Overview
The quick advancement of Artificial Intelligence (AI) has a big impact on the business analysis landscape. Business Analysts (BAs) play a crucial role in ensuring AI initiatives deliver meaningful business value for any software company. To stay relevant and lead in this transformation, BAs must re-align themselves with AI. BAs need to develop some very specific and quite unique AI skills—skills which are not only AI-driven but bear the potential of complementing their core competence in requirement management, stakeholder communication, and problem-solving. AI technologies can help business analysts uncover insights, automate processes, and make more informed decisions.
The aim of this paper is to introduce six indispensable AI skills that the business analyst should develop.
1. Prompt Engineering
As generative AI tools like ChatGPT, Gemini, and Copilot become integrated into day-to-day operations, Business Analysts are expected to know how to interact with them effectively. Prompt engineering is the skill of crafting clear, specific, and goal-oriented instructions to get accurate and valuable outputs from these AI systems & large language models.
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What to learn:
- Writing structured prompts like context + instruction
- Zero shot or Few shot prompting
- Iterative refinement (chaining prompts to get better responses)
Why it matters:
- Helps BAs in preparing for stakeholder meetings, generate user stories & acceptance criteria.
- Supports faster requirement analysis through summarization & faster creation of documents.
- Assists in drafting stakeholder communication, testing scenarios, and building training materials
Prompt engineering is less about coding and more about logic, clarity, and asking the right questions—skills that are already second nature to many BAs. It is an important addition to the AI skills of a business analyst.
2. Recognize Risks and Avoid Dangers
With great power comes great responsibility. AI introduces new risks, including hallucination and drift where output is either fabricated by the AI or simply inaccurate. Overdependence on automation & AI poses great risks in terms of inaccurate decision making. Unquestioned use of AI can result in a gradual decline of quality of output.
BAs are often the bridge between technical teams and business stakeholders—and are thus well-positioned to identify, flag, and help mitigate such risks early in the software development lifecycle. This is one of the key AI skills a business analyst must possess.
Key risk areas BAs should be aware of:
- Bias in AI models: Unequal treatment due to skewed training data
- Model working: Difficulty in understanding how decisions are made
- Data privacy: Improper handling of sensitive personal or customer data
- Regulatory non-compliance: Violating laws like GDPR
What to develop:
- A working knowledge of AI ethics and governance frameworks
- The ability to write unbiased & ethical requirements
- An understanding FATE i.e. of fairness, accountability, transparency and ethics principles
Risk recognition is a vital skill, an important addition to a business analyst’s AI skills, not only for responsible AI use but also for building stakeholder trust.
3. Build Domain Knowledge
No matter how advanced an AI system is, its effectiveness depends on how well it is aligned with real business problems. Domain knowledge is essential to helping a business navigate through advancements in generative AI. The analogy is that when an airplane experiences anything unusual, the autopilot is immediately turned off and pilots take control—at which point the pilots need to know what to do. Developing and maintaining these skills is essential, and a core component of the AI skills for business analysts.
Business Analysts serve as the contextual bridge—and domain knowledge is what empowers them to define meaningful requirements, ask the right questions, and prioritize the right features.
Why domain knowledge is crucial:
- Helps translate business problems into AI-ready requirements
- Prevents over-engineering solutions that may not deliver business value
- Enables faster validation of AI outputs and recommendations
How to build it:
- Study industry specific regulations, metrics, and use cases
- Analyse existing systems, reports, and workflows to identify gaps AI could fill
- Network with professionals, take relevant courses or certifications
Domain expertise turns BAs into strategic AI enablers who ensure that every initiative is grounded in real-world value. It is one of the most important AI skills for a business analyst.
Advance your business analyst career with our specialized AI certification course. Read our article on why mastering AI is important for business analysts.
4. Intellectual curiosity
AI is an evolving field. What works today might be outdated tomorrow. Business Analysts who exhibit intellectual curiosity stay ahead. They need to be agile and flexible in the face of the continuous progress in the field of AI.
This is less a real AI skill and more a mindset, but mastering and using new technology requires the openness to really want to use it. If you are reluctant to use artificial intelligence (and digital innovations in general), there is a risk of being left behind. It is a foundational trait for developing other AI skills.
Only with the necessary adaptability, a genuine willingness and curiosity to change and continuous development can keep pace with the dynamics of the working world.
Intellectually curious BAs:
- Ask “why” and “what if” questions about new processes or tools
- Dive into new AI use cases of your domain & outside of domain
- Experiment with AI tools to understand their possibilities and limitations
How to build it:
- Follow thought leaders in AI and business analysis on LinkedIn or other media
- Take AI-focused courses
- Participate in hackathons, meetups, or AI-focused BA communities
Intellectual curiosity enables BAs to learn new technologies like AI & apply them in innovative ways that create real business impact. It is a very important trait for developing AI skills. Be Open to Artificial Intelligence.
5. Effective interpersonal communication
AI may change tools and platforms, but the essence of a BA’s role—collaborating with humans—remains constant. Interpersonal skills such as the ability to communicate effectively, meaningfully engage with others, garner team cooperation, basic conflict resolution, skills of disconnecting from emotions, and practice mindfulness will always be performed by humans in any Human-AI collaboration. Strong interpersonal communication is one of the most important AI skills.
AI-specific communication responsibilities:
- Explaining what an AI tool or model does in business-friendly language
- Communicating uncertainty or confidence levels in AI predictions
- Translating stakeholder goals into feasible AI features
How to build it:
- Practice simplifying complex ideas without losing originality
- Use analogies and visual aids to explain AI concepts
- Develop empathy to understand stakeholder concerns
Strong interpersonal communication equips BAs to bridge the gap between AI capabilities and stakeholder expectations. It is this uniquely human skill that companies need, in addition to other AI skills.
6. Tool Proficiency & Integration Knowledge
AI capabilities are embedded into almost all the tools’ BAs use every day. Whether it’s documenting requirements, managing backlogs, or communicating with teams, learning to leverage these tools with AI features will significantly boost productivity and insight generation for BA. This is one of the most practical and immediately useful AI skills.
Examples of AI-augmented tools:
- Integrated Meeting assistants: MS Teams Co-pilot, Fireflies.ai (write Minutes of stakeholder meetings)
- Backlog management: Click up, Jira with AI plugins
- Documentation tools: Gemini AI, Confluence with AI add-ons
What to focus on:
- Learn what AI features exist in your current toolset
- Understand how to use integrations (e.g., connect Jira to Confluence summaries)
- Keep experimenting with emerging tools that helps in your work
Tool proficiency allows BAs to embed AI directly into their workflows. It helps to boost productivity in daily jobs and is an essential component of a business analyst’s AI skills.
Conclusion
The utilization of artificial intelligence in business analytics is reshaping the field of work and the decisions that organizations take. By learning these top AI skills, business analysts can improve their capabilities, bring innovation, and provide greater value to organizations. Embracing AI improves efficiency and opens up new opportunities for growth and success in the dynamic business landscape. Advance your business analyst career with our specialized AI certification course. Read our article on why mastering AI is important for business analysts.
