Identify AI concepts and capabilities (40–45%)

Microsoft Certified: Azure AI Fundamentals · 126 questions

A factory installs cameras above a bottling line so a system can automatically flag bottles with cracked caps or mislabeled bottles before they reach packaging. Which AI workload category best fits this system?
A bank's data science team is building a model to approve or deny personal loan applications. During testing they discover the model approves loans for applicants from one zip code at a much lower rate than applicants with similar income and credit history from other zip codes. Which Microsoft responsible AI principle is most directly at risk here?
A telecom company adds a chat widget to its support site that lets customers type questions in plain English, such as why their bill is higher this month, and receive a natural-language answer without waiting for a human agent. Which AI capability is this chat widget primarily demonstrating?
A real-estate analytics firm trains a model using historical sales records that include square footage, number of bedrooms, neighborhood, and the final sale price of each home. After training, the firm feeds the model square footage, bedrooms, and neighborhood for a new listing to estimate its price. In this setup, the final sale price used during training is best described as which of the following?
A law firm has 50,000 scanned contracts stored as PDF and image files and wants to build a searchable index that extracts key terms, dates, and parties from each document so paralegals can locate specific clauses in seconds. Which AI capability addresses this need?
A hospital deploys an AI system that recommends a likely diagnosis to physicians based on patient scans and lab results. The compliance team requires that physicians can see which factors drove each recommendation, and also requires that the patient scan data used by the system is protected from unauthorized access. Which two Microsoft responsible AI principles are being addressed by these two requirements? (Select TWO.)
A marketing team wants a tool that can take a short product description and produce several draft social media captions with different tones, which staff then edit before publishing. Which AI capability should the team use?
A card-payment processor wants to flag transactions that deviate sharply from a customer's normal spending pattern, but the company has almost no historical examples labeled as confirmed fraud. Which AI approach is most appropriate for this situation?
A regional bakery chain wants a system that reads handwritten notes from suppliers, submitted as scanned images, and turns them into searchable digital text stored in their inventory database. Which capability of AI should the vendor propose as the core building block for this solution?
An airline's customer service team receives thousands of typed chat messages daily and wants to automatically flag messages expressing frustration or anger so agents can prioritize them. Which AI capability best fits this requirement?
A logistics company is building a forecasting tool that predicts next week's fuel prices using ten years of historical daily price and demand data. The output needed is a continuous numeric value, not a category. Which type of machine learning task should the data science team frame this as?
A hospital wants an AI system to examine chest X-ray images and draw a bounding box around any region suspicious for pneumonia, so radiologists can quickly see where to focus. Which computer vision capability directly supports this requirement?
A retail company is evaluating vendors for an AI system that will approve or deny store credit applications. During due diligence, the company learns the training data historically contained far fewer approved applications from one zip code than its population would suggest. Which responsible AI principle is most directly at risk if this is not addressed before deployment?
A software team is comparing two natural language processing approaches for a customer support chatbot. Approach one uses a large pretrained language model that can generate open-ended, fluent responses to a wide variety of unscripted questions. Approach two uses a smaller model trained only to match customer questions against a fixed set of predefined intents and reply with scripted answers. Which statement correctly distinguishes generative AI from this second, non-generative approach?
A manufacturing plant deploys an AI system on the factory floor that monitors a robotic arm's sensor readings in real time and immediately halts the arm if it detects a reading pattern consistent with an imminent mechanical failure, to prevent injury to nearby workers. Which two responsible AI considerations are most directly demonstrated by designing the system to prioritize an immediate safe shutdown over continuing operation when uncertainty is high? (Select TWO.)
A city government wants to deploy a chatbot on its website to answer residents' questions about permit applications, using natural language so residents can type questions in everyday phrasing rather than selecting from a menu. During planning, which underlying AI capability should the team identify as necessary for the chatbot to interpret what a resident is actually asking?
A university admissions office wants to use a service that can accept a photo of a handwritten application form and output the applicant's name, address, and date of birth as structured text fields, without training a custom model. Which Azure AI capability should the office use?
A subscription box company wants to predict which of its current customers are likely to cancel their subscription in the next 60 days, using each customer's order history, support ticket count, and login frequency, so the retention team can reach out first. Which machine learning approach fits this need?
