Unlocking Insights into the Use of AI in Business Analytics

The use of AI in business analytics is becoming increasingly popular, transforming the way organisations make decisions and streamline operations.

Whether you’re a business analyst wondering how your role will change with the implementation of AI development services, a business wanting to know how to leverage technology for maximum success, or an individual simply curious about why efficient business analytics matter, read on for more details.

AI in Business Analytics: Changing the Role of Business Analysts

So, how is artificial intelligence shaking up the role of business analysts? Well, if you work in business analytics, you’ll know how burdensome and time-consuming some mundane tasks can be. However, when you use AI in business analytics, time can be freed up for the professional to think strategically and creatively, enabling them to focus on more demanding initiatives.

Therefore, not only is AI changing business analytics by making tasks and roles more productive, but it can also encourage a sense of forward-thinking and innovation throughout companies.

So, Why Does Business Analytics Even Matter?

At this point, you may be wondering why it’s so important to streamline the business analyst role. Well, business analytics is vital for driving informed decisions, improving operations, and enhancing the profitability of businesses in the long run.

Uses of AI in Business Analytics

There are many uses of AI in business analytics, so we’ve just listed some of the most popular ones below.

AI in business analytics can be used to:

1. Enhance data analysis

The most obvious use of AI in business analytics is that it can be used to process large amounts of complicated data in a short space of time. This can help business analysts gather more accurate business insights quickly, enabling organisations to create an informed plan of action that they can rely on.

2. Automate routine tasks

One of the handiest things about AI in business analytics is that it can automate routine, mundane tasks in business analysis. This could involve anything from reporting to data collection to sentiment analysis.

Not only does this take away the risk of human error, but it can also free up employees to focus on more complicated tasks and enhance the overall efficiency of the business.

3. Improve predictive analytics

Using AI for predictive analytics is now widespread within business intelligence. AI can be employed to analyse datasets like customer, marketing, and sales information, enabling businesses to uncover customer insights, potential market trends, and possible future risks.

By becoming aware of certain predictions, organisations can develop useful strategies to assist in the overall efficiency of business analysis processes.

4. Increase personalisation

AI can now be leveraged to analyse customer data and generate segments based on demographics, behaviours, and preferences. What this means is that organisations can now target specific customer segments with customised communications and special offers that are relevant to them.

Furthermore, AI can even recommend products or services to consumers based on their previous browsing behaviour and preferences, improving the overall customer experience and increasing conversions.

5. Leverage Natural Language Processing

As you may already know, Natural Language Processing models like LLMs can enable individuals to ask questions and receive a data-driven answer. Natural Language Processing can also analyse unstructured text data and develop valuable insights, from product feedback to customer sentiment. In turn, this can help guide a company in their current strategies.

The Benefits of AI in Business Analytics

From looking at the uses of AI in business analytics, you’ll probably be able to predict a few benefits your business can gain from this implementation. However, if you’re still unsure, we’ve created a list below!

Using AI in business analytics can:

• Improve fraud detection and risk management

AI can excel in detecting cybersecurity threats and fraudulent activities by picking up on anomalies and suspicious patterns. It can be leveraged to flag potential fraudulent transactions quickly so your business can act before it is too late.

Even better, AI-powered risk management tools can assess and mitigate potential risks, allowing organisations to safeguard their assets and preserve their reputation and credibility with key customers.

• Boost the customer experience

As we’ve already mentioned, AI can personalise interactions with all types of customers. While this was once a key factor to help businesses stand out, personalisation is now a necessity that customers have grown to expect.

This means it’s now more crucial than ever to leverage AI-driven analysis to start understanding your customers’ preferences and behaviours to segment them and create highly personalised communications. This can help you generate customer loyalty and satisfaction.

• Enhance accuracy

By eliminating the risk of human error, AI can create more accurate analyses and outcomes when implemented in business analysis processes. This means businesses can access real-time insights they can trust.

• Reduce costs

AI could be the answer if you want to streamline your business processes while saving money. 

