The applications of artificial intelligence in business continue to evolve as a result of incredible advancements in computing capacity which facilitates more complex programs than ever before. Decision intelligence, the convergence of technology and business needs, enables companies to think on a global scale and react quickly to opportunities. The growing prominence of artificial intelligence in helping to make crucial decisions characterizes both large and small businesses, but yet, there are still many companies hesitant in adopting the technology.
The applications of data-driven AI are no longer restricted to large companies working on massive budgets or technology companies with specialized knowledge. The technology can be easily leveraged by small to medium businesses by partnering with the correct group of data scientists.
Predictive vs. Prescriptive Analytics
In the past two decades, an AI technology that has grown significantly is prescriptive analytics. It enables companies to understand what they should do in response to given data and parameters. This application of AI involves complex programming and a massive amount of data, but it can produce highly accurate results.
Predictive analytics involves anticipating what will happen to a company in the future or what will occur based on a selected market.
Also, it plays a significant role in decision-making. Jumping from predictive to prescriptive analytics requires the use of artificial intelligence to support decision-making.
The Role of Computers in Business
Any business can leverage cost-benefit analysis using AI decision-making algorithms. It enables them to decide the best plan of action for maximizing profit or managing revenue effectively. Computers can manage a higher number of variables than the human mind, as a result, AI can formulate insights that simply cannot be derived from human decision-making techniques.
Humans are still needed to start and sometimes monitor computer-generated decisions, especially when the system is presented with new information it hasn’t learned yet.
Businesses can also use mobile business intelligence which allows employees to gain access to data and make decisions on the go. However, due to such advancements in AI in the past two decades, human decision-making is more than likely to be vulnerable to bias or flaws than AI-based decision-making.
High-level knowledge intelligence systems also function as the spine of the greater field of AI in business and marketing. Each decision-making system functions using AI that comprehends concepts instead of just storing data.
Ai can achieve human-like understanding using machine learning and the correct input from data scientists. Machine learning drives AI feedback in response to false positives or negatives that happen in the overall decision-making process.
Applications Across Industries
There is a wide range of potential applications for artificial intelligence that can vary according to the industry it is deployed in. Nowadays, it is very common for financial institutions to leverage decision intelligence to process credit applications, including applications for car loans and mortgages. Artificial intelligence can utilize a customer’s credit score, income and other related data to instantly assess if the client is eligible for certain goods and services.
A financial institution can also leverage decision intelligence to assess where and how much they should expand physical branch locations. This AI can use information such as projected growth, existing locations and customer intelligence to formulate a potential list of locations that are expected to deliver the maximum return on investment.
Retail companies can leverage decision intelligence to determine exactly how much inventory they should buy and when they should order it. Any service or retail business that depends on marketing can leverage AI to understand how much budget they should set aside for investing in marketing channels, including TV,
Oil and gas companies, as well as healthcare organizations, can leverage AI to manage the restocking of materials and goods. It can also outline how many staff members should be assigned to certain shifts. The potential applications of the technology are near limitless and they can be customized to fit large or small organizations regardless of industry.
Computer systems are developed by humans and can be flawed at times. Our methods of thinking about, processing and storing data are greatly influenced by biases, which can affect any conclusions the programs create.
Humans might oversimplify programs or omit important data based on the assumption that it isn’t useful, unwittingly removing the information necessary for the program to create useful decisions. Fortunately, data scientists and programmers have created systems and pathways of thinking about data that have played a major role in overcoming these issues.
Moreover, innovations like data lakes and cloud computing can store vast quantities of data, enabling big data analytics and artificial intelligence to process better results and circumvent the oversimplification of data. The best methods of data management and analysis keep getting improved and refined due to more and more businesses taking advantage of leveraging this technology.
Businesses and organizations of all sizes have unrealized potential that often goes overlooked by human eyes. Artificial intelligence allows these businesses and organizations to gather meaningful insights from that data and has led to the creation of a new frontier across industries. The adoption of AI-based decision-making is only going to grow further due to continuous technological advancements and its growing adoption across all industries.