Artificial intelligence (AI) has already entered various sectors of the global economy. AI, machine learning, and deep learning technologies have become actively implemented by companies around the world. While AI technologies certainly have the potential to significantly improve the quality of business operations in the corporate sector, they have the potential to transform and disrupt many existing established markets. AI can be easily extended, adapted, and applied to different business operations.
The reason why AI is being implemented on such a large scale is due to its ability to bring intelligence to tasks that have not been done before. This, combined with the ability of AI technology to automate repetitive processes with intelligence, makes it a disruptive force in various sectors of the economy.
Why AI is a disruptive force for some industries
Artificial intelligence (AI) is a computer program that can mimic certain aspects of human intelligence. Instead of just following commands given to it, AI uses intelligent strategies and heuristics to use human intelligence to solve problems, just like any other computer program.
Improvement in machine learning
Machine learning programs form a subset of AI that can learn from the data it receives even after deployment. This gives companies implementing machine learning algorithms a utility factor as maintenance and upgrade costs are reduced. Moreover, the self-improving nature of ML allows solutions to evolve dynamically according to the needs of the tasks being solved.
The capabilities of AI vary widely in enterprise settings, but one of the most important things to note is that pure data make AI better. Therefore, such algorithms are well suited for enterprises where there is an established data workflow with a large amount of data. Today, data collection and storage have become the norm, but sectors that have long-standing data banks, such as finance, healthcare, and logistics, will benefit the most from an AI solution.
Although the capabilities of AI are different and differ in implementation and deployment, some characteristics exist for all types of AI. First of all, they can use large amounts of data to find the best solutions. This is a huge draw for companies that have collected large amounts of data. They can simply train AI to solve a specific problem using that data and deploy a solution that fits their exact needs.
AI can be deployed and improved with minimal effort, as well as tailored to company requirements with the help of data. This close match of solutions to a given problem is one of the main reasons why companies choose AI-based solutions. This, combined with the ability of machine learning algorithms to improve themselves with additional data, makes AI a bargain for businesses.
Reducing costs (cheaper labor)
Artificial intelligence is not only several orders of magnitude faster than human labor but also much cheaper. This will soften the blow for companies looking to use AI as a solution, as the potential cash return is much higher than the initial investment.
Cloud computing and cloud service providers are also driving the adoption of AI. Cloud AI deployment is not only cheaper than an on-premises solution, but it also comes with plug-and-play tools. Pricing is flexible, further reducing the initial investment companies must make to try an AI solution.
Predictive advantage (predictive analytics)
Predictive analytics, a branch of AI, is very useful in various industries and business niches. Using machine learning algorithms and predictive models, a program can be trained to find relationships between different variables. The program then uses this information to predict what the relationship between variables will be like in the future.
For example, a forecasting algorithm used in a supply chain scenario would be trained using shipping data. The quantity, demand, and supply of each item will be taken by the algorithm among other data. The software can then accurately predict the quantity needed to ship by looking at the past relationship between supply and demand.
As you can imagine, predictive analytics can greatly improve processes by reducing inventory and overhead costs. This is especially useful in the retail, supply chain, and logistics markets. Predictive analytics simply points to another useful feature of sophisticated AI programs: pattern recognition.
Using the concepts of statistics and computer science, a machine learning program can be taught to recognize patterns. This includes not only patterns in the collected data, but also in areas such as image and video recognition. This gives AI broad applications in healthcare, defense, and customer service.
10 industries that AI will have a big impact on
Artificial intelligence has been actively implemented in various sectors of the economy over the past 5 years. With the introduction of machine learning and deep learning by enterprise algorithms, many existing sectors of the economy have seen widespread transformation and disruption due to AI technology.
Medicine and Healthcare
The introduction of AI in healthcare promises to bring many benefits to users. Above all, the health sector as a whole has been focused on collecting accurate and up-to-date data on patients and those who seek care. This makes artificial intelligence suitable for the data-rich world of healthcare. Second, AI could find many use cases in healthcare.