AI has the power to detect inefficiencies and optimise your organisation’s resource allocation, which can lead to enhanced productivity and reduced costs in the long term. Furthermore, you can decrease labour costs by automating manual tasks. Win-win!

• Increase your competitive advantage

It’s becoming harder and harder to stand out in business, so why not give yourself the edge you’ve been waiting for by leveraging AI?

AI can help your business respond faster to market changes by providing real-time insights and speeding up decision-making procedures. It can also help you identify or predict new trends to help you stand out in the industry.

Our Top Tips on How to Use AI as a Business Analyst

Knowing the uses of AI in business analytics is one thing, but implementing them is another. So, how can analysts start employing AI? If you’re a business analyst wondering how you can start using AI in data analysis, check out these top tips:

1. Encourage learning

Continuous learning is key to this process. AI is showing no signs of slowing down, so neither should your business analysts. By promoting a culture of continuous learning and offering training opportunities, you can help the whole team adapt and maintain its relationship with AI.

2. Use the right tools

The right results start with using the right tools. Arm your team with the tools to expand their capabilities and streamline decision-making processes. By becoming familiar with how AI-powered tools can automate data processing and analysis, predict future outcomes, and suggest recommended action plans, business analysts can streamline their own roles, make smarter data-driven decisions, and generally become more confident around AI.

3. Consider ethical standards

Remember to update your policies and processes when necessary, ensuring that the ethics of AI in business are always taken into account. There are often concerns with data privacy when AI comes into play, which is why your organisation needs to enforce compliance. Not only can this help you keep data secure, but it can also help you avoid other risks, such as biased outcomes.

4. Always communicate!

Your team needs to stay up-to-date with your AI practices, so you must remember to allocate someone responsible for managing change as the business analyst role adjusts. Business analysts and data scientists need to be able to communicate and work across departments, meaning they’re always informed about what will change and what will stay the same. This can also bridge the gap between data expertise and business acumen.

5. Prioritise data quality

AI relies on high-quality data for high-quality outcomes, meaning your team needs to focus on data accuracy and consistency. It might be helpful to frequently clean and manage your organisation’s data, ensuring that outputs are as reliable as possible when taking action.

Will Business Analysts Get Replaced by AI?

Now that you know a bit more about how a business analyst can utilise AI, you may be wondering if there is a chance they may get replaced altogether.

While artificial technologies have the chance to reshape the role of business analysts, it is unlikely to fully replace humans anytime soon. Combining AI efficiencies with the expertise, experience and common sense of human professionals is typically the best way to make the most of AI in your business analysis.

While AI excels in data analysis, processing, reporting, predicting trends, and automating processes, humans still need to be able to tackle complex problems that require creativity and critical thinking. Furthermore, business analysts are required for effective communication with stakeholders – something that AI can’t always pull off.

To remain relevant in the field, human business analysts may have to adapt by learning how to collaborate with AI in their daily tasks, such as understanding machine learning algorithms.

What is the Future of Business Analytics with AI?

We have a few predictions when it comes to the future use of AI in business analytics – we can’t wait to see where these new trends take us!

• Business analysts will learn to adapt to and collaborate more efficiently with AI
• Routine tasks, from data cleaning to reporting, will become increasingly automated by AI
• AI models will become more sophisticated in predicting future outcomes, leading to more informed business decisions
• Advancements in AI will make it easier to analyse data in real-time, allowing businesses to respond promptly
• AI-driven personalisation will give greater insights into consumer behaviour and preferences, allowing businesses to create tailored marketing and customer relationship strategies

Implement AI in Business Analytics with McKenna Consultants

Here at McKenna Consultants, we know all about the use of AI in business analytics and are here to help you implement the necessary changes to streamline your organisation.

Our team are well-practised in this field, having created AI assistants and implemented Retrieval-Augmented Generation solutions. If you want to discover our services in more detail and see how we can help you streamline data analysis, please get in touch with us. We’ll be happy to help!

Plus, if you can’t get enough of our AI insights, don’t forget to check out our blog.