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Embracing AI in Business Analysis: A Guide for BAs

Artificial Intelligence in business analysis is fast becoming the next big evolution of the BA practice. It acts as a superpower to enhance decision-making, automate repetitive tasks, free up time for strategic work.

BAs add value to organizations that AI cannot replace, like problem-solving, critical thinking, communication, and collaboration. But with increasing competition in companies, BAs can use an assistant like artificial intelligence to do more with less. This article covers the growing influence of AI in business analysis and how you can thrive as a business analyst in the age of generative AI.


AI in Business Analysis: A Growing Field

Business analytics powered by AI can detect patterns, anomalies, and deviations and raises them for review by business analysts.

Business analysts are embracing AI/ML tools to make more informed decisions and improve their competitive advantage. Tools like Tableau, Power BI, and others increasingly have a significant AI component

BA coaches have also begun thinking and producing content on how to use AI tools like ChatGPT for business analysis.

The growth of AI tools has also led to an increasing push for human oversight over AI. For instance, the European Commission has proposed a regulation the stipulates how high-risk AI systems like facial recognition algorithms should be created with human oversight in the loop.

Developing regulations like these will affect downstream industries like business analysis in due time.


AI-enhanced Business Analysts

The most beneficial way to deal with the rise of AI is to enhance your existing skill set using it. Generative AI tools can also lead to happier and more productive workers.


Here are some ways you can adapt to the changing reality:

Know your Core BA Skills

As recently as May 2023, Forbes recognized six core business analysis skills:

  • Analysis: Parsing large amounts of complex data and recommending solutions.
  • Communication: Active listening and clear delivery of data in verbal and written form.
  • Interpersonal: Working effectively with stakeholders and teams within client organizations.
  • Problem-solving: Creative solving of unique client issues.
  • Time Management: Prioritizing tasks and getting the job done quickly.

AI can do parts of these tasks for you, but none fully. For instance, an AI-based requirements management tool can help you analyze and write requirements based on raw data, but only with your approval.  But it fails at active listening, stakeholder engagement, or creative problem solving.

Without human oversight, AI can be ineffective or even counterproductive. Business analysts can excel through expert management of AI tools and ensure that AIs output aligns with the goals of the organization.

Another core skill that AIs cannot compete is an up-to-date understanding of the industry. BAs with domain knowledge can spot problems and suggest fixes before a project reaches the development team. They have the knowledge and connections to understand market conditions and protocols beyond what is available on AI databases.

Strategies for developing industry domain expertise include:

  • Researching the history, current situation, and prospects of the industry.
  • Learning market-specific protocols. For example, ASPICE is a key automotive regulation.
  • Competitive analysis.
  • Asking questions to other domain experts.

Enhance Your Data Management and Analysis Skills

According to Peter Sondergaard, the SVP and Global Head of Research at Gartner, “Information is the oil of the 21st century, and analytics is the combustion engine.” Analytical skills help BAs generate high quality outcomes that meet business needs.

In practical terms, you need to have a combination of the following data analytics skills to position you as a high-value and competitive BA candidate:

  • Data Literacy: Familiarity with data language, types, sources, and analytical tools.
  • Data Collection: Knowing how to collect unbiased and reliable data through various methods.
  • Statistical Analysis: Knowing statistical terms and techniques like hypothesis testing, linear regression, and p-values to extract insights.
  • Data Visualization: Presenting data honestly to communicate insights.

Learn to Work with AI Tools

A recent survey by Gartner showed that 70 percent of U.S. workers want to use AI to reduce some common tiresome and repetitive tasks.


The top task that workers hoped AI would automate is data processing. The demands of a business analyst already include many of these tasks and will do so in the future. Here’s how BAs can leverage AI tools for data processing:

  • Integration: Building “master lists” of data, like merging lists while retaining their integrity.
  • Classification: collecting, extracting, and structuring data from documents, photos, audio, video, and other media.
  • Cataloging: Organizing, cleaning, and retrieving data. SQL is already a key skill for data retrieval and OpenRefine helps with basic data cleaning.
  • Quality: Reducing errors, contradictions, or low quality in databases or requirements authoring.
  • Security: Keeping data safe from bad actors.
  • Compliance: Adhering to relevant industry-based or national compliance standards. E.g. ASPICE for automotive.