A game studio is building a mobile app that lets players scan a physical trading card with their phone camera and see the exact card's name and rarity displayed on screen, even though the studio has thousands of unique card designs. Which Azure AI service is best suited to this task, and which characteristic of the training data matters most? (Select TWO.)
A regional news outlet publishes hundreds of articles a day and wants readers to see a two-sentence summary at the top of each article without an editor manually writing one for every story. Which Azure AI Language capability addresses this need?
A hardware retailer wants to add a search feature that lets customers type a plain-language question like 'a drill that works well for tile and concrete' and get relevant product matches, even when the exact words do not appear in the product descriptions. The retailer is evaluating whether this requires generative AI or a simpler approach. What should guide that decision?
A call center manager wants to search past customer service calls for specific phrases mentioned during conversations, but currently only audio recordings exist. Which Azure AI capability should be used first to make the calls searchable by text?
An engineering team is training a warehouse robot to navigate around shelving units. The robot has no labeled dataset of correct paths; instead it repeatedly attempts routes and receives a positive score when it reaches the target faster and a penalty when it collides with obstacles, gradually improving its behavior over thousands of attempts. Which type of machine learning does this describe?
A grocery chain has years of purchase transaction data but no predefined categories for its shoppers. The marketing team wants an algorithm to automatically group customers into segments based on similarities in what they buy, without specifying labels in advance. Which machine learning approach fits this need?
A bank's AI system evaluates personal loan applications automatically. After a customer is declined, the compliance department wants the system to provide a clear, understandable statement of which factors most influenced the decision, so the applicant can see why they were declined. This requirement aligns most directly with which responsible AI principle?
A law firm builds an internal chatbot on a large language model to answer questions about the firm's specific internal compliance policies. During testing, the chatbot confidently states policy details that sound plausible but do not actually appear in any of the firm's documents. To reduce this problem, the team plans to have the chatbot retrieve relevant passages from the firm's own policy documents and include them in the prompt before generating an answer. What problem is this design meant to address?
A packaging company installs a camera above its bottling line. The system must read the expiration date text printed on each bottle cap and also draw a bounding box around any bottle that is missing its cap entirely so it can be automatically diverted off the line. Which two Azure AI Vision capabilities together satisfy these requirements? (Select TWO.)
A small manufacturing startup has only 200 photographs of its five proprietary machine part types and wants an image classifier that can tell the parts apart. The team has no data science staff and cannot collect thousands of additional images. Which Azure AI approach best fits this constraint?
An airport wants a self-service kiosk that compares a traveler's live camera photo against their passport photo to confirm identity before boarding, speeding up the line. Privacy advocates raise concerns about storing biometric images. Which Azure AI capability provides the core identity-matching function the airport is describing?
A conference organizer wants spoken presentations, delivered live on stage, to appear as scrolling captions on a screen for attendees in real time, updating within a second or two of each word being spoken. Which Azure AI capability should the organizer use?
A retailer has three years of purchase history for its loyalty members but has never assigned any of them to a segment or category. A data scientist wants an algorithm to examine the purchase patterns and discover natural groupings of similar shoppers on its own, without being told in advance what the groups should be. Which type of machine learning task is this?
A circuit board manufacturer wants a vision system that can look at photos of assembled boards and flag three defect types unique to its own product line, such as a specific solder bridge pattern that only appears on its custom connectors. A general-purpose image tagging service returns labels like 'circuit board' and 'metal' but has no concept of these specific defect types. What should the manufacturer do?
A hospital's data science team is tuning a screening model for a rare but serious disease. They deliberately adjust the decision threshold so the model flags more borderline cases as positive, accepting more false alarms in exchange for catching nearly every true case, because a missed diagnosis is far more costly than an unnecessary follow-up test. Which evaluation metric are they prioritizing?
A grocery chain installs cameras with facial recognition at store entrances to automatically identify loyalty-program members as they walk in, but it does not post any signage, update its privacy policy, or otherwise tell shoppers that facial recognition is running or how the images are used. Which responsible AI principle is most directly violated?
A law firm's document review team has 20,000 signed contracts as plain text and wants an automated step that scans each contract and pulls out structured items such as company names, monetary amounts, and effective dates, so paralegals can populate a tracking spreadsheet without reading every page. Which Azure AI Language capability fits this need?
