The Use of Ai in Real-time Data Analysis and Decision-making

Data can be the most powerful tool in a business’s arsenal. For organizations to use data efficiently, they must be able to interpret structured and unstructured data in real time. Historically, real-time data analysis is a pain point for companies of all sizes. Luckily, modern AI technology can shed light on complex data sets.

How Does AI Fit Into Real-Time Data Analysis and Decision-Making?

AI tools can analyze and interpret extensive structured and unstructured data sets in significantly less time than humans. As these tools learn more about the data, they can make predictions and help business owners make better decisions. For example, an essential oil business owner trying to decide whether to open a location in Kentucky can use AI to interpret unstructured social media data about essential oil use in Kentucky. The AI could then decide whether Kentuckians had a significant enough interest in essential oils to warrant the decision.

The Long History of AI in Business

In 1961, Unimate, an industrial robot tasked with transporting die castings and welding car parts, began working on a General Motors Assembly line. This robot didn’t possess decision-making capabilities but was the first instance of automating work tasks with robotics or AI. By 1966, ELIZA, a precursor to modern chatbots, was invented by Joseph Weizenbaum. This technology was foundational for the chatbots used today in customer service.
AI’s first boom was in the 1980s, as technologies like XCON, an AI built to order computer components, hit the commercial market. During this time, the Japanese government began investing heavily in commercial AI applications. The rise of big data, cloud computing, and machine learning technologies in the 21st century has further propelled AI's adoption in business.

AI in Business Analytics

AI tools with real-time data analysis and decision-making capabilities let businesses capitalize on emerging opportunities, optimize resources, and mitigate risks. Companies utilizing AI tools have a competitive advantage, as they can analyze unstructured data faster and more accurately than their competitors. Additionally, AI tools cut expenses since they can handle the workload of several teams of employees at a fraction of the cost.
Real-Time Data Analysis and Decision-Making

What Is Real-Time Data Analysis?

Real-time data analysis involves collecting, processing, and analyzing data as it is generated or received. This type of analysis is virtually impossible with human employees. With this strategy, businesses can identify patterns, trends, and anomalies as they emerge, allowing them to make informed decisions and predictions based on up-to-date information.

What Is Real-Time Decision Making?

Real-time decision-making involves rapidly evaluating and responding to new information within seconds or minutes. Often, real-time decision-making isn’t optional, as natural disasters, PR emergencies, and unexpected events can force a business to develop mitigation strategies in the spur of the moment. Still, quickly making decisions can effectively optimize business performance, even when it isn’t in response to an emergency.

Three Important Benefits of Real-Time Data Analysis and Decision-Making

1. Enhanced operational efficiency: When businesses are current on the latest developments that may impact their operations, they can avoid potential bottlenecks and allocate resources where they're needed most.
2. Improved customer experience: Real-time analysis lets businesses anticipate their customers’ needs, adjusting their product offerings and services accordingly.
3. Better risk management: Companies can identify potential risks before they halt business operations.

Benefits of AI in Real-Time Data Analysis and Decision-Making

Use AI to improve Efficiency and Accuracy

AI algorithms can rapidly process large volumes of data, identifying patterns and anomalies that might go unnoticed by human analysts. This increased efficiency allows organizations to make better-informed decisions and respond more quickly to changing circumstances. Additionally, these tools can analyze unstructured data, which is notoriously difficult for humans to manage efficiently.

Make Lightning-Fast Decisions

AI programs can analyze and interpret data in a fraction of the time humans require. This enables organizations to make more timely decisions and react promptly to market changes, customer demands, or internal issues. Some AI tools can partake in decision-making, helping business leaders determine the best course of action without stalling.

Enhance the Customer Experience

AI-driven real-time data analysis can enhance customer experiences by providing personalized recommendations, resolving customer queries, and addressing customer issues. For example, AI-powered chatbots leverage real-time data to offer personalized assistance, and customers don’t have to wait on hold to speak with them.

AI Leads to Increased Profitability

AI-driven insights help businesses identify new revenue streams, optimize resources, and reduce operational costs, allowing companies to achieve the same amount of work with fewer employees. Not to mention, AI programs can run through the night when other employees are gone. Continuously running AI programs lets brick-and-mortar locations operate some facets of their business 24/7 while cutting down on utility expenses.

