Cloud Digital Leader Why cloud technology is transforming business Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  The government should have used a different cloud provider with better uptime guarantees

  Why it's wrong here

  Selecting a different cloud provider with stronger uptime guarantees would address service availability, yet nothing suggests the platform was unreliable. Adoption is governed by perceived usefulness, ease of use, and institutional trust, not by three-nines versus four-nines performance. Even a perfectly resilient infrastructure will remain unused if citizens find forms confusing, mobile access poor, or data protection ambiguous. Moreover, migrating providers introduces migration risk, compliance revalidation, and cost without altering the core design and outreach gaps.

• ✓

  The initiative overlooked user-centered design, accessibility, digital literacy support, and citizen trust-building — critical dimensions of public sector digital transformation beyond technical delivery

  Why this is correct

  This captures the overlooked dimensions. Citizens adopt digital services when: the experience is intuitive (user-centered design), accessible to people with disabilities or limited technology experience, accompanied by digital literacy support, and trusted to handle personal data securely. Technical availability is necessary but not sufficient.

• ✗

  The government needs to force citizens to use online services by removing all in-person service options

  Why it's wrong here

  Forcing uptake by eliminating in-person channels would erode equitable access and backfire for the most vulnerable users. A compulsory digital-only model discriminates against elderly, disabled, and low-connectivity populations and conflicts with public service obligations to serve all residents. Adoption initiatives should combine intuitive interfaces, assisted digital support, and trusted privacy safeguards, not coercion. Channel stripping does not build capability; it abandons users who genuinely cannot self-serve online.

• ✗

  The initiative should have started with machine learning features before launching basic services

  Why it's wrong here

  Deploying machine learning features before fixing basic adoption assumes that smarter technology drives usage. In practice, ML functions add computational complexity, require rich user-generated data that low-traffic services lack, and demand higher digital competence from citizens. The observed barrier is not insufficient intelligence but poor usability, limited digital literacy, and weak trust; sophisticated features cannot substitute for a clear, accessible workflow. Basic services must first earn regular use before advanced analytics can add value.

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