Artificial intelligence has been around for a while, but it is only recently that we have begun to see its true potential in practical terms. With the development of machine learning and natural language processing (NLP), AI is now able to provide decision support systems that can help businesses and investors make better decisions faster and more efficiently.
More industries are adopting AI decision support systems to ease their workload and assist them in their day-to-day operations.
In this blog post, we’ll explore the role of AI in business and investment decision-making, and look at some of the exciting applications of this technology.
What are Intelligent Decision Support Systems?
Intelligent decision support systems (IDSS) use artificial intelligence (AI) to help humans make better decisions by providing them with relevant information and recommendations.
IDSS use a variety of data sources, collate them and process them to generate useful insights for analysts. Artificial intelligence decision support systems then offer recommendations and communicate them to users in a way that is easy for them to understand.
Nowadays, most businesses and investors have no trouble gathering enough relevant data, but knowing how to process it and what to do with the resulting insights has become the hardest and most time-draining challenge.
That’s where decision support systems that harness the computing power of AI technology come in. By automating the data processing and analysis, as well as generating recommendations, AI decision support systems can help businesses and investors make data-based decisions faster, and feel more confident about them to boot.
Benefits of Using Artificial Intelligence in Decision Support Systems
Artificial intelligence decision support systems offer a number of advantages over traditional methods of data analysis and decision-making.
Processing large amounts of data
AI can process large amounts of data much faster than humans. This is important because the more data that is available to an IDSS, the better it can identify patterns and correlations that would be difficult for humans to find.
Processing unstructured data
A lot of the data that is relevant to businesses and investors is unstructured, such as social media posts, customer reviews, and surveys. AI systems that use the most NLP technology are particularly good at processing this type of data and extracting useful insights from it.
AI decision support systems can filter out irrelevant information and focus on the most important data points. This is essential in today’s business environment, where there is an overwhelming amount of data available from a variety of sources.
Another useful feature of some AI decision support systems is their ability to generate recommendations based on the data they have processed. This can save businesses and investors a lot of time and effort in making decisions.
AI decision support systems can help businesses and investors avoid bias in their decision-making. Human data analysts may have personal biases that can distort their analysis of data, but AI systems are not susceptible to this.
The Exciting Future of NLP Technologies
One of the most exciting advancements in AI technology with applications in DSS is in the field of Natural Language Processing (NLP). NLP is a branch of AI that deals with the ability of computers to understand human language.
NLP technology has come a long way in recent years, and is now able to understand the context of language as well as the literal meaning of words. This has led to some amazing applications of NLP, such as chatbots that can have natural conversations with humans, and voice assistants that can understand complex commands.
When it comes to IDSS, NLP technology is used to process the unstructured data that is often relevant to business decisions. For example, in business, NLP can be used to analyse customer reviews and social media posts to identify sentiment and generate insights about customer satisfaction.
For investment decision-making, NLP can, for example, be used on quarterly earnings calls from leading firms of an industry. Word choice, tone and intonation on these calls can give analysts clues about how management feels about the current state and future prospects of their company.
Turning this unstructured data into structured data enables data analysts to make informed decisions manually about which companies to invest in and when, or these insights can be further processed by an artificial intelligence decision support system to generate automated recommendations.
How Intelligent Decision Support Systems Are Used
Artificial intelligence decision support systems have applications in a wide variety of industries. Below are just a few examples of how IDSS are currently used.
In marketing, IDSS can be used to generate insights from customer data, such as social media posts and surveys. This information can then be used to improve customer satisfaction or target marketing campaigns.
In eCommerce, IDSS can be used to recommend products to customers based on their previous purchases or browsing history. This can lead to increased sales and customer satisfaction.
In medicine, IDSS can be used to diagnose diseases, recommend treatments and predict patient outcomes. This can help doctors to make better decisions about patient care. Clinical decision support systems (CDSS) implementing AI are being developed by biotech companies to enhance diagnostic accuracy and assist physicians in their stressful work.
Investment Due Diligence
In investment decision-making, IDSS can be used to analyse data from a variety of sources, such as financial reports, news articles and social media posts. This information can then be used to generate investment recommendations.
IDSS can also be used to monitor a portfolio of investments and provide alerts when there are changes that may impact the value of the portfolio.
Artificial Intelligence decision support systems are a powerful tool that can be used in a variety of industries, from marketing to medicine.
NLP technology is a particularly exciting branch of AI for DSS, helping to process and generate insights from unstructured data, which can then be used to make informed, data-based decisions.
IDSS have the potential to transform the way businesses operate and make decisions, saving time and effort while also improving accuracy. In the future, IDSS are likely to become an essential part of many industries.
Get Started With Symanto
Symanto is a world leader in NLP research and technology. If you’d like to learn more about how NLP can be used in decision making, get in touch with us today. We’d be happy to discuss your specific needs and requirements.