A telecommunications company is considering an AI solution to improve customer service through automated chatbots. The project team is assessing the feasibility of the AI solution by examining its potential scalability and effectiveness.
What will present the highest risk to the company?

• A. The solution may not handle the volume of customer queries effectively.
• B. The team may lack experience implementing AI-based customer service solutions.
• C. The chatbot may not integrate well with existing customer service platforms.
• D. The solution might breach customer data privacy regulations, leading to legal consequences.

An IT services company project manager is creating an AI project scope statement. They need to include details on the environments, devices, and personnel that will use the AI solution. What should the project manager do?

• A. Develop a comprehensive usage scenario analysis.
• B. Create an AI efficacy program to complete the scope statement.
• C. Perform a detailed technical requirements audit for the scope statement.
• D. Gain stakeholder buy-in to proceed with the project.

The growth of Big Data has led to a desire to be able to do more to process and extract more value from Big Data. Simply storing data and providing analytics is no longer enough anymore to remain competitive. To keep your organization competitive, you need to:

• A. Make sure the technical team has deep understanding of big data and how best to extract value from big data to unleash it for competitive advantage.
• B. Make sure all senior leadership is data literate, understands the Vs of big data, data's connections to your specific team, and how to extract value from big data to unleash it for competitive advantage.
• C. Make sure senior management has deep understanding of big data and how best to extract value from big data to unleash it for competitive advantage.
• D. Make sure everyone on the team has an understanding of data, its connections to the organization, and how to extract value from big data to unleash it for competitive advantage.

A project team has completed the Data Preparation phase. The prepared dataset meets quality thresholds, but the effort consumed 60 percent of the total project budget.
What should the project manager do at this stage?

• A. Reduce the scope of the modeling phase to recover budget
• B. Escalate the budget overrun to the change control board for approval
• C. Conduct a go/no-go review that reassesses business value against remaining budget
• D. Continue to Data Modeling since the data quality objective was achieved

A project manager meets with a customer for initial discussions about an upcoming project. At the end of the meeting, the customer asks the project manager for a rough estimate of the project duration. Based on her experience with three similar projects, the project manager provides an estimate of 8-10 months. What's wrong with this timeframe?

• A. It's underestimating the project timeline by 3 months
• B. It's not accounting for data preparation timelines
• C. It fits into a waterfall timeframe, but not an agile project timeframe
• D. It's not accounting for potential project delays