A software company's support tickets arrive as typed text in French, German, and Japanese, but its support agents only read English. The company wants an automated step that converts each incoming ticket's text into English before it reaches an agent's queue, preserving the original meaning as closely as possible. Which Azure AI capability fits this need?
An insurance company is building an intake pipeline for claims submitted as photographs of handwritten paper forms. First, the text on each scanned form must be digitized into machine-readable text. Second, the extracted claim description must be checked for negative or urgent emotional tone so distressed claimants are routed to a priority queue. Which two Azure AI capabilities does this pipeline require? (Select TWO.)
A city parks department wants to know, ahead of time, how many visitors will show up at each park each day so it can schedule enough staff. It has three years of daily attendance records along with the day's weather and whether it was a holiday. It wants to feed in tomorrow's forecasted weather and get back a predicted attendance number for each park. Which Azure AI Foundry capability best fits this need?
A used-car marketplace wants to help sellers set an asking price. It has a database of past listings that already includes the final sale price alongside mileage, age, and condition rating for each vehicle. The company wants a model that, given a new car's mileage, age, and condition, outputs a suggested price. Which type of machine learning problem is this?
A nonprofit is building a mobile app that lets field workers photograph plant leaves to identify crop diseases. Leaves can be affected by more than one disease at once, and the app must return every disease it detects in a single photo, not just the most likely one. Which computer vision capability should the development team use? (Select TWO.)
A meal-kit delivery service wants to add a feature where customers type a request like 'something quick with chicken and no dairy' into a search box and get back matching recipes, even though none of the recipe titles contain those exact words. Which Azure AI capability is the customer directly interacting with when they type that request?
A ride-share company wants a system that watches live video from parking-lot cameras and immediately alerts security the moment it detects a person entering a restricted loading zone, without any human reviewing the footage first. Which combination of considerations should the team prioritize when choosing a computer vision approach for this specific requirement?
A regional bank deploys an AI system that automatically approves or declines personal loan applications. Executives want a governance structure where every automated decision can be traced back to a specific model version, a designated team is responsible for monitoring outcomes over time, and a human panel can be convened to review any disputed decision. Which Responsible AI principle is the bank primarily implementing with this structure?
A retail chain installs a ceiling-mounted camera at each store entrance. The company wants software that draws a box around every person who walks through the doorway and outputs a running count of visitors per hour, without identifying who any individual shopper is. Which computer vision capability should the company implement?
A consumer electronics brand's marketing team wants to monitor thousands of daily social media posts that mention its products and automatically tag each post as positive, negative, or neutral in tone, so the team can react quickly if a wave of negative posts appears about a newly launched phone. Which AI capability should the marketing team use?
A publisher converting its catalog of novels into audiobooks wants software that takes the plain-text manuscript of a book and produces natural-sounding narrated audio in a chosen voice, without hiring a human narrator for every title. Which AI capability fits this need?
A video streaming service wants to suggest new shows to each subscriber based on patterns across what similar subscribers have watched and rated, aiming to increase watch time without asking subscribers to fill out a preference survey. Which type of AI solution is being described?
A data science team builds a model to flag fraudulent credit card transactions. Only about half a percent of transactions in the historical dataset are actually fraudulent. A junior analyst reports that the model is excellent because it is 99.4 percent accurate, but closer inspection shows the model labels every single transaction as legitimate and never flags fraud at all. Which evaluation approach would have revealed the problem that overall accuracy hid?
An autonomous vehicle company trains a vision model that assigns every individual pixel in a camera frame to a category such as road, sidewalk, vehicle, or pedestrian, producing a colored map of the entire scene rather than boxes drawn around individual objects. Which computer vision technique is being described?
A software company's product team lists four proposed features and must identify which ones are examples of generative AI, since that decision determines which Azure AI Foundry model catalogue the engineering team should draw from. Feature one drafts a first version of a marketing email from a short list of bullet points. Feature two predicts next quarter's server costs from historical usage data. Feature three writes several alternate product description paragraphs in different tones from a single input sentence. Feature four groups support tickets into unlabeled clusters based on similarity. Which two features are examples of generative AI? (Select TWO.)
