As artificial intelligence continues to reshape how businesses function, one question dominates conversations across boardrooms and classrooms alike: what happens to jobs? In this article, we have discussed with some industrial and educational experts how the workforce can prepare for what lies ahead.
As artificial intelligence reshapes the way businesses operate, questions around which jobs will grow, which will shrink, and how the workforce should prepare for this shift are becoming urgent. We spoke to four experts across recruitment, finance education, AV technology, and higher education to get their perspective.
Which jobs are likely to grow, and which are at risk?
Devashish Sharma, Co-Founder and CEO of Taggd, says AI will boost demand for roles that “build, govern and apply technology to business problems,” while work built around repeatable logic and routine execution will be “fundamentally redefined” rather than eliminated outright.
CFA Sanjay Saraf, Founder of Sanjay Saraf Educational Institute (SSEI), Kolkata, points to growth in AI, data analytics, cybersecurity, risk management, investment research and fraud detection, along with strong demand for professionals who combine domain knowledge with technology.
Roles at greater risk, he says, include routine data entry, standard reporting, reconciliation, and templated research. His sharper warning: the real risk isn’t AI replacing people — it’s professionals who use AI well replacing those who don’t.
Vijay Sharma, Managing Director of Optoma Technology (India), expects a considerable boost in demand for AI integration, automation, data science, cybersecurity, software development, and intelligent AV systems, while manual data entry, administrative functions and customer service will be automated to a large extent.
Dr. Lovi Raj Gupta, Pro Vice-Chancellor of LPU, frames it historically: every technological shift, from computers entering banks and railways, changed the nature of work rather than eliminating it altogether. The roles most at risk, he says, are those “built around repetitive and predictable work.”
Sidharth Thakur, Director, Grassik Search, says, “Professionals today need AI literacy, sound judgment to question AI’s often-flawed outputs, and strong human skills like relationship-building that AI can’t replicate.”
What skills should students and professionals build?
Sharma of Taggd lists AI and Generative AI, machine learning, data science, Python and SQL, cloud engineering, cybersecurity, and full-stack development as key technical skills but adds that critical thinking, judgement, adaptability, empathy and stakeholder management will increasingly determine effectiveness, since “AI can accelerate the process,” but “human judgement, context, and relationships will determine the outcome.”
Saraf identifies three capabilities for finance professionals: strong fundamentals in accounting and valuation, technology and data literacy including Excel, SQL, Python and AI tools, and independent judgement the ability to question assumptions and separate information from insight.
Vijay Sharma emphasises continuous learning over a fixed skill set digital literacy, AI competency, critical thinking and creativity, alongside communication and teamwork.
Dr. Gupta says the most valuable skill isn’t knowing how to use AI tools, but knowing how to apply them to real-world problems, alongside analytical ability, ethical judgment and business understanding.
He notes recruiters are increasingly assessing capability over credentials, favouring live projects, internships and portfolios over theoretical knowledge alone.
Thankur of Grassik Search says “CXOs must get hands-on with AI themselves, since it now touches strategy, capital allocation and customer experience all at once.”
He suggests three habits that could make a real difference: “Block real weekly time for hands-on learning, set up reverse mentorship with the youngest people in your organisation, and study how AI is being deployed outside your own sector; cross-industry pattern recognition matters more than depth in any single tool.”
How should governments, institutions and companies prepare the workforce?
“Sharma of Taggd points to companies mapping skill taxonomies to identify workforce gaps, and highlights TARA Insights, the talent intelligence layer within Taggd’s agentic AI recruitment engine, TARA, as helping bring visibility into talent supply, skill availability and emerging capability needs.”
Saraf calls for a three-way effort: governments investing in affordable reskilling and vocational training, institutions moving beyond exam-focused learning toward AI literacy and live projects, and companies redesigning entry-level roles to give young professionals earlier exposure to analysis and decision-making.
Vijay Sharma stresses collaboration on lifelong learning and modular credentialing, with governments funding subsidised training and companies embedding upskilling into regular workflows.
For the AV sector specifically, he flags network engineering, IoT cybersecurity and AI system integration as priority skills.
Dr. Gupta says curricula must stay dynamic through continuous industry engagement a practice he says LPU follows in line with the National Education Policy but adds that curriculum alone isn’t enough.
Students need internships, live industry projects and multidisciplinary exposure before graduation, with institutions treating employability “as a continuous process rather than a placement outcome.”
Thakur of Graphic Search says governments, institutions and companies must fast-track reskilling toward high-growth areas like AI/ML and cybersecurity, while building transition pathways for at-risk roles like entry-level coders, testers and BPO staff.
