Digital Transformation
Data
Cloud
AI (Traditional)
Generative and Agentic AI
100

Difference between digitization, digitalization, and transformation?

Digitization = analog → digital; Digitalization = process improvements; Digital Transformation = rethinking business models & culture.

100

Difference between data and information?

Data = raw facts; Information = data + context.

100

Difference between IaaS and SaaS?

IaaS = infrastructure; SaaS = apps.

100

Difference between AI and ML?

AI = simulating intelligence; ML = subset where systems learn from data.


100

ore training task of models like GPT?

Next-token prediction.

200

Biggest leadership challenge in digital transformation?

Culture and mindset change, not technology.

200

Which of the 4Vs is hardest to manage strategically?

Veracity (trust/quality).

200

Harder challenge in migration: tech or governance/mindset?

Governance and mindset.

200

Supervised vs unsupervised learning?

Supervised = labeled data; Unsupervised = pattern-finding.

200

Major risk of GenAI in enterprises?

Hallucinations, bias, data/privacy risks.

300

Two reasons digital transformation often fails?

Lack of strategy, weak leadership, culture resistance, tech focus > customer value, poor execution.

300

Predictive vs prescriptive analytics?

Predictive = forecasts; Prescriptive = recommends actions.

300

What is cloud lock-in?

Dependence on one vendor; switching is costly and limits flexibility.

300

Why weren’t neural networks widely used before 2010s?

Limited compute, data, and scalable algorithms.

300

Why use Retrieval-Augmented Generation (RAG)?

Grounds models in enterprise data for accuracy & trust.

400

Example of a successful business model shift through digital transformation?

Netflix (DVDs → streaming), Adobe (to SaaS), DBS (digital-first bank).

400

Why is governance essential for AI adoption?

Ensures quality, security, compliance, and ethical use.

400

Why go hybrid or multi-cloud?

Flexibility, resilience, compliance, less dependency.

400

One dominant non-Generative AI application today?

Fraud detection, credit scoring, supply-chain optimization.

400

Difference between Agentic AI and Generative AI?

Agentic AI can plan, decide, and act autonomously.

500

What will matter most in the next 10 years: tech innovation or ecosystem orchestration? Why?

Ecosystem orchestration — success depends on platforms, partnerships, networks.

500

Advantage comes from owning data or using it?

From use — insights, decisions, speed, and innovation.

500

How will edge computing reshape cloud?

Moves processing closer to users, lowers latency, enables AI/IoT.

500

Key limitation of traditional AI?

Needs structured data, lacks creativity/adaptability/autonomy.

500

Why could Agentic AI disrupt SaaS?

Agents integrate across apps, reducing single-app SaaS demand.