A photo-classification startup trains a model on its labeled training set and it reaches 99 percent accuracy there, but the same model correctly labels only 61 percent of brand-new photos customers submit once it goes live. The live photos come from the same product catalog and were labeled using the same rules as the training set. Which concept best explains the gap between training and live performance?
A retail company builds a resume-screening model using five years of past hiring decisions as training data. Most of those past hires came from a small set of universities that historically enrolled few students from certain underrepresented backgrounds. After deployment, the model consistently scores equally qualified candidates from those backgrounds lower than candidates from the well-represented universities. Which responsible AI principle is most directly at risk in this scenario?
A healthcare software vendor publishes a public model card for its diagnostic-support tool that lists the tool's intended use, known limitations, and the sources of its training data. The vendor also requires a named clinical lead to personally review and sign off on every case the tool flags before the result reaches a treating physician. Which two responsible AI principles does this combination of practices demonstrate? (Select TWO.)
A retail analytics team builds a regression model to predict a store's monthly revenue. The inputs include the store's square footage, the number of sales staff scheduled, and the local population within five miles. The team also includes each store's actual monthly revenue from the past three years so the model can learn the relationship between the inputs and that outcome. In this dataset, what role does 'actual monthly revenue' play?
An airport security team uses a model to flag checked bags for manual inspection. Missing an actual prohibited item is far more costly than sending an extra harmless bag for inspection, so the team wants the model tuned to catch as many true threats as possible even if that means more bags get flagged unnecessarily. Which evaluation metric should the team prioritize when tuning the model?
A startup wants to compare the output quality of several pre-built large language models side by side before choosing one to power its customer chatbot, without writing any training code or collecting new training data. Which Azure AI Foundry capability directly supports this goal?
A payments company's fraud-detection model performed well when first deployed. Eighteen months later, without any change to the model itself, it starts missing fraud patterns because customers have gradually changed how and where they shop. Which concept describes why a previously accurate model degrades over time as real-world patterns change?
A bank wants to predict the exact dollar amount a customer will owe at the end of their loan term, expressed as a specific continuous number such as 4382.17, rather than sorting customers into pass or fail categories. Which AI workload type fits this goal?
An HR technology company trains a resume-screening model on ten years of its own hiring decisions. A later audit finds the model consistently scores resumes from a particular demographic group lower than equally qualified resumes from other groups, mirroring biased patterns baked into the historical hiring data. Which Responsible AI principle should most directly guide the company's response?
A paralegal uses a generative AI writing assistant to help draft a court motion. The assistant produces a citation with a plausible-sounding case name, a specific year, and a docket number, formatted exactly like a real legal citation. When the paralegal searches every available legal database, no such case exists anywhere. Which concept describes what the assistant did?
A bakery installs a vision system on its production line that inspects an image of each pastry and returns a probability that it is defective. Engineers configure the reject arm to activate only when that probability exceeds 90 percent, so that pastries with minor visual noise, like a bit of extra flour dust, are not removed unnecessarily. What is being configured here?
A photo storage app scans each uploaded picture and assigns every tag that applies. A single photo from a birthday party held at the beach might receive the tags 'outdoor,' 'people,' 'cake,' and 'water' simultaneously, rather than being forced into just one category. Which capability produces this kind of output?
A regional bank's automated loan-approval system must ensure that applicants from different neighborhoods with similar financial profiles receive similar approval outcomes, and separately must ensure that applicants' income statements and identity documents are encrypted and accessible only to authorized staff. Which two Responsible AI principles are most directly addressed by these two requirements? (Select TWO.)
A retail company collects thousands of customer product reviews as free text and wants a single score for each review classifying the customer's overall tone as positive, negative, or neutral, without needing a list of specific topics or products mentioned. Which Azure AI Language capability should the team use?
A manufacturer streams temperature, vibration, and pressure readings from a factory machine every second. Engineers have not defined fixed threshold values for what counts as a problem, but they want the system to automatically flag any reading pattern that deviates sharply from the machine's normal historical behavior. Which AI workload fits this need?
A software company's internal help-center has thousands of articles. Employees often type questions in their own words, such as how do I get my money back, and expect the system to return the refund-policy article even though that article never contains the word money or back. Which capability should the search feature rely on?
