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AI business school for government Microsoft Quiz Answers

Get AI business school for government Microsoft Quiz Answers

In government, decision-makers must take into account specific public sector considerations before they can realize the true transformational power of AI. It’s critical to understand the components of a strategy that will help the public sector create value with AI. This learning path is designed for government decision-makers to illustrate the true transformational impact of AI in the public sector.

Prerequisites:

None

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Module 2: Define an AI strategy to create value in government

In government, decision-makers must take into account specific public sector considerations before they can realize the true transformational power of AI. Government agencies need to think strategically about AI – and they need to start today. To create real value, a comprehensive understanding of all the strategic components is required.

Learning objectives:

In this module, you will:

  • Describe the outcomes governments have achieved through the adoption of AI.
  • Articulate the components of an AI strategy.
  • Apply the value creation framework.

Prerequisites:

None

This module is part of these learning paths:

Quiz 1: Knowledge Check

Q1. How can governments strengthen their AI outcomes?

  • Replace employees with conversational agents.
  • Leave it to AI experts to plan for and execute an AI solution.
  • Establish data practices that make it easier to collect and aggregate data from a variety of sources.
  • Focus on internal uses of AI above citizen-facing uses.

Q2. Which of the following will most likely help an AI solution perform more effectively?

  • Spending more money on the development of the AI solution.
  • Leveraging domain experts.
  • Developing the solution in-house.
  • Using more complex algorithms.

Q3. A local government is considering implementing an AI solution. Which criteria should it consider when choosing the best use case to start with?

  • Value creation.
  • Cost reduction.
  • Work reduction for employees.
  • Difficulty of data cleansing.
Conclusion:

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