The introduction of artificial intelligence can ensure the widespread adoption of predictive healthcare. Using the power of predictive analytics, AI can help doctors take proactive actions to ensure the health of their patients. This is a much better approach to healthcare than the reactive approach taken today. With the advent of embedded IoT-enabled devices, doctors can monitor the health of patients remotely and can also be informed if a patient is in an emergency.
In addition to predictive healthcare, AI can also make it easier to analyze scan results through image recognition. This has already been used to help doctors diagnose symptoms at a much faster rate since AI can process multiple scans much faster than humans. Health chatbots are also being developed. These bots will allow doctors to collect preliminary data about a patient’s symptoms.
Customer Service and Support Services
AI has already started transforming customer support and customer service. Natural language processing (NLP) algorithms have found their way into customer support lines in the form of chatbots. These chatbots can collect information about customer issues and enable service desk leaders to work more efficiently. In some cases, they can also solve customer problems themselves, only passing them on to management when necessary.
Due to their ability to understand exactly what the customer is saying, sufficiently advanced NLP algorithms can completely replace customer service executives. Instead of being a statically assigned algorithm with a set of predefined responses, a chatbot can dynamically adapt to whatever problem the client is facing. What’s more, since the customer doesn’t have to wait to contact the support manager, the waiting time is reduced, thereby improving the customer experience.
In addition to chatbots and customer support lines, recommendation systems can also be helpful. Amazon is a great example of this, the platform dynamically creates a separate homepage for all of its customers based on their browsing habits. Netflix also makes heavy use of recommendation engines, thus enhancing the customer experience by providing personalized recommendations for each user.
Banking, financial services, and insurance
AI and the financial sector are a great match. Just like in healthcare, financial companies have been collecting, collating, and organizing data for decades using predictive analytics, making AI a natural addition to the field. This technology was used to detect the possibility of a person committing a fraudulent transaction.
Banking is a sector where paperwork and documentation are always present. AI can also automate processes that used to be done manually, such as paperwork and documentation. This will not only reduce the time it takes to resolve problems but will also allow banks to better serve customers.
In addition, predictive analysis has also found great success in the banking sector. Banks can identify high value customers with predictive analytics through data mining and web text analytics. They can also retain customers longer by providing additional services based on their spending and financial performance.
By studying a customer’s credit history, AI can accurately predict the likelihood that a person will default on a loan. This simplifies the process of attracting new customers and reduces the likelihood of non-payment.
Logistics and supplies
AI in logistics can radically change operations. Predictive analytics can accurately predict the inventory a supplier needs and optimize routes to minimize overhead.
For example, Ab InBev, a global distributor of beverages such as Budweiser and Corona, has made significant use of AI to streamline logistics. Using predictive analytics, the organization was able not only to prepare the optimal amount of each drink but also accurately predict the demand for a particular product. This allowed them to significantly reduce storage costs and overheads.
Shipping companies will also benefit greatly from the adoption of AI. Usually, checking documents at customs posts delays the delivery process. Today, it takes a ship a few business days to get permission to ship all of its goods. Image recognition algorithms and intelligent automation can help customs officers conduct inspections more efficiently by scanning relevant documents and digitizing them.
This data can then be used to accurately track shipments and reduce time spent in ports. With the benefits of this technology, the global shipping industry has also adopted AI, especially predictive analytics, to optimize the economics of the supply chain.
Retail analytics has already become widespread among retailers. In addition to optimizing the supply chain, retailers can also accurately predict how much to stock in their supermarkets. What’s more, by collecting data on how customers enter the store, they can place products according to customer preferences, thereby increasing overall sales.
Retail will also be destroyed by artificial intelligence in the form of self-service stores. Amazon has already demonstrated a proof of concept for fully autonomous shopping. Amazon Go has already opened several experimental stores.