A bank's compliance team is rolling out an automated loan-decision system and sets two requirements: first, the system must be able to give each applicant a clear, understandable reason for its decision that they can review and contest; second, the system must keep working correctly and safely even when it receives unusual or edge-case applications it was not explicitly trained on. Which two Microsoft responsible AI principles do these requirements most directly reflect? (Select TWO.)
A team building a spam-email filter reviews their model's mistakes and decides that a legitimate email being wrongly marked as spam and hidden from the user is far more damaging than an actual spam email slipping into the inbox. Which evaluation metric should the team prioritize maximizing when tuning the model?
A retail marketing team types a two-sentence description of a new backpack into a tool and receives back five original, ready-to-use ad slogans, each written in a distinct tone such as playful, luxury, or minimalist, none of which existed anywhere before the request. Which category of AI capability produced this output?
A podcast production company records hour-long interviews as audio files and wants software that automatically converts each recording into an editable written transcript its staff can search, edit, and use as show notes. Which Azure AI capability accomplishes this?
A law firm holds decades of case files as scanned image pages, native PDFs, and Word documents. The firm wants a single search index that extracts the text buried in scanned pages, tags people and organizations mentioned throughout, and lets staff run one search query across all of these different, previously unsearchable document formats at once. Which AI workload describes this combined solution?
A factory attaches vibration sensors to a stamping press and logs a reading every second for an entire year. Engineers have never recorded an actual equipment failure in that time, so there are no labeled examples of what a breakdown looks like. They want the AI system to learn the machine's normal vibration pattern on its own and flag any reading that deviates sharply from that pattern, so a technician can investigate before a breakdown occurs. Which type of AI workload fits this requirement?
A hospital pilots an AI model that recommends dosage adjustments for a high-risk intravenous medication. Before letting the system influence real patient care, the clinical team runs extensive testing against rare edge cases, requires that every recommendation pass through a clinician for review, and continuously monitors the model's error rate after go-live so problems are caught quickly. Which responsible AI principle are they primarily applying?
A voice-controlled kiosk deployed in transit stations correctly understands able-bodied adult speakers but frequently fails to recognize commands from riders who use assistive speech devices or who speak with strong regional accents. The vendor responds by expanding its training data to cover a much wider range of speech patterns and by adding alternative input methods such as touch and text for anyone the voice system still struggles with. Which responsible AI principle does this response primarily address?
A research hospital wants to train a diagnostic model using ten years of patient imaging and lab records. Before any data scientist can access the dataset, the hospital's IT team strips out direct identifiers such as names and medical record numbers, encrypts the data at rest, and restricts access to a small approved team under audited credentials. Which responsible AI principle are these controls primarily supporting?
A conservation group deploys motion-triggered trail cameras that often capture several animals in a single photo. They need software that locates each individual animal in the frame, draws a separate box around it, and labels its species, so researchers can count how many individuals of each species appear per photo. Which computer vision capability fits this requirement?
A university library digitizes fifty years of scanned theses and research papers that have inconsistent file names and no catalog. Staff want researchers to type a topic into a search box and instantly retrieve relevant documents, with the system automatically pulling out metadata such as author names and publication years from the scanned text so results can be filtered. Which AI capability class fits this need?
A city council wants live captions displayed on a screen during public meetings as officials speak, so attendees who are deaf or hard of hearing can follow the discussion in real time. Which AI capability should the team implement?
A media company wants to publish English-language interview recordings to international audiences. The plan is to first produce an accurate written transcript of each recording, then convert that transcript into subtitle text in French, German, and Portuguese. Which two AI capabilities does this workflow require? (Select TWO.)
A robotics engineering team is training a warehouse picking robot in a simulated environment. The robot receives a positive score each time it retrieves an item and returns it to the correct bin within a time limit, and a negative score whenever it collides with a shelf or drops an item. Over thousands of simulated attempts, the robot's navigation strategy improves without any human labeling individual moves as right or wrong. Which type of machine learning approach is being used?
A law firm's e-discovery team must review thousands of emails collected for a case and automatically flag every mention of a person's name, company name, and date so paralegals can review them for privilege before production. The firm wants software that scans the plain text of each email and picks out these specific categories of words, rather than just searching for a single keyword typed by a user. Which AI capability should the firm use?
A city government is building a mobile app AI feature that reads street signs aloud and describes nearby obstacles for pedestrians who are blind or have low vision. During testing, the team specifically recruits users with a range of vision impairments, color blindness, and different reading devices to make sure the feature works well for all of them, not just users who tested it internally. Which responsible AI principle is the team primarily addressing by broadening its test group this way?
