How does the Artificial Intelligence revolution impact IT Business Analysts?
Artificial Intelligence development comes to the stage where non-technical people can use it in their everyday and professional life. There are numerous blog posts about prompt generation, image generation, and more clickbait about how people lose their job.
In this article, I would like to be on the professional side, so we do not talk about self-destructive machines and other fiction, but after you read it, you can prepare for the real future to increase your career.
If you are a professional, you are always preparing for the next big thing in tech. So these days, you probably want to know how Artificial Intelligence (AI) can affect the work of an IT Business Analyst.
What is AI?
According to Wikipedia,
Artificial intelligence (AI) is intelligence — perceiving, synthesizing, and inferring information — demonstrated by computers, as opposed to intelligence displayed by humans or by other animals. “Intelligence” encompasses the ability to learn and to reason, to generalize, and to infer meaning.
It seems science fiction, but the reality is, AI is a bunch of algorithms. We call simple chatbots, facial recognition systems, image generators, and machine learning algorithms as AI.
There is nothing new under the sun.
There were AI in the past decades, but we called them “management expert information systems”. They collected tons of data and based on the calculations, provided us with valuable insights and reports.
They were designed to help non-IT people get expert insights based on complex decision-making algorithms. The issue with these systems is that non-IT users need IT experts to ask proper questions and tell them how to understand the answers. (Did you hear about prompt engineering this year? Sounds familiar, right?)
A.I. is a broad field, it has a ton of subtopics, but generally, you can divide it into two main categories. Weak A.I. covers a lot of applications that focus on solving a single problem, like customer support chatbot, facial recognition, or generating funny pictures. Strong A.I. or called AGI is artificial general intelligence. AGI’s capability is equal to human intelligence. AGI hasn’t been achieved yet.
Currently, AI is really about developing systems that mimic human intelligence. Nothing more in 2023. Look at those diagrams on the picture.
AI can help to make better decisions, but it is not as simple as people think. That is the point where we have to talk about IT business analysis.
IT business analysis in the age of artificial intelligence
What does a Business Analyst do?
Gathering requirements, understanding processes, proposing solutions, tracking the requirement implementation…
Let’s see the official description.
Business analysis is the practice of enabling change in an organizational context by assessing an organization’s structure, procedures, technology and capabilities to identify and define solutions to roadblocks that impede the achievement of organizational goals. Organizations like humans evolve to survive in the environment in which they exist. And evolution is constant change and a constant changing needs. We analyze situations, we weigh the pros and cons of various potential solutions, and we define the requirements for optimizing the outcome of change. — https://www.iiba.org/professional-development/career-centre/what-is-business-analysis/
What does an IT Business Analyst do?
IT Business Analyst specialized in the technology part from the above description. It means a professional who has broad insight and knowledge in the field of technology and has analytical and critical thinking skills to identify and define solutions to achieve organizational goals.
I know a lot of IT business analysts, who started their careers as IT professionals and also know many good professionals, who worked as a process engineer or in any non-IT department.
The power of an IT business analyst is the deep understanding of how information technology works on different levels AND the capability to ask simple questions to provoke valuable answers.
There is an increasing need for IT experts who can communicate with
non-IT professionals, IT professionals, and machines/systems as well.
Why? Because you can not talk with AI the same way as humans. They can understand your keywords. Some of them can understand the context. But they can not understand the purpose of your question. The “real question behind the question”. That is why you get general and superficial responses most of the time, which could be risky in a business situation and could mislead decision-makers.
As an IT Business Analyst, part of your skillset is to understand the root cause, the purpose, the demand, and the required value behind the business need and all the answers you get in an interview, then use targeted questions to steer the conversation in the right direction.
You have to do the same when you or your business manager need information from AI.
So we talked about IT business analysis in general, now, let's see some real-world examples, of how you can prepare for the rise of artificial intelligence and related technologies, such as data science and machine learning.
How to implement AI-based business solutions as an IT Business Analyst?
Generally, a Business Analyst could work under three hats in an organization. Based on the level of work, the daily tasks can be different, but even if you are working with the top managers as a business analyst, the evolving and changing technology will inevitably have an impact on your work.
Let me tell you that these hats are interoperable. Maybe, you are working at all levels, maybe not.
IT business analyst as part of the data science team
If you are working in this hat, you were (or you will soon) be taking advantage of data analytics in your day job.
You are familiar with the following keywords:
SQL queries, spreadsheet “magic”, data lake, process mining, Tableau, Power BI, or any other business intelligence system.
Companies also call it an IT data analyst or Business Intelligence analyst.
You are using the right tools to interpret data models and data correctly to extract business intelligence. You do descriptive, diagnostic, and predictive analysis.
With evolving machine learning algorithms, predictive analytics will be more precise. AI can help business decision-makers to support them with more precise data or it can automatically decide based on algorithms.
So you as an IT data analyst will be equipped with better, deeper insights and can forecast behaviors, trends, and outcomes. If you are involved in a machine learning initiative, you have to decide what data should be the output for the ML application to learn the right things.
To choose, implement and refine these algorithms, a good data analyst professional with AI knowledge in the team is crucial.
IT business analyst as part of the software development team
As part of a software implementation team, your daily job is varied from creating features, and user stories, refining the requirements, ensuring that the client gets the value they are looking for, and writing functional and non-functional documentation. You are working closely with product owners, software architects, and developers as well.
(Just for the note: Some company needs an IT business analyst and software architect hybrid role, which is called IT System Analyst.)
Your job still remains the same, but you have to understand reinforced learning, deep learning, machine learning, and data science. You have to be familiar with the capabilities and use cases of artificial intelligence to propose valuable solutions to the business and translate them into technical language for the implementation team.
Today, the most widespread use of these technologies is chatbot development, so it is an advantage if you understand how a chatbot works and what are the capabilities and limitations of an AI tool.
But to mention another example, you can be part of implementing a Natural Language Processing solution for a market research company to get faster results from market research by telephone. NLP could help collect data by analyzing not just the meaning of the sentences given in response, but also the tone and emotions.
Of course, there are more use cases for AI, such as facial recognition, text recognition, robotics, automated decision-making systems, speech recognition, self-driven cars, and so on.
IT business analyst on enterprise or strategic level
This position is rare but respectable. Most of the time your job is to analyze bottlenecks in the organization structure and support the organizational change process from a technological viewpoint. Working closely with IT department managers, IT security professionals, and enterprise architects to identify the opportunities and risks of new technologies and how they impact the company's future technology stack. You are also involved in the company’s IT strategy development.
At this level, you need to constantly monitor technological developments, have a high-level understanding of the opportunities and threats of AI, and assess them from a business perspective to propose valuable suggestions to the company leaders.
Let me use the previous example. As an enterprise business analyst working for a marketing research company, you can propose a solution for implementing an NLP-based phone questionnaire analyzer tool. You can assess the need, identify the changes needed for proper implementation, also assess the result of the successful/unsuccessful/partially successful implementation for the organizational structure and business continuity.
Summary
As an IT Business Analyst and IT consultant, I recommend you stay updated with the latest developments in AI and related technologies.
Invest time in understanding AI concepts, such as predictive analytics and chatbot development, to effectively contribute to projects and communicate with both technical and non-technical stakeholders. Additionally, explore opportunities to work with data science teams and software development teams to gain hands-on experience and expand your skill set.
Continuously develop your analytical and critical thinking skills to extract valuable insights from AI systems and drive effective decision-making within your organization.
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