10 Questions on AI This Week (28th Oct 2025)
- Dr Sp Mishra
- Oct 28
- 4 min read
What students, jobseekers and professionals in India should know. (ICC Blog # 130)
The 10 Questions
Why are global investors still pouring big money into AI infrastructure and startups?
How are major tech companies using India as a strategic hub for AI investment?
What does the shift from “build the model” to “use the model” mean for jobs and skills?
Are we seeing signs of an AI investment bubble?
Why are Indian conglomerates like Reliance Industries Ltd pivoting hard into AI infrastructure?
How is the Indian startup ecosystem responding to global AI investment trends?
Which Indian sectors are emerging fastest for AI-applications (beyond tech start-ups)?
What kinds of roles should students/graduates focus on now if they want to ride the AI wave?
How significant are regulatory or governance shifts (in India or globally) around AI use and investment?
What should professionals already working in India’s tech/knowledge sectors change or upgrade in their skill set this week?
What these Questions on AI mean to you?
1) Why are global investors still pouring big money into AI infrastructure and startups?
The latest data shows that private investment into AI globally jumped significantly in 2024: generative AI alone attracted about US$ 33.9 billion — up ~18.7% from 2023.
Investors believe AI is foundational — infrastructure (data centres, chips, storage), platforms, services — it’s not just a “feature”. Every firm wants to build or use AI at scale, hence the rush.
Why it matters for you: If you’re in tech, data, operations, or planning a career pivot — infrastructure and application-roles will keep growing. Not just “build models” but “deploy models into real business workflows”.
2) How are major tech companies using India as a strategic hub for AI investment?
For instance, Google LLC announced a roughly US$ 15 billion investment over five years to establish its first AI hub in India. That includes large scale data-centre capacity, fibre networks, and local talent development.
What it means: India isn’t just a services/back-office location anymore. It is becoming a core region for global AI infrastructure and capability. For local job-seekers: huge opportunity to participate in global-scale projects in India.
3) What does the shift from “build the model” to “use the model” mean for jobs and skills? Earlier phases of AI invested heavily in model research & training. Now, much of the value is in application — deploying models into workflows, managing data pipelines, integrating AI into business systems.
Career implication: You don’t necessarily need to be a PhD in ML. Roles like AI product manager, AI operations engineer, data-pipeline specialist, domain analyst with AI tools will be in demand.
4) Are we seeing signs of an AI investment bubble?
Yes — the International Monetary Fund (IMF) has warned that the current AI investment boom could resemble the dot-com bubble. The scale of infrastructure spending, speculative valuations, and rush into many novel applications means one must be cautious.
For you: Treat all career bets wisely. Focus on acquiring transferable skills, and pick domains with clear value, not just hype.
5) Why are Indian conglomerates like Reliance pivoting hard into AI infrastructure?
Reliance Industries Ltd is reported to plan an investment of around US$ 12-15 billion into AI infrastructure (datacentres, hardware, AI-products) over the next few years. This signals that even non-pure tech firms see AI as a new growth frontier.
Your takeaway: If you’re interested in roles in non-traditional tech firms (manufacturing, energy, telecom), AI skills could make you stand out in those sectors, not just in “IT companies”.
6) How is the Indian startup ecosystem responding to global AI investment trends?
India’s total AI-investment commitments have crossed US$ 20 billion in 2025 so far.
Moreover, VC firms like Accel and Prosus are jointly investing into Indian deep-tech and AI startups. Angel One, Business Standard+1
What that tells you: There’s increasing funding for Indian-based AI ventures — a good sign for joining early-stage startups or building one.
7) Which Indian sectors are emerging fastest for AI-applications (beyond tech start-ups)?
Key sectors: heavy industry/manufacturing (for automation), telecom/datacentres, retail/consumer-apps, infrastructure. For example, large data-centre deployments and AI hardware rollouts are becoming central in India. TradingView+1
Career insight: If your domain is manufacturing, telecom, operations, supply-chain, logistics — learning how AI is being applied in those sectors gives you an edge.
8) What kinds of roles should students/graduates focus on now if they want to ride the AI wave?
Learn how to use AI tools (even if you’re not a coder) — e.g., data analytics, dashboarding, process automation.
Understand your domain (healthcare, retail, manufacturing) + how AI is applied in it.
Build a small project or internship involving AI application (not just theory).
Stay flexible: the boom might shift fast (see bubble warning) — transferable skills matter.
9) How significant are regulatory or governance shifts (in India or globally) around AI use and investment?
India is moving to mandate clear labelling of AI-generated content to curb deep-fakes. Globally, concerns about energy, infrastructure, concentration of AI power are rising.
What you should watch: AI policy/regulation will affect jobs and roles (e.g., ethics, compliance, governance). Professionals who understand “safe/ethical AI deployment” will be increasingly valuable.
10) What should professionals already working in India’s tech/knowledge sectors change or upgrade in their skill-set this week?
Get comfortable with one or two AI tools relevant to your domain (e.g., automation tools, AI-powered analytics).
Connect with a cross-functional AI project in your organisation (even if incremental).
Keep an eye on “infrastructure-adjacent” skills: data-handling, cloud services, model deployment, monitoring.
Impact of these Questions on AI
Don’t wait for the “perfect AI engineer” position — numerous roles will develop around utilizing AI, not just creating it.
Location is important: With significant investments in India, there's no need to relocate abroad for cutting-edge work.
Hybrid skills are important: combining domain expertise with AI tools and business understanding.
Be wary of hype: Acquire skills that will endure any market corrections.
Take action now: Initiate a small AI-application project in your field. It sets you apart.
Remain curious & adaptable: The environment (infrastructure, regulation, business use-cases) is rapidly changing.
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