3 Major Ways Generative AI is Revolutionising the Business Analysis Field

Got the talent for analysing business goals and developing insights that improve a company's processes? Then a career in business analysis is for you. Business analysts (BAs) are currently in high demand in Australia, with the latest data from SEEK showing that the field is set to grow by more than 27% in the next five years.

This upswing is mostly due to the ability of BAs to leverage data-driven decision making, streamline workflows, better respond to trends, and improve customer satisfaction. BAs have also become more important than ever when it comes to protecting organisations from various cyber threats.

And as BAs continue to evolve in their role, they now face an emerging technological development: generative artificial intelligence (AI). This powerful technology is set to revolutionise the business analysis field, offering both opportunities and challenges.

In this blog, we will discuss what generative AI is, its role in business analysis, and the challenges that BAs face in using it. We will share how Lumify Learn can help you enter the thriving business analysis field through online skilling.

What is Generative AI?

Generative AI is a subset of AI that produces text, images, videos, or other forms of content in response to a user’s request or prompt. It works by learning structures and patterns from various datasets using advanced algorithms trained to replicate and understand the data they are exposed to.

While this type of artificial intelligence has been around for some time, the technology gained significant popularity in 2022 with the release of ChatGPT. Shortly after, other companies like Microsoft and Google launched their own generative AI tools as well. Services like Copilot and Gemini are now part of everyday conversations (Pro tip: You can master the Microsoft Copilot range of applications with training from our sister company, Nexacu).

Generative AI is currently used in many fields like healthcare, finance, manufacturing, software development, and advertising. For example, it can analyse a large amount of patient information to develop a treatment plan tailored to the patient’s needs. It can even recommend the best financial investments according to your or your client’s goals.

What is the Role of Generative AI in Business Analysis?

Generative AI has recently been aiding the business analysis field through:

1. Predictive Analytics

By analysing vast amounts of data, AI can generate more complex and accurate predictive models that provide deeper insights and anticipate trends.

Let’s say a retail chain wants to optimise its inventory levels and avoid overstocking or stockouts. To achieve this, AI will take in historical sales data, weather patterns, economic indicators, and social media trends.

Next, it will identify correlations within the data, build predictive models that can forecast future demand, and simulate scenarios to assess potential impact on sales. Based on the forecasts and analyses, trained BAs like you can optimise inventory levels, reduce waste, and improve customer satisfaction.

2. Customer Sentiment Analysis

During customer sentiment analysis, you can evaluate and interpret your customers’ opinions, emotions, and attitudes based on their spoken or written feedback. This allows BAs or future BAs like you to transform customer sentiment into actionable insights that businesses can understand and respond to.

Generative AI models can help you process and analyse unstructured data like social media posts, reviews, and customer feedback. Ultimately, this allows your organisation to understand customer sentiment and preferences.

For instance, if your business wants to address customer concerns in one of its products, you can use AI to analyse social media buzz and customer reviews. As a trained BA, you can interpret the findings generated by the AI tool in a manner that stakeholders can easily understand. Additionally, you'll have the skills and knowledge to ensure that these align with your company’s objectives and needs.

3. Process Automation

Businesses are increasingly using AI to automate repetitive tasks. For example, it can be used to speed up the production of automotives and reduce the risk of human error. Apart from these, the technology helps you streamlines and automates repetitive business analysis tasks.

Consider a company dealing with a large volume of critical documents. AI can automatically extract important information from these files (e.g., dates, contract terms, and names), classify them based on content, and store them properly. This reduces the need for admin work like manual document management, allowing BAs to focus on more important tasks, such as analysing the insights within these documents.

What are the Challenges and Considerations of AI-driven Business Analysis?

Despite the many benefits that AI can bring to the business analysis industry, there are still some things that current and future BAs need to consider, such as:

1. Data Privacy and Security

As Australia experiences more cyber attacks every year, it’s essential for businesses to protect their IT systems. In fact, cyber criminals can target AI systems to steal or manipulate sensitive data. They can also disrupt business operations, resulting in significant downtime and financial loss.

Maintaining the integrity and accuracy of data is also vital to ensure that you can perform your duties as a BA effectively. If data is tampered with or corrupted, business analysts can develop incorrect insights and recommend wrong business decisions.

And by prioritising data privacy and security, businesses are more likely to gain the trust of customers, stakeholders, and partners. This strong reputation for safeguarding data can be a significant differentiator with the competition.

2. Ethical Considerations

AI systems can unintentionally reinforce biases in the training data. For example, a company using AI to target certain segments for its marketing campaigns might prioritise younger, urban customers if their training data primarily consists of this demographic.

As a result, this can result in overlooking the needs of other customer segments, biased algorithms, and lower conversion rates. To avoid this, organisations must ensure their AI models are trained on diverse data sets.

Additionally, businesses - and the BAs within them - need to ensure that AI-driven decisions are transparent and there is accountability for any errors or unintended consequences. A lack of these can lead to mistrust and scepticism within the company.

3. Skills Development

As AI technology constantly evolves, so must the knowledge and skills of business analysts. This is why current and aspiring business analysts must invest in continuous learning and development. They can do these by:

• Enrolling in a course: You can take online courses that that enhance your business analysis skills. So, you can be sure to gain the relevant knowledge to excel in the field.

• Developing Strong Communication Skills: BAs must know how to convey complex ideas to both technical and non-technical audience, so they must invest in improving their ability to clearly articulate and present information.

• Join Business Analysis Events: Participating in these events gives you the opportunity to connect with and learn from other professionals in the field. Joining BA events help you stay updated with the latest trends and technologies, too.

Start Your BA Journey with Lumify Learn as a Certified Professional

Now that you understand the benefits and challenges of generative AI in business analysis, how do you take the first step into the field? Enrol in Lumify Learn’s Business Analysis Certified Professional course!

In this program, you will gain fundamental skills like requirement gathering, process modelling, and stakeholder and contact management. You’ll even get hands-on business analysis experience through a project that mimics real-world business problems.

The best part? Two certifications await you by the end of the course:

• BCS Business Analysis Foundation: This micro-credential in business analysis principles and practices helps you develop a deep understanding of the field.

• BCS Requirement Engineering Practitioner: Learn to gather, document, and manage project requirements effectively.

Aside from an understanding of AI and machine learning, this online boot camp has no specific prerequisites and can be taken by anyone. Once you complete the course, you can join our exclusive career support initiative, Lumify Edge. Through this service, we will connect you with employers looking to hire business analysis professionals. You’ll also get to stand out from the crowd through our professional resume and LinkedIn profile update program.

Ready to get started? Enquire with us on a course today.