AI will change every aspect of our lives, especially in the work environment. Most roles are going through a big shift, and business analysts are no exception. But instead of focusing on the possibility of replacement, it's worth seeing the opportunities for everyone to get rid of repetitive tasks and instead focus on problem-solving activities and strategic thinking.

In this article, you'll learn how artificial intelligence is changing business analysis, what it means for your organization, and how it relates to predictive valuations.

Will business analysts be replaced by AI?

Answering this question with full certainty is impossible, as it is close to predicting the future. However, with the information available today, it's safe to say that business analysts will not be replaced anytime soon.

What is happening, according to several experts, is that AI is automating tasks, analyzing large sets of data, and making connections between several information streams which then can be contextualized by a business analyst.

"Exploring data holistically with machine learning allows analysts to look at questions they haven't been able to consider before. For instance, what if customer demographics weren't as important in generating sales volume as other (previously unanalyzed) drivers?," wrote Michael Amori, CEO of Virtualitics, on Forbes.

How AI is used for business analytics

Using AI today is a matter of survival. According to the latest McKinsey Global Survey on AI, 65% of respondents report that their organizations regularly use gen AI, nearly double the percentage from a year ago.

Business analysis is an area that can expand its impact by using AI technologies to go over large volumes of data, predict market trends, and identify patterns at scale.

However, the human perspective is still needed. Business analysts play an essential role in the interaction between artificial intelligence tools and the rest of the organization. They're responsible for translating the findings of the IT team to others, working with other departments to fulfill requirements, understanding and improving business processes, and problem-solving.

Business analysts who use AI-powered tools can provide actionable insights for organizations. Through predictive analytics, the executive team can make better decisions regarding resource allocation; by using natural language processing, analysts can extract valuable insights from unstructured sources of information, leading to a better understanding of their target audience or customers.

Here are some of the most frequent uses this valuable tool has regarding business analysis:

1. Data-driven insights

Data is the fuel for business analysis, and by using AI systems, professionals can extract insights that will help CEOs make better decisions. This technology can handle large volumes of data and efficiently identify patterns, trends, and correlations.

Business analysts can better understand the customers' behavior, market preferences, and industry trends. This information allows executives to seize opportunities and reduce potential risks. Companies can use this new knowledge to polish their growth strategy, enhance their customer service, optimize their resources across the organizations, find potential opportunities in the market, and make decisions aimed at increasing profitability.

2. Automation

Another use of artificial intelligence is the possibility of automating repetitive tasks. Doing so can result in less staff focusing less on time-consuming tasks, and more strategic thinking can bring profit to the business. Some tasks that can be covered through automation are data collection and cleaning, report generation, and predictive analysis. Automating these activities can give business analysts more time to understand complex business requirements and to work on relationship-building with key members from other teams.

3. Customized customer experiences

AI is also used to offer a unique customer experience to current clients. Businesses can do so by having a tailored approach to each client based on their preferences, previous behavior, and past use patterns of the service. This segmentation can be used to provide better customer service, run specific marketing campaigns, create sales bundles for a group of clients, and more.

4. Predictive analysis

With predictive analytics, business analysts can gain valuable insights by reviewing historical information, analyzing market and industry trends, and even considering other predictive models. As a result, AI will show industry patterns, forecast customer trends, identify potential risks, and more. With this information, companies can pivot their strategy and stay ahead of competitors.

5. Improved risk management

With the use of AI, the IT team can find potential cybersecurity threats. Fraud detection models powered by this technology can review past data to find patterns and use those to flag any potential fraudulent activity.

6. Enhanced efficiency 

AI can be used across an organization; its benefits aren't only for a department since it can boost efficiency throughout the company. Using data analysis, marketing teams can identify useful patterns for paid campaigns that can be used later to get the most out of resources. Furthermore, business analysts can automate several routine tasks to focus on critical thinking issues affecting the organization's results. Overall, AI excels at providing useful insights that can help solve business needs.

How to integrate AI with business analysis

AI is a technology that can be used in several industries and for different purposes, and when properly integrated into business analysis, it can be a powerful ally for the company's key decision-making. These are a few ways to integrate AI when doing business analytics.

1. Choose the best AI tools for your business

Business intelligence tools can provide valuable insights by allowing you to look over several scenarios with little data, automate reports, and create data stories based on your findings. Some of the most popular tools are Tableau (data visualization and business analytics), ChatGPT (prompts for business analysts), MonkeyLearn (no-code text analytics), Microsoft Power BI, and Akkio (AI assistant for data).

2. Learn how to integrate new AI tools into the business

It's safe to say that new AI tools will keep developing new and powerful features. In light of that, embrace a culture of early adoption within your business that allows you and your team to find a potential new tech ally. By exploring and learning what these new tools can do for you and your venture, business analysts will be eager to try new alternatives.

3. Update your decision-making process according to new tech

With AI tools changing how you make business decisions, your processes and policies should also be updated. Previously, you probably had to review some scenarios backed by historical data analysis. Now, you have to find the best option among scenarios built based on past data and predictive models.

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