AI Landscape Quiz: Do You Know the Models That Matter?

Which layer of the AI stack contains products like ChatGPT, Microsoft Copilot, and Perplexity?

The API and platform layer The training data layer The application layer The foundation model layer

A sales team writes a different prompt every time they need to generate a follow-up email after a meeting. What is the highest-leverage improvement?

Only the most senior team members should use AI — it causes quality variance Switch to a more powerful AI model Each salesperson should develop their own unique prompting style Create a reusable prompt template with clearly marked variables for meeting date, client name, key discussion points, and next steps

A small business owner is considering three AI marketing tools, all with similar feature sets. Which evaluation question is MOST important for long-term cost management?

Which tool was most recently founded? Which tool has the most integrations in their marketplace? What is the pricing at the volume I'll be using? (Many tools have low entry prices that become expensive at scale) Which tool has the best-designed user interface?

A company builds a prompt library in Notion with 30 useful templates. After 3 months, some templates produce worse results than they used to. What is the most likely cause and solution?

AI model updates changed behavior — review and update templates when models are upgraded, and record a version history The team is using too many templates — reduce to fewer than 10 All templates expire after 3 months due to API policy Notion is not a suitable storage tool for prompt templates

A small accounting firm uses the free version of an AI chatbot to help draft client financial summaries. The summaries include client names and income figures. What is the primary data risk?

No risk — small accounting firms are exempt from data confidentiality regulations The AI chatbot will share client financial data with the IRS Free-tier AI tools may use inputs for model training, potentially exposing client financial data — this likely violates professional confidentiality obligations Free AI tools automatically encrypt all submitted data

A small business evaluates an AI tool and discovers it will fine-tune its model using the company's customer data to improve future recommendations. What is the most important consideration before agreeing?

Whether fine-tuning on small business data produces measurably better results Whether using customer data for model training complies with the business's privacy policy and applicable data protection regulations — and whether customers consented Whether the model will be available to the business for download Whether the model improvement will be visible to the business within 30 days

Which Gemini feature most directly reduces hallucination on questions about recent events?

Google Search grounding — responses can be anchored to live Search results Gemini Flash's lower latency Gemini's fine-tuning on Google's proprietary dataset Gemini's large context window

A small law firm uses an AI document tool that stores all case materials. They are considering switching providers. What vendor-related risk should they have addressed during onboarding?

Whether case documents can be exported in standard formats — allowing migration without data loss if they switch providers Whether the new provider offers a lower price Whether the AI was trained on legal documents Whether the existing provider offers referral discounts

A small physical therapy clinic wants to use an AI scheduling chatbot on their website. Patients will input their names, contact info, and appointment reasons (which may reference medical conditions). What is required before deploying the chatbot?

HIPAA only applies to clinics with more than 20 employees A standard terms of service acceptance by the clinic is sufficient A Business Associate Agreement (BAA) with the chatbot provider, since the chatbot may process Protected Health Information under HIPAA Chatbots don't count as HIPAA-covered technology — only EHR systems do

Which of these vendor claims is a RED FLAG suggesting a tool may not have meaningful AI capability?

'AI-powered' prominently featured in marketing but no specific explanation of what the AI does in the product The vendor has raised venture capital funding The tool integrates with Zapier The tool requires a free trial signup before showing pricing

A manager asks an AI to recommend which of two job candidates to hire. What is the correct role for AI in this decision?

AI can make the final hiring decision based on the resume data provided AI can make the recommendation, but a human must type it into the HR system AI can help structure the evaluation criteria and surface considerations, but the hiring decision should be made by the human hiring manager AI is too risky to use in any hiring process

A small business wants to use AI for drafting responses to customer complaints that include customer names and order details. What is the simplest way to reduce privacy risk while still using AI?

Ask the AI not to store the customer's name after the session Use AI only on Tuesdays when server load is lower and data is more secure Never use AI for any customer-related communications Anonymize the data — replace the customer name with 'Customer' and describe the order generically — before sending to the AI tool

What is the biggest risk when an AI produces a confident-sounding analysis of your business?

AI doesn't know your actual organizational context — it analyzes the concept you described, not the specific realities of your situation AI may accidentally leak your business data to competitors The AI may refuse to complete an analysis if the business is in a regulated industry AI analysis is too long — it always produces 10+ pages

A healthcare startup wants to use AI to analyze sensitive patient records. Sending data to external cloud APIs is not permitted under their compliance policy. What type of deployment is most appropriate?

Google Gemini Pro — all Gemini data stays in healthcare-dedicated servers Self-hosted open-source model (e.g., Meta Llama) on the organization's own infrastructure ChatGPT Enterprise — data privacy is guaranteed by contract Whichever model has the highest benchmark score

A strategy team wants to use AI to stress-test a business plan. Which prompt is most effective for this goal?

'Act as a skeptical board member. What are the three riskiest assumptions in this plan, and what evidence would change your view?' 'Summarize this business plan in three paragraphs' 'Tell me if this business plan will succeed' 'What improvements can you make to this plan?'

Which prompting technique best helps a professional use AI to identify blind spots in their own analysis?

Ask AI to write a better version of the analysis Ask AI to list the critical assumptions the analysis relies on, then ask what would happen if those assumptions were wrong Ask AI to score the analysis out of 10 Ask AI to summarize the analysis back in its own words

Which of these prompt template practices is MOST important for a large team to maintain quality over time?

Lock down templates so only administrators can use them Rotate to a new AI model every quarter to keep outputs fresh Document expected outputs alongside each template so users know what 'good' looks like and can spot when quality has degraded Require every user to rewrite 30% of the template before use

A healthcare company is evaluating an AI vendor's product for processing patient records. The vendor's product is built on a closed-source foundation model API. What is the primary data privacy consideration?

The application layer encrypts data before it leaves the company Closed-source models automatically comply with HIPAA The foundation model will permanently memorize patient data Patient data will be transmitted to the foundation model provider's servers

Why can many different AI products (e.g., a writing tool, a customer service bot, a code assistant) feel similar in capability?

They all copy ChatGPT's training data AI models can only do one type of task well They may all be using the same underlying foundation model via API Foundation models are open-source and freely copyable

What is the primary reason Meta makes its Llama models available as open-source at no charge?

Meta's Llama models are too weak to sell commercially Open-source is required by US government regulation for AI models To establish Llama as the dominant open-source standard, growing Meta's AI ecosystem influence and accelerating research adoption Meta cannot afford to run a paid API service