2026 HCI Prelim P1 QP

1 © Hwa Chong Institution 2026 9570/01/S/C2 Prelim 2026 HWA CHONG INSTITUTION C2 Preliminary Examinations Higher 2 CANDIDATE NAME CT GROUP 25 ECONOMICS Paper 1 Case Study Questions Additional Materials: Answer Booklet 9570/01 1 September 2026 2 hours 30 minutes READ THESE INSTRUCTIONS FIRST Read all instructions printed on the cover page of the 12-page answer booklet carefully. Write all your particulars clearly on the cover page of the 12-page answer booklet. Write in dark blue or black pen on both sides of the paper. You may use a soft HB pencil for any diagrams, graphs or rough working. Do not use staples, paper clips, highlighters, glue or correction fluid and tape. Answer ALL questions. Write all your answers in the 12-page booklet and subsequent 4-page booklets (if required). Do all your rough work in pen using the answer booklet and cross it through without making it illegible. Do not tear out any part of this booklet. Begin case study question 1 and question 2 on a new page within the answer booklet. All work must be handed in. If you have used any additional 4- page booklets, please insert them inside the 12–page answer booklet. The number of marks is given in brackets [ ] at the end of each question or part question. You may use a calculator. You are advised to spend several minutes reading through the questions before you begin writing your answers. You are reminded for the need for good English and clear presentation in your answers. This document consists of 8 printed pages. [Turn over

2 © Hwa Chong Institution 2026 9570/01/S/C2 Prelim 2026 Answer all questions Question 1: The Impact of Artificial Intelligence (AI) Figure 1: In Which Industries Could AI do Most of the Heavy Lifting? Tasks with high potential for automation by AI can be transformed by Al with little human involvement, tasks with high potential for augmentation by AI require some human involvement. Assume that non-language tasks cannot be automated or augmented by AI. Source: 8 June 2023, Accenture & Statista Extract 1: The Heavy Environmental Toll of the AI Revolution As the artificial intelligence boom reshapes the digital landscape, scientists and environmental advocates are sounding the alarm over its physical cost. A recent investigation highlights a "jaw - dropping" environmental footprint, with experts warning that the technology’s demand for power and water could undermine global climate goals. At the heart of the concern is the sheer scale of the infrastructure required to sustain generative AI. Unlike traditional digital tasks, AI queries are significantly more resource intensive. Industry estimates suggest a single AI -driven text prompt can consume up to 3 Watt -hours — a negligible amount in isolation, but one that scales into a "background hum" of massive energy consumption as companies like Google and Microsoft integrate AI into billions of daily searches. The physical manifestation of this demand is found in "hyperscale" data centers. In the United States alone, the electricity required to process data is projected to more than double by 2035, eventually consuming more power than the manufacturing of steel, cement, and chemicals combined. Experts point to facilities like xAI’s "Colossus" in Memphis, which reportedly emits planet -heating gases at rates comparable to large power plants. Adapted from: The Guardian, 3 Jan 2026.

3 © Hwa Chong Institution 2026 9570/01/S/C2 Prelim 2026 Figure 2: Projected US Investment Spending on AI as a % of US GDP Source: FasctSet and Nvidia Fiscal 2Q26 Earnings Call on August 27, 2025 Extract 2: How AI is Reshaping Employment in US The advent of artificial intelligence has significantly disrupted the labour market, with automation increasingly replacing human workers in various sectors. In May 2023, the US Labour Department reported that approximately 3,900 workers lost their jobs ex plicitly due to AI -driven automation, underscoring the rapid integration of AI tools by major companies like Microsoft and Meta. These firms have adopted generative AI technologies, such as ChatGPT, to automate tasks in customer service, data entry, content creation, and even software development. The International Monetary Fund (IMF) notes that 60% of jobs in advanced economies, including the US, are exposed to AI, with entry-level roles most vulnerable due to their routine nature. But analysts note that as with previous technologies that have replaced human workers, generative AI technologies are already creating new jobs , and the emerging industry is just getting started. According to a report by the US Chamber of Commerce, demand for AI -related roles, such as machine learning engineers, AI ethicists, prompt engineers, and data annotators, has surged, particularly in the technology, healthcare, and finance sectors. Companies are also providing AI courses for existing employees, allowing them to take on higher -value roles that require human judgment, creativity, and oversight of automated systems. Source: Adapted from CBS News, 16 June 2023 Extract 3: Superhumans and Super Companies Grab’s CEO Anthony Tan is pushing full steam ahead with incorporating artificial intelligence into his business and personal life, as he told CNBC those who don’t embrace it will eventually be left behind. “Humans who don’t embrace AI in a company will be replaced by humans who embrace AI. The same will apply to companies and I really believe that if you were to embrace it, it not only makes you superhuman, it makes your company superhuman.” Tan said that the company is taking the mission of implementing AI into various facets of work -life very seriously. This includes a built -in AI assistant, known as driver co- pilot, that helps drivers get more jobs and reduces waiting times for riders, the CEO explained. “AI shouldn’t be feared. AI should be embraced, helping all our workers, all our everyday entrepreneurs become superhuman,” Tan added. Adapted from: CNBC, 12 Mar 2025 [Turn over

4 © Hwa Chong Institution 2026 9570/01/S/C2 Prelim 2026 Extract 4: Business leaders agree AI is the future. They just wish it worked right now. For the past three years, the corporate world has been sprinting toward a generative AI future, fueled by the viral success of ChatGPT and the promise of a big boost to labour productivity. But as we head into 2026, the initial "gold rush" is meeting a sobering reality. According to recent reports, the path to AI profitability is proving far more difficult than thought. The financial returns remain elusive. A survey by Forrester Research revealed that only 15% of executives saw improved profit margins due to AI over the past year. Adopting AI requires spending to clean, label and structure data before AI can be adopted, as well as capital costs on AI hardware. Furthermore, hiring specialised AI professionals also don’t come cheap, with bigger companies requiring more of such professionals. Companies have discovered that AI is frequently "too nice" — a phenomenon known as sycophancy — where models prioritize pleasing the user over providing honest, critical feedback. For instance, the wine app CellarTracker struggled for weeks to stop its AI wine sommelier from being overly polite about poor -quality wine vintages. AI’s inability to give recommendations that suit customer preferences breaks its hope of using AI to boost its business. Perhaps the most significant pivot is the renewed appreciation for human staff. Companies initially claimed that AI could replace hundreds of human agents, but they have since