Challenges of AI in Real-Time Data Analysis and Decision-Making

Technical Challenges

Implementing AI in real-time data analysis can present various technical challenges, such as integrating AI with existing systems, selecting the right algorithms, and scaling AI solutions. Organizations must have a clear understanding of their technical infrastructure and limitations. Often, a company’s development team will be unfamiliar with AI programs, meaning they may need to hire new employees.

Data Quality Challenges

AI programs make inaccurate predictions or decisions when they’re fed inaccurate data. These tools often lack the human tendency to question the information they’re presented with. Additionally, AI tools are trained using human-generated content, meaning they may learn human biases. These biases can then affect an AI’s interpretation of a data set.

Ethical Challenges

AI-driven data analysis raises several ethical concerns, including data privacy, algorithmic bias, and transparency. Organizations must establish ethical guidelines and adhere to data protection regulations to maintain public trust.
After implementing AI tools, businesses will surely question whether they need their entire employee base. The use of AI tools often leads to some employees losing their jobs, making the human cost of implementing AI tools potentially quite high.

Best Practices for Implementing AI

Establish Clear Goals and Objectives

Before implementing AI, organizations need to understand how they’ll use it. Identifying the problems that AI can address will ensure that needless software integrations don’t bog down business operations. After the integration, businesses should set measurable performance indicators to ensure the tools have the intended effect.

Ensure Data Quality and Accessibility

High-quality data is essential for accurate AI-driven analysis. Organizations should invest in data validation, cleaning, and integration processes to ensure their AI solutions can access accurate and up-to-date information. It’s essential to develop strategies to verify the validity of the data sets if AI tools are used in collecting and structuring data.

Make Sure You Have a Skilled Team

A well-rounded AI team comprises professionals with expertise in various fields, such as data science, machine learning, and computer programming. Ongoing training and resources are imperative. If the business owner isn’t skilled in AI, it’s best to outsource the creation of training materials.

Real-World Examples of AI in Real-Time Data Analysis and Decision-Making

Amazon Go

Amazon Go uses AI-powered computer vision, sensor fusion, internet of things (IoT) devices, and deep learning algorithms to detect customers' actions, such as picking up items from shelves. This real-time data analysis enables the store to automatically charge customers for purchases without going through traditional checkout lines.

Netflix

You’ve likely experienced Netflix’s real-time analysis first-hand. When you begin watching more true-crime series, you’ll notice more of them being recommended. This is because Netflix utilizes AI to analyze real-time user data and make personalized content recommendations.
By continuously updating its recommendations, Netflix improves its user engagement and customer retention.

Uber

Uber uses AI algorithms to predict demand, optimize pricing, and efficiently match drivers with riders. Its AI tools incorporate customer and driver location, time of day, and traffic patterns to estimate arrival times more accurately.

How Will AI Affect Business in the Future?

Machine Learning and Predictive Analytics

As AI algorithms become more sophisticated, predictive analytics will enable businesses to identify potential opportunities and risks more precisely. For example, financial institutions can use AI-driven predictive analytics to assess credit risk, detect fraudulent activities, and optimize investment strategies.

Advancements in machine learning will enable more accurate predictions. AI developers are sure to improve unsupervised learning algorithms, which can identify patterns in data sets without human intervention. This technology will increase the speed and accuracy of businesses’ predictions.

Natural Language Processing (NLP)

As NLP algorithms continue improving, AI systems will better understand context, nuance, and emotion in human language. This will let businesses analyze customer feedback more accurately while monitoring brand sentiment.

Internet of Things (IoT)

IoT devices are interconnected machines that collect and transmit real-time data. AI-powered IoT sensors can monitor equipment performance, detect potential issues, and initiate preventative maintenance to reduce downtime. As these devices become smarter, they’ll be able to contribute to businesses in new ways.

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AI technology is here to stay and will likely become a bigger part of our lives in the coming years. Set yourself up for success in the AI-driven future by getting your Master of Science in Artificial Intelligence in Business. University of the Cumberlands offers a flexible class format designed with working adults in mind. You won’t have to put your career on pause to advance your AI skillset.