A brief on AI #
Almost all the industries and job roles are influenced or being influenced by Artificial Intelligence (AI). Everyone wants to take advantage of AI to excel in their respective fields and business analysis is no exception.
It all started from 2022 when Open AI released ChatGPT (Generative AI technology) for the general public and it was a massive hit. ChatGPT has become the household name. Isn’t it? It triggered a storm of innovations in the AI space and it’s rising continuously in different domains. More and more players are investing and innovating in AI.
As of now, the AI that exists today is called ANI (Artificial Narrow Intelligence) also known as Weak AI and it’s marching towards AGI (Artificial General Intelligence) also referred to as Strong AI.
ANI (Weak AI) is designed to perform a single or narrow set of tasks. It cannot perform tasks beyond its defined capabilities. E.g. Siri, Alexa, ChatGPT.
AGI (Strong AI) is currently a theoretical concept. It would be capable of performing any intellectual task tha a human can, using its learnings and skills to accomplish new tasks in different contexts without needing further human intervention.
In 2023, the businesses started leveraging AI into their operations and realizing the benefits.
Now, 2024 is a crucial year for AI where the researchers and big enterprises are working towards integrating AI more practically into businesses and our daily lives. Let’s see how it unfolds.
Latest Innovations in AI space as of 2024 #
Here are a few latest innovations in AI space across various domains as of 2024:
-
AI in Creativity and Content Generation (GenAI)
- AI driven text based content generation and validation tools such as ChatGPT, Grammerly.
- AI driven design tools that generates realistic images and videos such as Midjourney, DALLE
- Generative Art Platforms such as Adobe Firefly
- Voice Assistants like Siri, Alexa
- Automated Text to Speech and Speech to Text
- Conversational Bots for Search and Market Research (ChatGPT, MS Copilot)
- Software Development - Code Generation & Auto Completion (Github Copilot), Auto Code Review, Test Automation, Code Translation, Code to Documentation (such as API docs), Code Refactoring, Detecting security vulnerabilities and Compliance checks
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AI in Banking and Finance:
- Automation of manual processes such as data analytics, forecasting, risk assessment and fraud detection.
- Algorithmic Trading
- Risk Management & Compliance
- Credit Scoring
- Customer Support and Engagement through Chat bots and Virtual Assistants
- Centralized Operating Models
-
AI in Health Care
- Discovering and developing new medicines using GenAI
- Personalizing treatment plans
- Identifying types of strokes
- Monitoring brain health in real time
In near future, we are going to experience more advancements in AI such as Customized Chatbots, Multimodal AI, Edge AI etc.
Business Analysts and AI #
The reason why I mentioned the current AI capabilities is because it’s very important for a business analyst to be on top of AI advancements happening in the respective business domain.
Whenever any new technology is introduced and its started disrupting the market such as Cloud, Blockchain, AI etc, it’s the Business analyst’s responsibility to understand and leverage that technology for the benefits of the business when an opportunity arises.
A business analyst generally works at one or more of the following levels within an organization.
- Operational - Requirement analysis and execution. Works with Software development teams.
- Tactical - Elicitation and Prioritization of business requirements. Works with Business stakeholders.
- Strategic - Define business strategy aligned with vision and mission of organization. Works with C level executives.
Now, there is an influence of AI at all 3 levels and a business analyst should take it into consideration in order to deliver value to the business.
Strategic Level Business Analysis and AI #
At the Strategic level, a business analyst can contribute towards defining the strategy to infuse AI into the systems (internal or customer facing). To be able to do this effectively, a business analyst should be aware of the capabilities and maturities of AI based tools, technologies, cost effectiveness, pros and cons.
A business analyst can propose strategic solutions that may utilize ready made AI models/tools or need to develop and train custom AI models based on the available data.
Currently, the widespread use of AI (ANI) is to develop Chat Bots within an organization for various purposes such as internal knowledge assistance, customer support and customer engagement.
Tactical Level Business Analysis and AI #
At the Tactical level, a business analyst should find an opportunity to automate/improve business processes using data driven insights and AI while eliciting and prioritizing the requirements. To be able to do this effectively, a business analyst should be able to gather various data and draw out useful insights using business analytics.
Another use case would be to identify the features and functions of the app that can be powered by AI and suggest that to the stakeholders. For example, If you are working on an Email Marketing software (SaaS app), AI can be used to predict best times to send promotional/marketing emails that would improve the email open rate.
Operational Level Business Analysis and AI #
At the Operational level, a business analyst should find an opportunity to appropriately integrate the software’s usage data with the data analytics or business analytics platforms and the outcome of that analytics can be used later on to develop AI powered features into the system or to improve a business process. To be able to do this effectively, a business analyst should be able to identify the set of data, it’s reporting structure and work with developers and data analysts to build data analytics over that data.
Conclusion #
In nutshell, a business analyst should be adapted to the AI world, remain up to date with the AI advancements and find an opportunity to make use of AI into the solutions to address business goals or problems.
A point worth considering is that, since the usage of AI is in it’s early stages, there are potential risks, dangers and challenges involved while using AI such as Deepfake, Copyright issues and misinformation so a business analyst should be careful in using AI based tools and proposing AI based solutions. It’s always required to critically think about the usage of AI. More and more countries and governments are trying to regulate AI to handle these problems and we’ll witness those regulations in coming years for sure.
Lastly, a business analyst’s role would become more crucial and interesting with the rise of AI.
