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4 Ways to Use AI in Data Analytics

| March 29, 2023 | By
A young data analyst reviewing financial data and taking notes.

By Debashis Rana - 

Every customer or patient interaction, connection between systems, and business process produces data. In fact, one estimate puts the amount of data produced every day at 3.5 quintillion bytes1.

So what does that mean for your organization? You’re likely sitting on a mountain of untapped potential to identify new products, operational efficiencies, and methods to wow your customers. However, you can only find these diamonds in the digital rough if you have the tools to process and harness all that data.

That’s why so many organizations invest in artificial intelligence (AI) to amplify the impact of their data analytics programs and find these insights faster and easier.

So whether you’re building out your data analytics program or looking for ways to boost its impact, here’s what you need to know about AI and data analytics, and examples of how you can use it to strengthen your customer experience.

What You Need to Know About AI

Even before the buzz around AI-powered chat programs like Google Bard and OpenAI’s ChatGPT2, AI was viewed as a powerful tool for business operations. At its core, AI refers to the simulation of human intelligence in machines3 that are programmed to think like humans and mimic their actions. 

Most often, AI is used to process large amounts of data quickly and accurately, boosting an organization’s ability to:

  • Detect patterns.
  • Make informed decisions.
  • Predict trends.
  • Identify insights that can drive new products.
  • Perform automated actions based on the above.

As AI performs these tasks, it can learn new techniques and perform new actions as the cycle repeats. Additionally, more organizations are turning toward AI as it can work without getting tired, has lower chances of making mathematical errors, and can process data around the clock.

Why Use AI with Data Analytics?

Every day, customers, employees, systems, and processes are producing data, making data analytics more complex and time-consuming. These challenges align well with AI’s strengths. In particular, AI can:

Accelerate traditionally slow, highly-manual processes.

AI can automate repetitive and time-consuming tasks, such as data entry, data cleaning, and report generation. Handing off these tasks to AI tools frees up time for valuable individuals in your organization to focus on more complex and creative tasks, such as developing new analytical models, exploring data, and identifying insights. 

Make unstructured data actionable.

Using natural language processing (NLP)3, transcription, and computer vision, AI can analyze unstructured data such as text, images, and videos. These techniques enable businesses to gain additional insights from diverse sources that would otherwise be difficult or impossible to analyze using traditional data analytics methods.

Amplify existing data analysis techniques.

By analyzing vast amounts of data, AI can help companies make informed, data-driven decisions. AI tools can quickly identify patterns and correlations that may be difficult or impossible for human analysts to detect, providing insights that allow for strategic decision-making.4 

4 Use Cases: How AI Amplifies Data Analytics Programs

AI has become increasingly prevalent across industries, with businesses leveraging its capabilities to automate processes, gain insights, and drive innovation.

Here are just a few examples of AI in action:

  • Finance and banking: AI can be used to monitor, detect, and flag unusual account behavior, identify trends that support new product development, or make processes like transfers and deposits more efficient.
  • Insurance: AI can improve the speed and accuracy of claims adjudication through consistent and fair application of business rules. AI can also reduce fraud by spotting anomalies and patterns otherwise hiding in the noise of everyday business.
  • Healthcare: AI already helps healthcare organizations process large amounts of data from diverse data sets to identify trends that lead to new or more effective treatment plans. Like other industries, AI is also being used to improve patient education and service by empowering personalized experiences.
  • Retail and Entertainment/Hospitality: Retail businesses can use AI to automate manual processes, process customer data to identify new products or friction points, or suggest product recommendations in real time, driving sales and reducing overall operating costs.

Bringing It All Together

From simplifying everyday tasks to churning through terabytes of data, AI is already revolutionizing our personal and professional lives. When paired with machine learning, natural language processing, computer vision, and more, AI can deliver the competitive edge businesses need in our increasingly digital world.

Are you ready to see how AI can streamline operations and boost your data analytics program? RCG has a team of experts that know how to put your data to work with cutting-edge AI solutions tailored to your business needs and goals. Click the link below to get started:

Schedule a Meeting


Works Cited

1. EarthWeb (2023, Apr 7) "How Much Data Is Generated Every Day in 2023? (NEW Stats)" Retrieved from

2. OpenAI

3. Investopedia (2023, Apr 24) "Artificial Intelligence: What It Is and How It Is Used" Retrieved from

4. IBM "What is natural language processing?" Retrieved from

5. Techradar (2022, Jun 6) "Why data is key to enhancing the customer experience" Retrieved from