When things start to think: Artificial Intelligence 101
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When things start to think: Artificial Intelligence 101

Artificial intelligence refers to machines or systems that can improve by emulating human intellect. In other words, artificial intelligence might be defined as the capacity of the robot or computer system to duplicate human cognitive abilities.

Artificial intelligence is not a single discipline. Machine learning and deep learning are inclusive phrases that define artificial intelligence. The cognitive abilities of AI systems include planning, learning, reasoning, problem-solving, knowledge representation, and perception. We'll look at each one in turn below. In information technology, AI is frequently used instead of artificial intelligence.

The history of artificial intelligence in a nutshell

In the 6th century BC, Aristotle discovered a set of principles for obtaining analytical results, and Ctesibius of Alexandria constructed the first self-controlled, rational, non-reasoning machine in 250 BC. During the late 1940s, a group of scientists at Princeton University in New Jersey was working on the idea of artificial intelligence. The notion of artificial intelligence is considered to have emerged during this time. When we look at it through the lens of current AI capabilities, it's obvious that it falls under II. It evolved with the electromagnetic equipment produced with crypto analysis requirements during World War II.

The originator of artificial intelligence is Alan Mathison Turing, who brought machine intelligence into the discussion by asking, "can machines think?" The term "artificial intelligence" was coined by John McCarty, Marvin Misky, and Claude Shannon at the Dartmouth Conference in 1956. They defined artificial intelligence as any operation carried out by a machine thought to require human intellect.

In 1997, world chess champion Garry Kasparov was defeated by IBM's Deep Blue; in 2011, IBM's another system named Watson defeated its rivals in a television competition program. And in 2016, Google's AlphaGo defeated world Go champion Lee Sedol. These were some hot turning points that changed humanity's view of artificial intelligence.

Why is artificial intelligence important?

Today, the exponential growth in data generated by both people and machines makes it difficult for businesses to judge based on this information. Artificial intelligence now serves as the foundation of all computer learning and has taken the place of human employees in all complicated decision-making processes. Artificial intelligence systems with a near-zero chance of error compute relevant combinations and permutations to reach the best decision in a business process.

What are Artificial Intelligence application areas?

Artificial intelligence has invaded nearly every aspect of our lives today. Many artificial intelligence instances exist in daily life and business, from personal voice assistants such as Siri and Alexa to behavioral algorithms with sophisticated predictive abilities and self-driving cars.

However, we must emphasize that artificial intelligence is still in its infancy. Many current systems are based on predefined situations or algorithms that respond to user actions. The use of self-learning artificial intelligence technologies in everyday life, as seen in HBO's popular TV series Westworld or Alex Garland's Ex Machina, is still severely restricted. AI is being increasingly used in some sectors of the economy. Let's look at several applications of AI in the business world and everyday life to see how they're changing things.

Industry agnostic benefits of AI

Artificial intelligence technologies will soon take the leading role in all decision mechanisms in the commercial sector, with machine learning and deep learning. We may summarize the advantages that AI applications provide to all industry-independent business procedures as follows:

  • AI improves both performance and efficiency.

  • AI relieves the burden on current resources by providing multitasking support.

  • AI enables complex tasks to be executed without significant cost expenditures.

  • AI works 24 hours a day, seven days a week, and has no downtime.

  • AI increases employees’ productivity who perform different tasks in business processes.

  • AI has mass-market potential and can be used across industries.

  • AI simplifies decision-making processes by making the process faster and smarter.

How do enterprises use artificial intelligence?

Artificial intelligence is becoming increasingly prevalent in the commercial realm. According to the Global AI Adoption Index, 31% of firms use AI in their day-to-day operations, and 43% investigate how to apply it to their business. According to business experts who took part in the study, the most common reason businesses embrace AI is due to the pandemic's changing demands; 43% of respondents claim they have sped up their AI projects due to the epidemic.

This technology is now accessible to more businesses due to the development of artificial intelligence technologies. Artificial intelligence can improve data security, process automation, and customer service. Natural language processing (NLP) is one of the fascinating artificial intelligence fields in today's business environment. According to the index, NLP applications are being used by more than half of businesses utilizing artificial intelligence.

