How to be valuable in the AI era? Approach for Business Analysts and Product Managers


  1. Shift in Product Management (PM) Roles:

    • Earlier, PM roles were generalist-heavy, with MBA graduates favored.
    • Now, technical skills, AI literacy, and domain expertise are critical.
    • AI is automating tasks like PRDs, competitor analysis, and reporting.
    • Scenario: A fintech startup replaces manual competitor analysis with AI dashboards. The BA validates data quality and business rules, while the PM focuses on framing market positioning and strategy to win investor trust.

  2. Changing Hiring Trends:

    • Demand for PMs surged during 2020-2022 but declined post-funding slowdown.
    • Companies now prefer specialized PMs over generalists.
    • Hiring cycles have lengthened, and roles are more selective.
    • Scenario: In a healthtech company, a BA with strong compliance knowledge secures a role by ensuring product requirements meet HIPAA norms, while the PM with clinical domain expertise drives roadmap prioritization aligned with regulations—making the company stand out in selective hiring rounds.

  3. Impact of AI on PM Roles:

    • AI tools handle repetitive tasks, forcing PMs to focus on strategy and validation.
    • Technical fluency (e.g., understanding ML models) is becoming essential.
    • Human judgment remains irreplaceable for decision-making.
    • Scenario: An e-commerce company deploys an AI-based recommendation engine. The BA translates customer behavior data into requirements, while the PM ensures ethical design (avoiding biased product recommendations) and aligns the AI roadmap with revenue goals.

  4. Salary & Career Trajectory:

    • Earlier, PM salaries were high (entry-level ~₹17 LPA, senior ~₹1.3 Cr).
    • Now, compensation is tied to niche skills and AI adaptability.
    • Scenario: A senior PM with AI fluency commands a premium salary in an enterprise SaaS firm by mentoring BAs on leveraging AI tools for automated reporting, thereby saving the company 20% in operational costs.

  5. New PM Profile:

    • Must bridge tech and business, acting as a "mini-CEO."
    • Skills needed: Data storytelling, technical depth, leadership, and AI utilization.
    • Scenario: In a logistics startup, the BA identifies inefficiencies in shipment tracking through data analysis, while the PM builds a business case for an AI-driven optimization product—unlocking a new revenue stream and securing funding.

Approaches for Different Career Stages to Stay Relevant:

1. Early-Career Business Analyst (BA):

  • Upskill in AI & Data: Learn tools for automation (e.g., AI-driven analytics, SQL, Python).
  • Develop Technical Fluency: Understand APIs, databases, and basic ML concepts.
  • Focus on Problem-Solving: Shift from reporting to actionable insights using AI.
  • Gain Cross-Functional Exposure: Work with engineering and design teams to build product intuition.
  • Scenario: A junior BA at an edtech firm learns SQL and uses AI to generate insights on student engagement. The PM leverages these insights to push a feature that improves course completion rates by 15%.

2. Mid-Career Product Manager (PM):

  • Specialize in a Domain: Fintech, healthtech, or AI-driven products need deep expertise.
  • Master AI Tools: Use AI for market research, user feedback analysis, and roadmap prioritization.
  • Improve Leadership: Move from execution to strategy—mentor junior PMs and influence stakeholders.
  • Adopt Data Storytelling: Present insights in a business-impactful way.
  • Scenario: In an insurance company, the BA builds an AI-powered churn prediction dashboard, while the PM uses those insights to design loyalty features, reducing churn by 10%.

3. Experienced Product Manager / Senior PM:

  • Become a Strategic Leader: Drive AI adoption in product development.
  • Focus on Ethical AI Use: Ensure responsible AI deployment in products.
  • Mentor & Upskill Teams: Guide junior PMs on AI integration and technical depth.
  • Explore Adjacent Roles: Transition to CPO, startup advisor, or AI product strategist.
  • Scenario: A senior PM in a healthcare SaaS firm leads AI adoption. The BA defines business rules for patient data security, while the PM ensures ethical AI is built into triage tools—earning trust from hospital clients and expanding market share.

Final Takeaway:

  • AI is an enabler, not a replacement. PMs & BAs who leverage AI will thrive.
  • BA ensures requirements and data integrity, PM ensures vision and market alignment.
  • Technical + Business Acumen is key. The role is evolving into a hybrid of strategy and execution.
  • Continuous learning is non-negotiable. Stay updated on AI trends, regulations, and domain shifts.

Compliled by Dr M Khalid Munir, Product management professional. Used sources like business publications and news reports. 

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