They use machine learning, deep learning, image recognition, and intelligent automation to enable customers to get in and out of the products of their choice. By analyzing the browsing patterns of customers and their purchases on the site, Amazon can accurately predict similar products, thereby maximizing sales.
AI in cybersecurity can work with extensive databases that most cybersecurity companies maintain to check for virus attacks. This technology is also being used by antivirus companies to provide a proactive method of dealing with cyberattacks.
With the wealth of existing data on cyberattack types, malware, and attack vectors, AI can be taught to reason. This will allow companies to use set-and-forget AI solutions that will constantly monitor the network for any suspicious activity. If inappropriate activity is detected, the algorithm can immediately fix the security hole or notify problem handlers. This reduces the time it takes to resolve a problem, thereby minimizing the risk and loss of information.
In addition to this, long-term cyberattacks against high-profile targets such as multinational enterprises can also be detected earlier with AI solutions. AI actively monitors networks for malicious activity, allowing the company to detect an attack much earlier. This is an integral part of reducing damage and protecting the company from financial loss and data loss.
Autonomous driving is considered one of the most revolutionary ways to use AI in the real world. Self-driving cars have already become popular thanks to companies like Tesla, and even Uber is considering deploying autonomous vehicles. Giants like Google are also building autonomous driving technologies.
In addition, autonomous driving can also be used to transport goods. Self-driving trucks will enable faster deliveries and more efficient costs because they do not require rest stops and will cost less than human drivers. An example of this is the Tesla Semi car. This truck has safety features made possible by artificial intelligence algorithms. These image-processing algorithms can determine if a collision is imminent based on the speed of the vehicle and the perceived depth of other vehicles on the road.
Soon, this technology will be advanced enough that people can take the position of supervisor, who will only need to monitor the AI. Driving in such conditions will become autonomous, which will reduce the burden on drivers and reduce the costs for companies.
The marketing industry will benefit from AI in two main ways. The first is more personalized messaging and the second is better targeting. Other smaller benefits, such as intelligent automation and AI-based tools, have already begun to emerge and are being rolled out.
AI-based marketing solutions can also determine the most effective messages for a company based on customer preferences. For example, if a customer orders a pair of shoes, the algorithm sends a notification to the customer about similar products, thereby increasing the likelihood that the customer will buy another product.
AI will make it easier for marketing departments to reach customers as targeted ads using neural networks become more common. Services such as Google and Facebook ads have already started using artificial intelligence technology for better targeting. Recommendation engines can also be used for user-to-user personalized advertising.
Defense and weapons
Although the promotion of autonomous weapons as a new type of weapon is highly regulated, this sector will undoubtedly develop as capital is invested in it. The ethical implications of building autonomous weapons have also been considered, but experts say AI weapons are indicative of the next arms race.
In addition to autonomous weapons, image, and video recognition can be used to monitor the general population. Based on existing databases with biometric data and face scanning, a citizen can be identified using facial recognition algorithms in surveillance networks. On the one hand, this increases the overall security of the nation, but also reduces human interference and infringes on the freedom of people.
There have already been ethical discussions about the use of this technology, as it can be misused to enforce an authoritarian style of government. This technology is already being used in China and partly in the US. Widespread facial recognition algorithms are used to create a social credit system and for other tasks. Citizens are judged based on their actions, which are recorded using AI-based cameras.
A new way of life with AI
AI will also lead to a number of lifestyle changes such as smart homes and integrated lifestyles. Devices such as Google Home and Amazon Alexa have become popular all over the world, and chatbots may become more widespread across industries in the coming years.
Such devices are already widespread among the population. Along with the development of the Internet of Things, prediction algorithms can provide an automatic lifestyle for users. For example, a refrigerator can use image recognition algorithms to determine if it is running out of vegetables. It can then place an order at a nearby grocery store and have the products delivered to the user’s doorstep using a robot.
This AI lifestyle will extend to everyday household chores. Moreover, the overall impact and impact of AI will fundamentally change life as we know it.