A prop-tech startup is building a supervised regression model to predict home sale prices. For each historic listing in its training dataset, the team records the square footage, number of bedrooms, and neighborhood, and it also records the actual final sale price the home achieved. (Select TWO.) Which two elements of this dataset make supervised learning possible?
A logistics company receives paper bills of lading from freight drivers. Each form has a similar layout with a shipment ID, ship and delivery dates, and a signature line in roughly the same place. The company wants software that scans a photo of each form and returns the shipment ID, dates, and signature presence as separate structured fields it can feed directly into its transportation management system, rather than just a block of extracted text. Which AI capability best fits this need?
A regional bank's finance operations team automates two processes. The first automatically approves and reimburses any expense report under $50 whenever the total matches a fixed threshold coded directly into the workflow. The second reviews years of past transaction records, learns the spending patterns that preceded confirmed fraud cases, and flags new transactions that resemble those patterns even though no explicit threshold was written for them. Which process is best classified as an artificial intelligence workload?
A specialty chocolatier uses a vision model to inspect truffles on its packaging line before they go into gift boxes sold at a premium price. Discarding a perfectly good truffle that the model mistakenly flags as defective wastes an expensive, hand-finished piece, while a genuinely defective truffle that slips through is rare and is usually caught by a human at the next station anyway. Which evaluation metric should the team prioritize when tuning the model's decision threshold?
An agricultural technology company builds a computer vision model that runs on drones to identify irrigation leaks in farm fields. Before allowing the drones to operate over active fields, the company tests the model against thousands of images captured in fog, direct sunlight, dust, and after recent rain, and refuses to deploy it until it performs consistently across all of those conditions. Which responsible AI principle does this practice primarily reflect?
A software company deploys a generative AI chatbot to answer customer questions about its own product line. To reduce the chance that the chatbot invents a feature or a return-policy detail that does not actually exist, the engineering team configures it to first retrieve relevant passages from the company's current product manuals and support articles, then instructs the model to base its answer only on those retrieved passages. What is this technique called?
A data science team receives a large set of customer transaction records with no labels indicating which customers belong to which segment and no flags marking which transactions are fraudulent. The team wants to use unsupervised machine learning to group customers into naturally occurring segments based on purchasing behavior, and separately to identify transactions that deviate sharply from typical patterns without being told in advance what fraud looks like. Which two techniques should the team apply? (Select TWO.)
A media monitoring service ingests thousands of news articles per day and needs to automatically pull out the specific companies, people, and locations mentioned in each article so analysts can search and filter by those entities later. Which natural language processing capability should the service use?
A publishing company wants to convert its catalog of e-books into audio versions automatically, producing natural-sounding narration directly from the written text of each book without hiring voice actors. Which AI capability accomplishes this?
A retail company wants to add a product-recognition feature to an in-store kiosk that has limited processing power and a requirement that results appear within a fraction of a second, even when the kiosk's internet connection is unreliable. A larger, more accurate cloud-hosted vision model is available in Azure AI Foundry's model catalog but requires a network round trip and noticeably more processing time. Which factor should most influence the team's choice of model?
A retail store installs a camera above its entrance that detects human faces in the video feed and increments a counter each time a face passes through the frame. The system never stores an image, compares a face to a database, or determines who anyone is; it only notices that a face is present and where. Which AI capability does the store's system use?
A customer support team receives thousands of open-ended feedback comments each week and wants software that automatically pulls out the main topics and terms mentioned in each comment, such as 'shipping delay' or 'packaging damage', without judging whether the comment expresses a positive or negative opinion. Which natural language processing capability should the team use?
A convenience store wants a camera system to scan a photo of a stocked shelf and return the location and category of every individual product visible, such as three soda bottles in the upper left and two chip bags in the lower right, rather than a single label describing the whole photo. Which computer vision capability fits this need?
A manufacturer wants a vision model that recognizes forty different proprietary bracket models unique to its own product line, none of which appear in any public image dataset. The pre-built image classification API the team evaluated was trained on common household and industrial objects and cannot tell the forty brackets apart, returning only a generic 'metal part' label for all of them. What should the team do to get accurate, part-specific results?
