent errors and "human error," if AI systems are configured appropriately.
  • Utilize data to forecast consumer preferences and provide a more tailored experience for them.
  • mine a huge amount of data to provide quality leads and expand your clientele
  • enhance income by spotting and seizing sales opportunities
  • develop knowledge by facilitating analysis and providing astute guidance and assistance
A recent Infosys study found that competitive advantage was the primary motivator for deploying AI in business. Next, the source of the motivation was:
  • an executive-made choice
  • a specific operational, technical, or business issue
  • an internal trial
  • clientele's desire
  • an unforeseen fix for an issue
  • a branch of an additional project

advantages of human-AI cooperation

Studies indicate that AI isn't always the greatest system working alone. While AI technologies are excellent at automating or even driving repetitive, lower-level tasks, organizations typically see the biggest gains in productivity when human and machine collaboration occurs.

In order to fully utilize this potent technology, you should think of artificial intelligence as a way to enhance rather than to replace human abilities.


  1. class McCullochPittsNeuron:
    def __init__(self, weights, threshold):
    self.weights = weights
    self.threshold = threshold

    def activate(self, inputs):
    net_input = sum(w * x for w, x in zip(self.weights, inputs))
    return 1 if net_input >= self.threshold else 0

    # Define XOR function using McCulloch-Pitts neurons
    def xor_function(input1, input2):
    # Define weights and threshold for each neuron
    weights_hidden = [1, 1]
    weights_output = [-1, 1]
    threshold_hidden = 1
    threshold_output = 0

    # Create neurons
    hidden_neuron1 = McCullochPittsNeuron(weights_hidden, threshold_hidden)
    hidden_neuron2 = McCullochPittsNeuron(weights_hidden, threshold_hidden)
    output_neuron = McCullochPittsNeuron(weights_output, threshold_output)

    # Activate neurons
    hidden_output1 = hidden_neuron1.activate([input1, input2])
    hidden_output2 = hidden_neuron2.activate([input1, input2])
    final_output = output_neuron.activate([hidden_output1, hidden_output2])

    return final_output

    # Test XOR function
    print("0 XOR 0 =", xor_function(0, 0))
    print("0 XOR 1 =", xor_function(0, 1))
    print("1 XOR 0 =", xor_function(1, 0))
    print("1 XOR 1 =", xor_function(1, 1))