7 Ways AI Can Help Business Analysts

Generative AI can be a powerful tool for helping with your work as a Business Analyst, but you may be wondering how exactly, or you may know a few but don’t know that there are many other ways to leverage the power of generative AI.

Here are seven ways that you can use AI as a Business Analyst, with some examples to show you how to do it yourself.

1. Generate requirements

One of the core tasks of every Business Analysts is to elicit requirements. This typically involves using different elicitation methods such as focus group workshops, one-to-one interviews, observation, interface analysis, or document analysis to extract these requirements from your stakeholders.

This usually will take several rounds of back and forth, email threads and endless to get it right. However, with Generative AI, this process can be drastically sped up.

For instance, you’ve been given a task to collect requirements for a login process for a new mobile app that is been developed by your organisation.

You can pick an AI tool of your choice and ask it to generate requirements for a login process for a mobile app using the prompt below.

As a Business Analyst, Generate a list of requirements for the login process of a mobile app for a [organisation context]. Rank the requirements on a scale of 1-5 with 5 been the must have and 1 been a nice to have. Put in a table.

The AI will generate a list of requirements which you can use as a starting point for your discussions with your stakeholders and speed up the process of eliciting for requirements.

It is important to state that this doesn’t replace the need for stakeholder collaboration. Instead, it enhances and speeds up the conversation because there’s a baseline, and also the AI might have picked up areas that you or your stakeholders might have forgotten.

2. Write User stories

User stories are straightforward to write because it has a set structure –

As a [x]
I want [x]
So that [x]

However, some requirements can be tricky to break down into the exact user story to capture the requirement.

Moreover, some organisations still struggle with accurately documenting their requirements using a consistent user story structure. Not sure why 🤷

Generative AI can greatly assist IT Business Analysts in the process of creating user stories. By analyzing existing requirements and project documents, the AI can generate new user stories that accurately describe the needs of different stakeholders in a clear and concise way.

This not only streamlines the process but also minimizes the misinterpretation of user requirements. Below is a prompt you can use to create user stories today:

As an IT Business Analyst, create some user stories for [requirement]. Ensure they are well-defined and express the user’s needs and the expected value clearly

3. Write acceptance criteria

Generative AI can significantly aid IT Business Analysts in writing acceptance criteria for projects. Acceptance criteria specify the conditions under which a project will meet the business requirements and are an essential part of defining project scope.

Generative AI can significantly assist IT Business Analysts in writing acceptance criteria by streamlining the process and improving accuracy.

Take the user stories or requirements document and ask the AI to generate acceptance criteria or use a tool like PaceAI, enter your requirement ot user story and hit generate.

This enables analysts to quickly generate a draft of acceptance criteria, saving time and effort while ensuring consistency between the two documentation sets.

Define clear acceptance criteria for the [user story ] Include specific conditions or outcomes that must be met for the feature to be considered complete and satisfactory

4. Ideate/draft process maps

This is an exciting one as many IT Business Analysts struggle with different aspects of creating a process map.

AI has the potential to provide significant assistance to IT Business Analysts in the ideation and drafting of process maps.

AI-enabled tools can now quickly and efficiently generate preliminary process maps based on the input of user requirements, historical data, and industry best practices.

By parsing textual descriptions or guidelines provided by IT business analysts, generative AI can identify key components and relationships in a given process.

This information is then used to construct a visual representation of the process, taking into account the sequence of events and the primary actors involved.

The creation of draft process maps using generative AI can significantly reduce the time and effort required by IT business analysts, allowing them to focus their attention on refining and optimizing processes rather than starting from scratch.

Additionally, these AI-generated drafts can serve as a valuable starting point for discussions and collaboration among team members, as they provide a clear and concise representation of the process under consideration.

Create a detailed process map for [product/feature/process]. Identify key decision points, responsible stakeholders, inputs, outputs, and any decision logic involved in each step. Ensure the process map reflects current procedures and is clear and easy to understand for both technical and non-technical stakeholders. Additionally, highlight any potential bottlenecks or areas for improvement in the process

5. Analyse data

As Business Analysts, Data is important in making decisions concerning the product. However, not all Business Analysts are data savvy. But Generative AI has come to the rescue.

Business Analysts can now use Data AI tools to process and interpret vast amounts of data more efficiently and derive valuable insights that aid decision-making.

Through natural language processing, generative AI can help IT Business Analysts comprehend and analyze textual data from different sources, such as customer feedback, reports, and emails.

These AI systems can automatically identify patterns, trends, and anomalies in the data, enabling analysts to focus on drawing actionable insights.

[Upload data] Analyze the data related to customer support ticket resolution times over the past year to identify trends, patterns, and potential areas for improvement. Provide insights on factors influencing resolution times, such as ticket type, agent performance, and customer feedback. Additionally, suggest data-driven recommendations to optimize the support ticket handling process and enhance overall customer satisfaction

6. Draft requirement documents

Utilizing generative AI can significantly aid IT business analysts in drafting requirement documents.

The technology streamlines the initial stage of the documentation process by automatically generating draft content based on existing data sources and patterns.

This allows analysts to focus on refining and validating the requirements rather than spending time on tedious tasks.

Moreover, generative AI ensures that the format of the documents remains consistent throughout, making them more accessible for all stakeholders.

Develop a comprehensive Business Requirement Document (BRD) for [descibe system/project]. The BRD should include detailed information about the objectives, scope, and functional requirements of the CRM system, as well as any non-functional requirements such as performance, security, and scalability. Additionally, outline any integration needs with existing systems, user roles and permissions, reporting and analytics requirements, and a high-level project timeline. Ensure that the document is clear, concise, and structured for easy review and approval by stakeholders.

7. Communicating with stakeholders

Generative AI can greatly assist IT Business Analysts in communicating effectively with stakeholders. There are AI tools embedded in your email app or communication apps that help simplify complex processes and present information in a digestible manner.

Additionally, generative AI can transform raw data into concise summaries. By extracting relevant information, AI can create reports highlighting a project’s most important aspects.

This saves the analyst and the stakeholder time, allowing them to focus on critical issues and increasing overall efficiency.

Lastly, AI can facilitate discussions by identifying common ground between stakeholders with diverse perspectives.

By computing their input data and preferences, AI can pinpoint areas of agreement and disagreement, enabling IT Business Analysts to guide the conversation towards consensus and productive outcomes.

In summary

Let’s face it: AI is here to stay! You can either leverage the power of AI or get outshined by someone else using AI.

Generative AI is a valuable tool that can improve communication between IT Business Analysts and their stakeholders, ultimately leading to enhanced collaboration, informed decision-making, and project success..

Patrick G Avatar

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