BAs should also learn how to interact with AI tools. Some tools have button-based interfaces, but others like ChatGPT use prompts. Engineering prompts will itself become a skill not dissimilar to making SQL queries. The right query may be the difference between an important insight and a dead end.

This collaborative approach to AI in business analysis will help increase the efficiency and effectiveness of the entire organization. The MIT Sloan Management Review and Boston Consulting Group’s global executive survey found that companies combining AI and human abilities are best positioned to succeed.

These days, many tools help boost the productivity of BAs. Some staples like Tableau and Power BI have into their legacy offerings. Others have leveraged the to analyze, write, rewrite, and suggest requirements.




Adapt to Changing Roles and Responsibilities

Beyond working with AI tools, BAs will have to adapt and expand their skill sets to market realities. BAs can stay on top of things by:

  • Keeping up with cutting-edge technologies like blockchain, digital trust, and artificial intelligence.
  • Asking better questions about business needs, technology needs, and stakeholder satisfaction.
  • Considering hybrid roles that combine BA skills with related fields like statistics, data analysis, project management, and UX.
  • Enhancing soft skills. BAs who communication, critical thinking, negotiation, and collaboration skills can adapt and thrive in any environment.


The Future of Business Analysis is Bright

The fundamental role of the business analyst will be no less relevant in the near future. Somebody has to perform crucial tasks like business processes evaluation, problem identification, and more. Embracing the paradigm of new AI tools will only increase the productivity of BAs. Combined with their core BA toolkit, domain expertise, fluency in data management, and soft skills, business analysts can thrive and drive the success of their companies in the 2020s and beyond.


Source: AI in Employee Engagement: 7 Applications to Try Yourself | Zavvy [AS1] [AS1] [AS2]


Information Science, Knowledge Management and the Business Analyst

In today’s fast changing world, information, and technology are changing the way organizations and nations operate. The quality of information available to an organization, its ease of use and systems of dissemination can make the difference between organizations that thrive and those that get left behind in the archives of history. To understand this better, let’s look at the science of information.

Information science is the discipline that deals with managing information, from creation to final archiving or destruction. It is concerned with the generation of data, the associated technologies, and the transformation of data into information and knowledge. What is information? Let’s begin by defining data.



Data can be described as independent entities, , numbers, letters etc. that on their own do not convey any useful meaning. Consider the following data set:  ‘A’, ‘John’, ‘boy’ ‘good’ ‘is’ ‘1’, ‘class’ ‘and’ ‘in’  ‘number’ ‘his’ . Each entity on its own does not really convey any useful meaning. However, when this data is put through a transformation process, with a pattern or structure, it conveys a meaning ‘John is a good boy and number 1 in his class – these entities which has been structured or patterned becomes information within the system.



Information can therefore be described as data with a meaningful pattern to the system receiving it, such that it can change the state of the system. In other words when information is received by an individual, an organization or a system, it must be meaningful to that system: they have been transformed by this information. In some cases, the information received enables them to take an action or make a decision. This change in state might be from a current (as-is) state to a future (to-be) state, or just a change in position from point a to b, or from a less informed state to a more informed state.



Knowledge: When information has been fully understood, digested, and internalized by a system such that the system can reproduce it in various forms and disseminate it easily to others, it has become knowledge to that system. For example, an employee may build up their knowledge of a domain through multiple channels: training, conferences, water cooler conversations etc.  and become an expert with a full understanding of the subject area. They can simplify it into various forms and train others: the information they have absorbed has become their knowledge.

This relationship between data, information and knowledge can be represented as shown below in a knowledge circle.



The importance of knowledge to an organization can never be overemphasized. Organizations can thrive or fail depending on the quality of knowledge that exists within them. Knowledge in organizations exists in two forms: explicit and tacit knowledge.

Explicit knowledge is the knowledge that exists in the public domain of an organization. It is in their culture, in their SharePoint systems, books, journals… It is documented and widely available to all.

Tacit knowledge is the knowledge that exists within individuals and SMEs, it is unwritten, can be heuristic, is veritable and often lost when such individuals are no longer with the organization.

