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

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?

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 A standard terms of service acceptance by the clinic is sufficient HIPAA only applies to clinics with more than 20 employees

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?

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

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

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

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 team of 50 professionals already uses Gmail, Google Docs, and Google Sheets daily. Which AI path offers the lowest adoption friction?

Claude API — requires integration by a developer Self-hosted Llama — requires technical setup ChatGPT Enterprise — requires a new platform adoption Google Gemini for Workspace — AI is embedded directly into their existing tools

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?

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

What does SOC 2 certification indicate about an AI tool vendor?

The vendor stores data in the US and is subject to US law The vendor has undergone an independent security audit verifying their security controls, data availability, processing integrity, and confidentiality The vendor's AI models are certified as bias-free The vendor is approved by the US government for handling classified data

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?

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

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

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

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

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 Lock down templates so only administrators can use them Require every user to rewrite 30% of the template before use

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 Free AI tools automatically encrypt all submitted data Free-tier AI tools may use inputs for model training, potentially exposing client financial data — this likely violates professional confidentiality obligations The AI chatbot will share client financial data with the IRS

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?

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

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 the model improvement will be visible to the business within 30 days 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

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?

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

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

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

Which prompting technique best helps a professional use AI to identify blind spots in their own 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 write a better version of the analysis Ask AI to summarize the analysis back in its own words

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

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 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

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

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

A company wants to connect an AI assistant to its private internal knowledge base so it can answer employee questions. Which technique is most relevant?

Retrieval-Augmented Generation (RAG) Switching to an open-source model Building a new foundation model Fine-tuning the foundation model from scratch