AI Consultant Assessment

1. Scenario (5 points)

A mid-sized logistics company is experiencing rising fuel costs, increasing customer complaints about delivery delays, and difficulty retaining experienced drivers.

A1 (3 points): Identify three distinct business problems AI could potentially address for this company.

A2 (2 points): For one of those problems, briefly outline what success would look like (i.e., key performance indicators AI would improve).

2. Value Proposition (5 points)

“AI can save businesses money.” Critique this statement. How would you reframe the value proposition of AI to a CEO who is bottom-line focused but also concerned about long-term strategic positioning and innovation?

3. Opportunity Brainstorm (5 points)

Choose an industry you are familiar with (other than tech). Describe two specific, currently under-utilized AI opportunities that could lead to significant positive and productive change in that industry. Explain *why* these are good opportunities and what kind of AI might be involved.

4. Solution Recommendation (6 points)

A client in the e-commerce sector wants to “use AI to personalize the customer experience.”

B1 (3 points): What clarifying questions would you ask the client *before* recommending any specific AI solutions?

B2 (3 points): Based on potential answers to your questions, describe two different AI-driven personalization approaches you might recommend, highlighting the data needed and the expected customer impact for each.

5. Generative AI Application (5 points)

A marketing department is keen to use generative AI to improve content creation efficiency for their blog and social media. What strategic advice, including potential benefits and crucial watch-outs/risks, would you provide to the Head of Marketing?

6. Functional Change Impact (5 points)

Imagine recommending an AI-powered predictive maintenance solution for a manufacturing plant. Beyond the technical implementation, what key functional changes or adjustments would the plant’s operations and maintenance teams likely need to make to fully realize the benefits?

7. Data Strategy Prerequisite (4 points)

A company has a lot of data but it’s siloed across different departments and of varying quality. They want to jump straight into advanced AI model building. How would you advise them, and what foundational steps would you recommend regarding their data *before* significant AI investment?

8. Ethical Consideration (5 points)

A financial institution wants to use an AI model for loan application approvals to speed up the process. What are the top two ethical considerations you would raise, and what recommendations would you make to mitigate these risks while still achieving their goal of efficiency?

9. Measuring AI Success (5 points)

A company has implemented an AI-powered chatbot for customer service.

C1 (3 points): Beyond “number of queries handled,” what other metrics would you recommend they track to measure the *true* positive and productive impact of this AI?

C2 (2 points): How would these metrics inform future adjustments or improvements to the chatbot or customer service strategy?

10. Overcoming Resistance (5 points)

You are proposing an AI solution that will automate certain tasks currently performed by employees. You anticipate resistance due to fears of job displacement. How would you advise the client’s leadership to manage this change and communicate the AI initiative to their workforce to foster adoption rather than fear?