A company records its weekly three-person planning meetings and wants a transcript that not only converts the speech to text but also labels each line with which of the three participants said it, so readers can follow who proposed each action item. Beyond basic speech-to-text transcription, which additional capability does the team need?
A software company deploys a generative AI chatbot to answer employee questions about internal HR policy. Because the underlying language model was trained on general public text and has no knowledge of the company's specific, frequently updated policy documents, engineers configure the chatbot to first retrieve relevant passages from the company's internal policy repository and insert them into the prompt before the model generates its response. Which concept does this design apply?
An operations team is scoping four candidate AI features for next quarter's roadmap and must sort each one by workload type to budget for the right specialists. (Select TWO.) The candidates are: extracting invoice line items from scanned image files using optical character recognition, translating shipping manifests from English into Spanish, counting vehicles in traffic camera footage using object detection, and condensing lengthy supplier contracts into short paragraphs. Which two candidates are computer vision workloads?
Before deploying an automated resume-screening model, a company's AI governance board requires that one named executive be formally designated as responsible for reviewing the model's decisions and for answering to regulators or affected candidates if the system causes harm. Which responsible AI principle does this requirement primarily reflect?
A parking garage operator wants a camera system that, for each captured frame, draws a separate bounding box around every vehicle in view and labels each one by type (car, truck, motorcycle), so the system can report how many of each type are currently parked. Which Azure AI Vision capability should the team use?
A city library is designing an accessibility kiosk for visitors with low vision. The kiosk must be able to (1) read the printed text on a posted event schedule aloud and (2) describe the general content of a photo on a nearby exhibit wall in a natural-language sentence. Which two Azure AI Vision capabilities does the team need to combine to meet both requirements? (Select TWO.)
A regional utility company wants to predict, for each of the next 168 hours, the expected electricity demand using a sequence of past hourly readings, calendar effects, and weather forecasts, so operators can plan generation capacity a week ahead. Which machine learning approach best fits this need?
A consumer lender's board adopts a policy for its automated credit-decision system stating that a specific, named team must be able to explain any individual automated decision, that customers may request a human review of an automated denial, and that the team bears responsibility if the system causes harm. Which responsible AI principle does this policy primarily implement?
An online furniture retailer has purchase histories for 200,000 customers but no predefined customer categories. A data science team wants a model to discover natural groupings of customers with similar buying patterns on its own, without being told in advance what the groups should be or how many exist. Which type of machine learning task fits this goal?
An e-commerce company collects thousands of product reviews each month and wants to automatically compute an overall customer satisfaction trend by determining whether each review's overall tone is positive, negative, or neutral, without a human reading every review individually. Which AI capability should the team apply to each review?
A company deploys a generative AI chatbot on its public website to answer visitor questions. Before any chatbot response is shown to a visitor, the company wants an automated check that screens the generated text for hate speech, violence, and self-harm content and blocks or flags anything that crosses a defined severity threshold. Which capability satisfies this requirement?
A credit card processor monitors millions of transactions per day and wants a model that learns the normal spending pattern for each cardholder and flags any transaction that deviates sharply from that pattern for manual review, without being given a labeled dataset of past transactions marked fraud or not fraud. Which AI capability fits this requirement?
A stock-photography marketplace wants to automatically generate a list of descriptive keywords for each uploaded photo, such as 'beach', 'sunset', and 'dog', so customers can find the photo through keyword search. The marketplace does not need to know where each object sits within the frame, only which concepts appear somewhere in the image. Which AI capability best fits this requirement?
A museum is building a mobile app feature that, when a visitor points their phone camera at an exhibit placard, must (1) produce a one-sentence natural-language description of what the photo shows and (2) pull out any printed text visible on the placard, such as the artifact's name and date. Which two AI capabilities does this feature require? (Select TWO.)
A logistics company hosts live conference calls between English-speaking dispatchers and Spanish-speaking drivers and wants each spoken sentence translated into the other party's language and spoken back almost immediately during the live call, rather than produced afterward as a written transcript. Which AI capability addresses this requirement?
A global software company's support ticket system receives messages in dozens of languages and must automatically identify which language each incoming ticket is written in before deciding which regional support queue and translation pipeline to route it to. Which AI capability should run first in this pipeline?