Seeing the value of knowledge to the continued existence of organizations, how can businesses best elicit the knowledge within their domain? How can they ensure the quality of their information, and extract valuable tacit knowledge from SMEs? Answers to these questions lies in the domain of business analysis.




Business Analysts

Business Analysts are change agents who often sit between the business and technology arms of an organization. They help the communication between the business and technology, ensuring data from both sides is translated into meaningful information which both parties understand, ultimately causing a change in the state of the organization. Business Analysts help organizations move forward from a current state to a future state.

Business Analysts by nature of their training can elicit tacit knowledge from SMEs, document the knowledge and ensure organizations do not increase their technical debt when valuable employees leave. They are also well placed to investigate and scrutinize the volume of information accessible to an organization by verifying and validating it with SMEs before such information is used in business decisions, thus improving the quality of an organization’s information and knowledge.


Some of the Business Analysts’ skills include the following:



Concluding Remarks

The knowledge circle will continue to be at the heart of an organization’s growth. Organizations which harness their knowledge correctly will continue to outperform their counterparts, and Business Analysts who understand their role in this circle will continue to be great assets and instrumental to the success of their organizations.


Ode to a Picture

Practically everyone has heard the expression “a picture paints a thousand words”.  In the world of art, a picture can be used to express ideas and evoke emotions, or it can also simply be used to capture on canvas something or someone significant. In the professional world, carpenters and architects rely on drawings to build to precise specifications. In the business analysis world, the whole purpose of creating a picture, otherwise known as a diagram, is to clearly communicate information without using words.

There are many different types of diagrams at our disposal, and I will attempt to name a few key ones here: entity, activity, data flow, sequence, use case, flowchart, system context, workflow, object, component, and UML.  However, the focus here is on what you want to convey to your audience through a diagram and the benefits of doing so, rather than how or which diagram you should use to do so. The point is to emphasize the benefits in the use of diagramming in many situations to communicate meaningful information and transform your business analysis efforts!


What a Diagram Can do for You

Diagrams can tell a story from numerous perspectives. For example, they can be used to confirm our understanding of processes, or to define system interfaces. They can illustrate system and network connectivity. They can help to explain complex processes. Diagrams can depict workflow, business processes and system interactions. They can help to define in scope and out of scope features.  They can also help establish or confirm understanding between the business analyst and a stakeholder in a way that verbal or written words sometimes cannot.

Diagrams can help confirm requirements by illustrating what needs to happen in a system or workflow. They can also be used to model database structures and to depict data flow. Diagrams can cut across confusing jargon or long-winded verbal or written explanations and get right to the point in the simplest of terms. When you consider all of the benefits, the power of a diagram is undeniable!


Diagrams are Blueprints to the Past, Present and Future

Diagrams can be used as blueprints for past, current or future conditions. For instance, diagrams from the past can help explain why outdated processes or procedures might have come into existence. How many times have you come across the question “why do we do this”? The typical answer of “because we’ve always done it this way” never solves the problem.

If only you could time travel back in time to document a process using a diagram so that in the current day you or anyone else could easily answer any questions about the “why’s” of a process or procedure. Prevent this lapse of information for future questions and diagram your process!


Take Time to be in the Present

Although your stakeholders (and you) might be very familiar with the tasks and workflow used with a given process, it is still beneficial to take the time to depict current “as-is” diagrams.   These diagrams are helpful to illustrate current interactions between actors and systems as well as point out manual tasks that might be targets for process or system improvements. Current state/as-is diagrams can also serve as a valuable documentation tool. New employees and auditors alike tend to appreciate the information conveyed in a diagram.

Additionally, going through the process of building out diagrams for current business systems and stakeholder processes can help demonstrate the need for better written procedures. Current state diagrams can also help point to key performance indicators when changes are proposed. For instance, when comparing the proposed future state to the current state, time-consuming manual tasks will hopefully be earmarked for potential elimination. Having these diagrams at your fingertips can make these improvement opportunities stand out, which will make the task of quantifying the time saved or cost savings (or whatever differences) that much easier to document.