It's only natural that the growing usage of AI is a good thing. Given the technology's potential to provide significant cost savings and productivity improvements, it's no surprise that it has become so popular. We take a deeper look at the most common uses of AI to understand its business advantages better:

Customer experience and services

Artificial intelligence is also being employed in customer service and services. Chatbots, for example, are computer programs that can converse with humans in natural language. They understand inquiries and respond appropriately based on machine learning algorithms and natural language processing technology. The most significant advantage of utilizing artificial intelligence in this area is that chatbots can complete the procedure faster and less expensively than people.

AI is used to create predictive models that recommendation engines may employ to identify goods and services that customers might want.

Artificial intelligence does not always remove humans from customer-facing activities; it also allows people to serve clients more effectively. Employees may provide customer suggestions as they chat with them by utilizing analytics similar to those used in chatbots and recommendation engines. AI may suggest the finest actions, more client conversations, and how to highlight a certain option.

Targeted marketing

Websites that operate online employ clever technologies to understand their users and clients. Users offer firms critical information about their interests and potential purchases with each online action. This information displays the advertisements that may appeal to each user. Today, almost every advertisement on the internet is managed by bots solely concerned with increasing click-through rates.

Artificial intelligence is used to carry out personalized, targeted marketing in the real world. Companies use analytics and smart technologies such as facial recognition and geospatial software to identify target consumers and advertise goods, services, and campaigns tailored to their specific preferences.

Supply chain management

Artificial intelligence is employed to enhance supply chain management. Many firms use machine learning algorithms to forecast when goods will be required and determine ideal shipment dates utilizing data. AI can also automate and streamline the replenishment process in this case by reducing (often eliminating) stock-holding and the danger of product shortages. According to Gartner, most supply chains will be controlled by intelligent tools with artificial intelligence and advanced analytics capabilities by 2024.

Efficient operations

Business applications are increasingly being enhanced with AI, and more organizations deploy it. Today, AI-powered technologies target all business support departments, such as human resources, finance, law, and customer service.

AI can now fulfill a variety of client needs on its own. When human beings are needed, it can route customer calls to any employee and those most suited to the requirements outlined by the consumer.

On the other hand, retailers employ artificial intelligence to develop smart store design, product selection, and monitoring of in-store activities. Artificial intelligence is also being used to keep track of inventory on shelves in various ways, including perishable goods' freshness.

Artificial intelligence is also impacting the way IT operations are carried out. Some intelligent security software, for example, may identify anomalies that suggest hacking or ransomware attacks, while AI-powered solutions can automatically solve infrastructure problems.

Safe operations

Artificial intelligence is used to improve security in many industries. Construction companies, government agencies, farms, mining companies, and other organizations working in the field in large geographic areas collect data from endpoint devices such as cameras, thermometers, motion detectors, and weather sensors. Management solutions adapt to the data collected and then use intelligent technologies to detect problematic behavior, dangerous situations, and business opportunities. AI-powered systems can make efficiency or security-enhancing recommendations and take preventative or corrective measures for businesses.

Artificial intelligence is also used to keep track of security situations. Manufacturers employ artificial intelligence software and computer vision technology to monitor employees' actions to ensure they follow safety procedures. Artificial intelligence is also being used by businesses from various sectors to analyze data from IoT ecosystems and track their assets or employees.

Quality control

Manufacturers have relied on computer vision, a form of artificial intelligence. Lately, they've started to profit from quality control software with deep learning capabilities to improve quality control operations speed and accuracy while minimizing expenses. Because deep learning algorithms develop clear standards for evaluating product quality, these systems provide a more accurate and up-to-date quality guarantee.


AI-driven enterprise apps use algorithms and modeling to convert data into actionable insights about how operations and business processes can be improved, known as optimization. From employee schedules to product pricing, AI-based company applications employ techniques and modeling to turn statistics into practical recommendations on how things might be optimized.