Re-Imagining the BA Role. Now that we have Generative AI.

Gabriel Botsie
Mar 8, 2024
4 min read

The Business Analyst origin story started in the 1940’s.

The position was created from the existing System Analyst role, after the realisation that aside from technical and domain skills, an understanding of the business and business actors was also required.

Initially the focus for Business Analysts (BA) was software engineering, later expanding to include all business model operations.

Nowadays, BA’s can be found in multiple industries. Their titles may vary e.g. — Business Intelligence Analyst, Product Owner — however, the emphasis on business value persists.

The Modern BA

The BA role is often depicted as a Venn diagram of overlapping technical, domain and soft skills. Soft skills such as Communication, Persuasion, Active Listening are essential for effective stakeholder management.

The Business Analyst — Image by the Author

The Venn circles are normally represented symmetrically, assuming all 3 skill areas are the same level i.e. good across domain, technical and soft skills.

The reality is asymmetrical.

BA’s have varying experiences i.e. candidates could have:

High Domain — Medium Soft — Low Technical skills,
Medium Domain — Medium Soft Skills — High Technical skills

Or any other combination.

Business Analyst Skill Representations — Images by the Author

Impact of Generative AI

The power of Generative AI is in it’s natural language processing.

Using natural language, it’s capable of multiple outputs — text, image, video, code, audio all via prompt engineering. No pre-requisite qualifications, expensive courses, books. Immediate results with everyday language.

This benefits BA’s in task and artifact production:

User stories and diagrams, produced in seconds
Client / project documents uploaded for immediate summarisation

What this means for domain and technical skills

Examples of common domain and technical BA struggles, include:

Low programming skills e.g. Python
SQL Knowledge — when should an Outer Join be used?
Production of accurate and consistent documentation

The appropriate Generative model alleviates these struggles.

Low programming skills?

Work with Codex
Input natural language
Codex provides the code
Learn from the experience.

Need accurate and consistent documentation?

Work with Claude to produce user stories
Tell Claude you want consistent formatting
Review the outputs
Work with Claude to improve accuracy.

In these two examples, Generative AI has augmented the BA’s skills, upping their domain and technical skills to match the use case.

Technology Adoption

New technologies change industries, we’ve seen this across all industries with Cloud and Big Data. Below are specific examples of technology change in the BA domain:

Before Jira — Agile projects were managed and maintained with paper task cards on wall mounted swim lanes
Before Zoom and Miro — client collaboration meant in person meetings.

To this end, an additional circle should be added to the BA Venn diagram — “Technology Adoption”.

Re-Imagining the Business Analyst —Technology Adoption, Image by the Author

Technology Adoption is different to technical skills as it relates to the willingness to adopt and adapt, as opposed to learning Python, SQL. Whilst Generative AI has stolen the media limelight, there are other equally transformational technologies, some of which are added as reference in the Venn diagram.

Re-Imagining the BA Role

A subjective take on the BA role taking into account the impact of Generative AI and the wider adoption of new technologies.

Project Role

a. Reduction in time for project processes

Generative AI excels at tasks, this will lead to decreased time for project processes and eventually project plans.

To illustrate, project discovery, normally a 2–3 week activity to allow for documentation, could be reduced to a week .

Why would the client pay for an additional 1–2 weeks for documentation when Generative AI can output in hours as opposed to days?

b. Improved quality and speed

Wireframes & prototypes are normally required on digital projects.

With text to image as well as text to video capabilities, a well crafted prompt can produce near instant results. This supports greater collaboration and experimentation between design, product teams and the client on initial solutions.

c. Value Creation

Allowing Generative AI to focus on tasks such as producing user stories, saves BA time. Time which can be repurposed to addressing project and stakeholder goals.

The call to action — use prompt templates for reusable, consistent outputs on projects.

Organisational Value

The BA is a versatile and popular role found in many leading organisations.

I anticipate that the role with its varying titles, will get more popular as organisations look to implement technologies such as Generative AI for competitive advantage

With technical, domain, soft skills, plus the capacity to adopt new technologies the BA is perfectly equipped to provide more organisational value.

Career Prospects

There’s a well trodden path for BA’s going into project, program and product management roles.

Augmented with Generative AI with the soft skills to persuade and influence, other non traditional paths to CEO, CTO or CIO could also be in reach.

Not forgetting BA’s who freelance, quicker production of documentation, augmented analysis using Generative AI will help drive your business.

Summary

The post started with the origin of the BA role, before advocating for a new Venn circle — “Technology Adoption” — along with domain, technical and soft skills.

It also provided subjective thoughts on changes to the BA role as a result of Generative AI. There’s a strong call to action to embrace new technologies for the improvements they bring to the role and ultimately greater value creation for stakeholders.

The post hasn’t commented on:

Technology Adoption risks
Interaction with stakeholders using Generative AI

The technology risks are considerable. With Generative AI, data privacy, security and how to manage model hallucinations are legitimate concerns.

Overall, as a subjective opinion, the benefits — increased productivity, time savings — can be balanced with appropriate mitigation such as blocking Generative models from training on private organisation data.

Interaction with other users using Generative AI is another interesting area in itself. It’s not just BA’s using Generative AI, developers, product managers and UX designers have their own use cases.

Clients will be using Generative AI to produce documentation for the project team.

New processes / workflows are needed to ensure stakeholder inputs and outputs are streamlined to ensure project success.

Overall, I’m optimistic about the impact of new technologies on the BA and how the role can continue to provide stakeholder value.

This post was originally published on Medium.