What is the Role of AI in Business Analytics?

Ever since ChatGPT became the next best thing after Wordle, the world has been finding new ways to use artificial intelligence to make their lives easier. Among other things, machine learning and advanced algorithms could be used for data analysis and empowering decision-making. But are we there yet?

What is business analytics?

Business analytics is the use of data analysis, statistical models and quantitative methods to interpret and analyze business data. The end goal is to understand available data, predict business performance, spot trends and anomalies and most importantly, make better decisions for the future of your business.

Does AI have a place in business analytics?

AI-powered tools have taken the world by storm in recent years, but the average CEO or upper-level executive may have concerns when using AI for automation, forecasting and solving business problems. They might worry about the reliability of AI algorithms, the potential loss of human touch in customer interactions processed by these tools. However, when implemented thoughtfully, AI tools can help in everyday work tasks, starting from AI meeting note taker solutions to AI-powered chatbots, they can complement human expertise, offering efficiency.

The reality is that AI definitely has a place in business analytics, as it helps make business decisions faster, it enhances the depth and speed of analytics and it allows teams to automate routine tasks so they can focus on the business strategy.

The way we see it at Luzmo, the future is not fully AI-powered, but AI-enhanced. With the right AI tools, data analysts can work more quickly with big data sets and automate tedious tasks around data collection, the cleanup of unstructured data, and more.

For business users outside of the data world, AI lowers the barrier to entry. It will no longer be necessary to understand complex BI terms in order to analyze and visualize data, and make a strategic decision about your business.

The benefits of using AI for business analytics

Whether you’re a business analyst, a marketing manager or a CEO, AI, machine learning and natural language processing (NLP) have something to offer for you. These are the main benefits of AI in business analytics.

Improved accuracy and efficiency: AI can analyze vast amounts of data in a short period of time, helping your team get to actionable insights and more informed decisions quickly. At the same time, it reduces the number of in-house experts you may need for data analysis.

Predictive analytics: supported with the right models, AI can fairly accurately predict future outcomes based on historical data. When trained on the right datasets, AI can be very useful in predicting the future of your business.

Personalized insights: with proper setup, business analytics dashboards can be tailored to your own unique needs and requirements. AI can use the surrounding context for the data to create tailored insights for the specific end user. 

For example, a marketing manager could open their marketing software and use AI to tailor the insights based on the most commonly used features, viewed reports, their role in the company and more.

Real-time analytics: your business initiatives don’t have to wait for the data team to finish with a data model or create a specialized dashboard. Relevant stakeholders can get insights into business data by probing their data in real-time.

Scalability: AI tools can accommodate large datasets and an increasing number of users. You can work with 50 users as easily as you would with 5. This makes decision-making accessible to a larger group of people who may not know much about data analysis.

The concerns of using AI in business analysis

While machine learning algorithms can automate repetitive tasks, there are a few concerns that business leaders should be aware of before trusting AI algorithms with making data-driven decisions.

Data quality and quantity: the effectiveness of AI analytics in any business largely depends on the input. The data quality needs to be impeccable for the end-results to be accurate and actionable.

High initial costs: for some businesses, it can be costly to get started with AI analytics. Infrastructure, software, people - the costs add up.

Biases and fairness: AI models are trained on existing data. This means that your analytics tools can give biased and inaccurate results and predictions.

Security concerns: some AI technologies rely on third-party software that can use your data for training purposes. When choosing your next AI business analytics tools, make sure to understand how they handle your data (and customer data) and who has access to it.

Over-reliance on AI: when overused (for e.g. predicting market trends), AI can cause teams to lose focus on data analytics and let the algorithms do all of the heavy lifting.

Integration challenges: to get valuable insights through means such as visualization of real-time data, you’ll need to integrate AI tools in your existing workflows. Without proper development and data analytics help, this can be costly and time-consuming. 

How Luzmo’s AI features can help with business intelligence 

The truth is that AI is still not in a place where it can autonomously do data analysis, visualization, forecasting and all the advanced operations required from a data science team. However, generative AI is becoming advanced enough where it can provide a competitive edge to any business when used in the right way.

Luzmo’s AI tools allow anyone to do data visualization and analysis with some light prep work. And thanks to our simple embedding, you can add these capabilities straight into your software product too.

Our AI Chart Generator uses natural language processing to help end-users type in a query and have a fully functional dashboard within a few minutes.

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Our Instachart lets you turn sketches, screenshots and design mockups into fully functional dashboards. Upload a design and watch AI turn it into a dashboard in front of your eyes.

At Luzmo, our tools won’t replace a data scientist on your team. However, they will help you build more user-friendly data products, so your product users can analyze large volumes of data more easily and streamline their operations. For your end users, this means no longer needing a degree in data science to play and work with data.

Don’t take our word for it - grab a free demo of Luzmo and see how AI and business analytics can work together.