Illuminate the Future

Future state or “to-be” diagrams can help to illuminate the roadmap for upcoming changes, whether that might be a business process, a system component, or a new business system altogether. For instance, they can help define system changes and plan improvements to technical interfaces, thereby avoiding future outages. They can help to confirm our understanding of impending changes to processes and to thereby plan accordingly. They can also help identify the business processes that may become obsolete. Future state diagrams can also help the organization stay focused on the planned and specified changes or help to inform decisions to adjust the plan if necessary.



As a business analyst, the diagram has to be one of the strongest tools in the arsenal of BA weapons. There are so many uses and applications where a diagram can transform work efforts. It doesn’t have to be fancy or complex. In fact, the simpler the better. The point is to use a diagram to convey the desired information in as clearly a manner as possible. The benefits of a diagram can be felt across all levels of the organization, communicating across different levels of knowledge and understanding. Diagrams can clarify information for stakeholders and business analysts alike.

They can validate or improve existing understanding and inform future changes. They can serve as documentation for auditors, and training tools for staff. Diagrams can highlight the need for improvements and underline performance improvement indicators.

The uses and benefits go on and on, so hopefully this will inspire you to take a little time in each of your project efforts to paint the picture that will prevail in communicating your message and save yourself a thousand words!

The Three Cs of Business Analysis

Recently I returned to work from an extended leave and was immediately thrown into the deep end of the pool with an assignment on the next phase of a major project. There was hardly time to get my bearings before needing to elicit requirements and write user stories, much less be able to understand how the product owners want the product to function. As a result of my rapid reintroduction to the project, I came to quickly appreciate the Three Cs of Business Analysis: Connection, Communication, and Collaboration.

1. Connection

Building connections is one of the most important things a business analyst can do. Forming relationships with stakeholders, development and QA teams, product owners, and many other individuals is vital to reaching a good output. I had the benefit of previously working with many of the same individuals, which made it much easier to jump back in quickly, as I already had those established relationships. However, for those individuals with whom I had never worked, the lack of time to build those connections has made it more challenging to understand their processes and how I can contribute to help them perform their jobs more effectively.


Obviously, the longer you are with a company, the more time you have had to establish and strengthen connections with those stakeholders around you. Even something as simple as a quick chat in the breakroom or reaching out with a simple question goes a long way in deepening those relationships, which makes life much easier when you need to work with those individuals on a project. Connections are resources of information, and the more resources you have, the easier it is to obtain information when you need it.


2. Communication

Whether you have good relationships or are just getting to know your stakeholders, establishing good communication practices is a top priority. Each stakeholder may prefer to receive communication via different methods, so understanding the best way to communicate questions or information with each individual is something that should be established early in your relationship. Some stakeholders prefer email, some do better with IM, others need direct communication via a meeting; and if you attempt to communicate with someone in a less-than-desirable method, there may be delays in obtaining the needed information. I have dealt with product owners who rarely respond to emails but will respond to an IM within an hour; I have also known other stakeholders who are the exact opposite.


In my case, since I had previously worked with many of those stakeholders, I already had a good idea of how best to collaborate. This made it much easier to quickly jump back in and get the answers I needed to my questions. For those individuals with whom I had never worked, we’re honestly still figuring it out. Obviously, whether you are co-located also makes a big difference in establishing relationships and best practices for how to communicate. Being able to walk to someone’s desk vs having to send a meeting invite does matter and can make it more challenging to get started.




3. Collaboration

The third C is what completes the circle…collaboration. We can build connections and learn how to communicate with those individuals, but it will all be for naught unless we collaborate. The Webster’s definition of collaboration is simple but explains exactly what we need to do: “To work jointly with others or together especially in an intellectual endeavor.” As business analysts, our job is to bring stakeholders and team members together, which means we must be the bridge that allows all interested parties to be part of the discussion. Now, what that looks like in reality can mean many different things depending on the scenario. It could look like:

  • A requirements elicitation session with stakeholders
  • Working with UX designers and product managers to understand how the design will allow the requirements to be met
  • Meeting with developers/testers to review stories and understand the level of effort
  • Reviewing the level of effort with product owners to determine priorities


Being part of the collaboration discussion with stakeholders on a project, as well as simply facilitating the discussion so various stakeholders can collaborate amongst themselves, are both tasks we perform as business analysts. If decisions are made in a silo without that collaboration, the result can be missed requirements, incorrect implementation, and dissatisfied clients. We must collaborate in order to understand the big picture and how requirements fit within the design and how the implementation functions, so we can ensure the client receives the intended outcome.