A food delivery startup wants a model that predicts, for each new order, the estimated number of minutes until the food arrives at the customer's door, expressed as a specific number such as 27 minutes rather than a category such as 'fast' or 'slow'. Which type of machine learning model fits this requirement?
An aviation manufacturer is building an AI system that predicts when a jet engine component is likely to fail so that maintenance crews can replace it before an in-flight failure occurs. Because an incorrect prediction could put passengers at risk, the engineering team requires the model to be rigorously tested against edge cases, monitored continuously in production, and never deployed until it consistently performs as expected under real-world operating conditions. Which Microsoft responsible AI principle is the team primarily applying by requiring this level of testing and monitoring?
A hospital is deploying an AI system that recommends which patients should be prioritized for a limited number of ICU beds during a surge in admissions. The clinical governance board requires that the system be validated to perform consistently across patients of different ages, ethnicities, and insurance types, and that it undergo extensive testing under simulated surge conditions before any patient's care is affected by its recommendations. Which two responsible AI principles is the board applying with these requirements? (Select TWO.)
A corporate legal team has forty years of scanned contracts stored as PDF images with no searchable index. They want an AI solution that extracts entities such as party names, dates, and clause types from the scanned documents and builds a searchable index so paralegals can quickly locate every contract mentioning a specific counterparty. Which AI workload category best describes this solution?
A retail marketing team wants an AI tool that, given a short prompt describing a new product and a few example paragraphs written in the company's brand voice, produces original draft marketing copy for the team to edit and approve before publishing. Which AI workload does this describe?
A data science team trains a classification model on a labeled dataset and achieves 99% accuracy when they evaluate it on the exact same rows used for training. When they run the same model against a separate set of labeled rows that were held out and never used during training, accuracy drops to 61%. What does this gap between the two accuracy figures most likely indicate?
A water treatment plant streams temperature, pressure, and flow-rate readings from hundreds of sensors every second. Engineers do not want to define every possible failure pattern in advance; instead they want a model that learns what normal combined sensor behavior looks like and automatically flags any reading pattern that deviates significantly from that learned norm for human review. Which AI capability does this describe?
A veterinary clinic wants an AI feature that reviews each uploaded x-ray image and assigns it to exactly one of four triage categories, normal, fracture, foreign object, or inconclusive, so a technician can prioritize review order. The clinic does not need the software to mark where on the x-ray any abnormality appears, only which single category best describes the whole image. Which computer vision capability is the simplest fit?
An online lender uses an AI model to help decide whether to approve a personal loan application. Company policy requires that every applicant be told when an AI system contributed to the decision and be given a plain-language description of the general factors the model weighed, such as income and credit history. Which responsible AI principle does this disclosure requirement most directly support?
A telecom company is rolling out a virtual support agent embedded in its mobile app. Before launch, the team adds screen-reader-compatible transcripts for every spoken response, a plain-language mode for non-native speakers, and holds testing sessions with customers who have motor impairments and use switch-access devices. Which Responsible AI principle is this work primarily addressing?
A grocery chain is preparing to deploy a self-checkout camera system that flags unscanned items in the bagging area. Before the rollout, engineers run the model against thousands of hours of footage captured under fluorescent lighting, dim evening lighting, and glare from sunlight through storefront windows, and they configure the system to route any low-confidence detection to a cashier for manual review rather than automatically flagging the customer. Which Responsible AI principle does this testing and fallback design mainly reflect?
A regional bank's fraud detection team trains a model on years of customer transaction history. Before any engineer can query the training data, the security team requires the data set to be encrypted at rest, restricts access to a named list of approved data scientists, and logs every query run against the data for later audit. Which Responsible AI principle is the security team primarily enforcing?
A retail analytics team is scoping four candidate features for a new store-monitoring system: counting how many shoppers pass through the front entrance by detecting people in video frames, drawing a bounding box around each shopping cart in a camera frame and labeling it 'cart', condensing a week of customer email complaints into a short list of recurring themes, and predicting next month's hourly foot traffic from two years of historical hourly counts. (Select TWO.) Which two features are computer vision workloads?
A marketing team wants a tool that takes a one-paragraph creative brief describing a new product and produces several original draft variations of ad copy in different tones for the team to choose from and edit. Which type of AI workload does this capability represent?