AI is everywhere today.
No matter which country you live in, there will be an AI system that works around you.
You may not know it, but businesses are adopting AI rapidly.
Many people still think of AI as something that is shown in sci-fi movies, but it is a lot more than that.
It is shaping how the world moves ahead, and the limits of AI systems are endless.
Businesses always want something that makes them money with the least investment, and AI surely checks that box. Once an AI system is developed and deployed, it will keep on working forever with slight maintenance and effort.
Though initial investment in building the AI system would be significant, the returns are great.
If you are a business owner who is not tech-savvy but wants to have the best for your business and wants to implement AI, this article is for you.
As we advance, we will unpack what AI is and how it is revolutionizing the business landscape.
Let’s start by understanding what artificial intelligence is.
What is Artificial Intelligence?
Artificial Intelligence (AI) is a set of technologies that can be used to create software with human-like intelligence and processing. Computers and other such systems were often considered dumb and unintelligent as they would only give output based on input.
AI has gained so much attention amongst developers and it is one of the best choices for designing smart applications.
There are many popular AI programming languages which are used when it comes to designing AI-based applications.
With the progression in research and technological implementations, machines can now be given intelligence through algorithms and intelligent processes.
AI is often referred to as a wrapper for any smart system, but there are various branches of AI.
Some of those branches are discussed below.
Branches Of AI: Machine Learning
Machine learning is a subset of AI where systems are programmed to learn things on their own from a set of input data.
There are different types of machine learning, and they are all used for specific purposes.
Supervised learning is a type of machine learning wherein the input data is labeled, and sample output data is also given.
Different machine learning algorithms are deployed on the labeled input data, and the algorithms try to find a relation between the data and come to the labeled output.
On the other hand, when input data is unlabelled, a machine learning algorithm tries to come up with relations and inferences between the data points. Such an approach is called unsupervised machine learning.
There is one more type of machine learning where the machine learns and gets better over time.
Input data is provided, and the algorithm is defined to perform on the data. If the model makes the right choice, it is rewarded, and if it makes a wrong choice, it is punished.
This reward-based way of developing a machine-learning model is known as reinforcement learning.
Neural Networks
Human brains are based on a large number of tiny neurons that work together to complete tasks and make decisions.
With the help of mathematics, and neurology, such neurons can be created artificially, and they are also known as perceptrons.
Neural networks are a type of AI that replicates neurons inside human brains.
These neurons apply various statistical algorithms and techniques to complete tasks or make any decision similar to humans.
Natural Language Processing (NLP)
Humans understand natural languages, while computers and software products only understand commands in binary.
There was always research behind how to make computers understand commands in natural language, and natural language processing came to light.
Natural language processing is a branch of AI that deals with searching, understanding, analyzing, and deriving knowledge from unstructured datasets full of natural text.
It is used in many different places, and some of the prominent applications of NLP are spam detection, sentiment analysis, understanding the intent of conversations, replying to queries, etc.
Having known about the different branches of AI now is the best moment to know how this technology is revolutionizing businesses.
How AI is Revolutionizing the Business Landscape
Enhanced Data Analytics
Data analytics is one of the prime areas where AI is used in businesses.
Below are the three ways in which enhanced data analytics with AI makes a difference in businesses.
- AI-powered Data Collection and Processing
In traditional methods of data collection and processing, there is a high dependency on humans. Whenever the dependency on humans increases, the chances of errors also increase significantly.
AI algorithms can be used in a variety of ways to collect data from varied sources like web apps, social platforms, sensors, IoT devices, etc.
The algorithms can crawl, scrape and extract data from all the sources and store them in one place without any challenges.
Once the data is stored at a centralized place, AI algorithms can help in processing the data, cleaning it, standardizing the formats, and also filling the missing values with the most appropriate data points.
After data is cleaned, AI can help business owners process the newly acquired data and find many insights and patterns from the data easily.
- Real-time Insights and Predictive Analytics
Suppose you have a huge business where data is generated every moment, and it is important to leverage that data for business decisions.
In that case, AI systems can help you with stream processing and real-time analytics of the incoming data.
Such systems can continuously monitor and merge data coming in from various sources and process them in real time so that business insights can be derived for decision-making.
Predictive analytics is a type of data analytics that is concerned with predicting the future.
It is not just concerned about looking at the past data.
Predictive analytics through AI helps businesses to understand and predict customer behaviors, forecast demand for their businesses, find out fraudulent transactions, and many other things.
Machine learning algorithms can be applied to real-time data, and predictions can be made to forecast the future and make data-driven decisions easier.
- Improved Decision-making and Strategic Planning
AI helps businesses to predict or simulate environments that may arise during business transactions.
Predictive analysis models can predict the future based on historical data, and they can provide an idea of what can happen if similar situations arise.
AI algorithms can simulate various business scenarios, and organizations can always use these scenario-based models to find the most optimum decisions in such situations.
Overall, with the usage of scenario-based models and predictive analytics, management can understand the impact of their decisions even before the decision is made. Such an informed approach can help management to make more informed decisions.
Moreover, decisions taken with such an approach are better, and they are usually the ones that are best for any organization.
Automation and Efficiency
Another core implementation area of AI is automation and efficiency.
AI saves a lot of money by automating many simple and complex processes of businesses.
Here are some points on how businesses use AI for automation and efficiency.
- AI-driven Process Automation
AI-driven process automation is one of the most extensive applications of AI in businesses.
A large number of business processes can be easily automated with AI. You can set up an IoT network and infuse it with an AI system that can make decisions on its own.
Once that is done, you can easily set up process automation for your business.
Process automation with AI in a factory may work like once the raw materials are loaded in the area, a machine might be started that cleans the raw material.
Once the cleaning machine stops, the conveyor belt may take it to a set of other machines that complete the manufacturing.
AI systems can even complete the packaging based on the type of product manufactured, and they can make the finished goods ready for dispatch.
- Enhanced Productivity and Cost Savings
Once AI systems are installed in your manufacturing units, you can reap their benefits for a long time.
AI can make a lot of your workers free to focus on better tasks which will ultimately increase their productivity.
Moreover, AI process automation provides immense cost savings by removing the need to hire multiple people for the same task.
Personalized Customer Experience
Providing a good customer experience is quite essential.
Without customer experience, many businesses lose their customers to competitors.
While the ones who have learned to use AI in customer experience, they do it in the following ways.
- AI-based Customer Segmentation and Targeting
Every business has significant data about its past customers, and a lot of sales and revenue come from repeat customers.
If a business wants to find its best customers, it is pretty easy with AI.
AI algorithms can be used to carry out customer segmentation and clustering. This helps businesses to group customers with similar attributes together and cluster them so that they can be targeted.
AI can also be used to identify high-value targets for lead generation and sales.
A customer who has interacted with your brand multiple times is undoubtedly a better target than one who does not know about your brand.
You can identify targets in a better way through AI algorithms, clustering, and segmentation techniques.
- Chatbots and Virtual Assistants for Customer Support
Hiring a lot of customer care representatives is a thing of the past.
With AI-based chatbots and virtual assistants, businesses can solve a large number of common queries of their customers quickly.
Chatbots are easy to make, and they provide an effortless way for customers to get their queries solved in real-time without waiting for customer representatives to be available.
Conclusion
Though there are many other areas where AI is used in businesses, these are the primary areas where every business uses AI.
With the extensive usage of AI systems, the business landscape is changing rapidly, and the businesses that do not adopt AI will have to pay the price by losing their customers and competitive edge.
