Since the 16th century, automation has been one of the cornerstones of successful companies. Companies have been looking for and implementing cost-cutting strategies without sacrificing product quality since the dawn of manufacturing hundreds of years ago. Algorithms were first used to automate commercial operations in the 1950s. The main players started sponsoring and implementing machine learning for business in the 2010s.
Artificial Intelligence (AI) has the potential to revolutionize the commercial world
One of its main roles and responsibilities is this. Here are some problems that machine learning techniques can help with:
Responsiveness. Artificial intelligence, unlike traditional algorithms, is capable of adjusting to new situations and data without prior training.
Profits have increased. Simply using machine learning in the pricing system can result in a 5% boost in income. A company’s revenue can increase by many times with an integrated strategy.
The human element. Artificial intelligence is devoid of feelings. It has functions rather than emotions, and technology and knowledge have taken the role of mood swings.
Fraud prevention. Neural networks self-learn. It assists in the analysis of user behavior, the identification of questionable transactions, and the development of algorithms to prevent financial losses. As a result, the system becomes less susceptible, which is a prerequisite for consumer confidence.
Create a marketing plan based on the information supplied and the objectives set out. Artificial intelligence assists marketers in their work by not just analyzing historical sales but also using forecasting to “predict” future sales. It considers rival conduct as well as the general market environment. Also, having augmented reality software can help your business in personalizing the shopping experience for your customers. In the long run, you’ll start noticing an increase in sale conversion rate thus improving overall revenue.
Algorithmic business and areas of application of AI
- Making a financial commitment (In mobile banking apps, risk management, forecasting, crypto trading bots, and chatbots are all available.)
- Business (Customer behavior analysis and marketing strategy effectiveness, buying management, tailored loyalty program development, and in-depth analytics).
- Security of data (anti-fraud technology, threat analysis and prevention of emerging risks, and data for a shared database).
- Plants that are medicinal (record keeping, diagnostics).
- Workplace (Control of the manufacturing process, optimization, equipment diagnostics, breakage data, preventative actions, and automation).
This is only a small portion of AI’s potential. Funding is also required for the early development of a self-learning system. However, in the long run, its aid in processing large amounts of data is critical.
Why are algorithms important?
Working with AI entails a number of processes. The entrepreneur’s first and most important step is to acquire as much data as possible regarding sales over the previous several years. A dataset is a collection of data in this format. Fortunately, since the introduction of online cash registers, this data is automatically preserved. Without any manual input, the system synchronizes with them in only a few clicks. You may sometimes get by with systematizing the data you already have. In other situations, though, you may need to devote more time and effort.
Here are a few things that AI can look after:
- Administrative responsibilities that we’ve already addressed.
- Increasing specialist productivity by streamlining work processes.
- Client’s technical and information assistance.
- Reducing the human factor’s influence on decision-making.
- Improvements in internal communications, especially addressing language barriers.
- Financial transactions are monitored, and suspicious user activity is identified.
- You have complete control over information security and data privacy.
- Marketing plans are developed.
- Short-term and long-term forecasting
The brightest examples of AI implementation
Alibaba, a Chinese corporation, is the largest e-commerce platform in the world, selling more than Amazon and eBay combined. By tracking every car in the city, the City Brain project employs artificial intelligence algorithms to construct smart cities and assist in alleviating traffic congestion. Furthermore, Alibaba’s Alibaba Cloud computing branch assists farmers in tracking crops in order to enhance yields and lower expenses.
AI is used by Amazon in many parts of its company, including its digital voice assistant, Alexa. Amazon’s AI collects data on consumers’ purchasing habits and uses predictive analytics to create purchase recommendations. At a time when many traditional businesses are struggling to stay relevant, Amazon Go, America’s largest online retailer, is introducing a new idea for convenience stores. Unlike other stores, there is no need to check out. Artificial intelligence technology in the stores records the goods you pick and charges you for them automatically using the Amazon Go app on your phone.
3. Apple Inc.
The iPhone, which contains FaceID, and devices like the AirPods smart speakers, Apple Watch, and HomePod, which utilize the Siri smart assistant, both leverage artificial intelligence and machine learning. Apple is also extending its service offerings, employing AI to recommend music in Apple Music, locate photographs in iCloud, and use maps to route to your next appointment.
For many years, IBM has been at the forefront of artificial intelligence. It’s been more than two decades since IBM’s Deep Blue computer defeated the world chess champion for the first time. Project Debater is IBM’s most recent artificial intelligence breakthrough. This AI is a cognitive computing engine that participates in debates against two professional debaters.
Tencent, a Chinese corporation, has incorporated artificial intelligence into nearly all of its products. With one billion users, the WeChat app has expanded its reach to include games, digital assistants, mobile payments, cloud storage, streaming, sports, education, movies, and even self-driving cars. “AI in everything” is one of the company’s slogans. Tencent collects a large quantity of data and makes use of it to benefit the firm.
The key steps to implementing AI
It will take the money and effort to develop a self-learning algorithm, but the level of the cost will be defined by the industry. Instead of designing their own recommendation system, retailers may go for off-the-shelf options. Increased income is one of the functions of such systems. After just three months of use, AI pays for itself and then begins to generate net profits through considerable cost savings and higher sales.
The following are the major steps in deploying AI:
- Obtaining and digitizing data for analysis, as well as entering it into a data processing program.
- The creation of an algorithm from the ground up or the refinement of an algorithm based on a framework.
- The algorithm’s learning and self-training.
- Creation of a new comprehensive marketing strategy for the organization and all business processes that incorporate AI capabilities.
Artificial intelligence is quickly becoming a requirement in all business areas. The only question is who will be the first to use contemporary technology and get rapid results. And who will pull up at the last possible moment to at least stay in the game?
About the author
Olesia Zamyshliaeva considers writing to be her favorite free-time activity. She enjoys reading about something that she hasn’t heard of before and then sums up the information on paper. Any topic is interesting to her, as long as it is possible to find first-hand information about the subject on the Internet.