Forming connections, establishing good communication practices, and collaborating with all individuals involved in a project are three of the key pieces to building a successful product. They also make it much easier to float when you’re thrown into the deep end of the pool on an inflight project!

The Dilemma of Test Scripts

Mention software testing to 10 people in IT and you will get several different responses.

“That’s what QA is for.”

“Unit testing covers what we need.”

“What do we need to test for? The application works fine!”

“We’re Agile. We don’t need to test.”

“The client’s not banging down my door – so all is good.”

“No, we can’t release to UAT yet. I’m only halfway through writing the test scripts.”

“I don’t have time to test.”

“I don’t know how to test this. I’ll need some guidelines.”

“That’s not in the budget.”

If you work as a BA in an IT department, you have likely heard all of these retorts – sometimes even from those who should know better.


It is also a trigger that can lead down a deep rabbit hole of shortcuts and excuses, with the ultimate result being sloppy code, error-prone software, and possibly tons of rework post-release. Not only impacting you and your team, but also potentially leaving your company with very unhappy customers.

Software testing has several variations, all meant to ensure that the customer is happy in the end and that fewer issues, or bugs come back to haunt the product development team. Unit testing and smoke-testing are two of the most common types of testing. Unit testing is ordinarily done by the engineer as a part of coding and is meant to test the individual functions of the various components of the specific software. Smoke-testing is done after the release of the code into production. It serves as a means to make sure that nothing has been broken by the new code. Another critical form of testing is called regression testing, which focuses on how the new code works with the existing code. Regression testing requires additional planning and visibility of enhancements between releases.

At a bare minimum, unit testing and smoke-testing are essential. They are cheap and easy and require a minimal amount of effort.


The real testing, however, comes in the form of functional tests and acceptance tests. This is how you connect the code that is created by the engineers with the business needs of the customers and the real-life use of the application.

Functional tests validate that the newly designed process aligns with the requirements that were provided to the development team. Functional testing is best performed by either the business analyst or the QA analyst. A distinct benefit is gained here when functional tests are designed and completed by someone who is familiar with both the application and the enhancement requirements. Here is a tip: well written requirements and an experienced QA analyst are your best friend for stellar results!

Acceptance tests (also known as User Acceptance Testing or UAT) validate that the finished product aligns with the needs of the business user. This type of testing allows the end user to touch-and-feel the new process to make sure that it will correctly address the defined business need. An end user is also looking to make sure that the workflow is not made worse. At the end of the day, the user still has a job to do!




A well-designed set of test scripts is the most efficient way to track results, and to facilitate tracing the functionality back to the requirements. A plethora of applications exist that do this for you! Many of these applications can also run the test scripts in an automated fashion, which works great for regression testing. If I have access to an experienced QA analyst, I leave the decision up to that person. I simply provide rock-solid requirements and expectations and make myself available for questions.

That said, I am a big advocate of DIY.

If I am running functional tests myself, I create test scripts the old-fashioned way: Excel spreadsheets. The perception is that this takes too much time. Yes. It can be tedious. However, if you consider that good test scripts can also be used for system and user documentation – a bonus for start-ups – it is an essential task, regardless of the effort. They can be maintained and re-used.

Put your user hat on and give it a try!


Begin with a few basic columns:

Who is the user? What role is the user filling while performing this task?

What is being tested? Describe the function in simple terms.

What are the exact steps to get the desired result?

What is supposed to happen when the steps are completed?

What actually happened when the steps were completed? Ideally, you would want this to be the same as what was supposed to happen. Many times, it is not.

Did the test Pass or Fail?


Add more context for tracking and tracing back to the requirements, like test IDs for each test and date tracking to facilitate repeat testing.  Add a column for additional comments so that the person who is running through the tests can add additional observations about what was experienced during the test.



In short, product quality drives customer satisfaction. Complete and consistent testing and retesting is one of the best ways to drive customer satisfaction with new products and product enhancements. It’s well worth your time and effort.

Happy testing!