A-Level Business
2027 Predicted Essays
& A* Model Answers

Plan - Define AI adoption, competitiveness and “disruption”; note that the question sets a long-run benefit against a short-run cost. - Case for: lower unit costs and faster service, so a cost or differentiation advantage (Porter). ONS data shows adoption is rising fast. - Counter: if every rival adopts, AI becomes a cost of staying in the market, not an advantage (resource-based view). - Workforce: ONS shows few firms cutting headcount so far; the disruption is reskilling and job redesign, which Lewin and Kotter help manage. - Evaluate: depends on type of service, depth of adoption, and whether the firm invests in training. - Judgement: AI improves competitiveness more than it disrupts, but only for firms that pair it with training and use it to do something rivals cannot copy.

The answer (≈1,030 words incl. examiner notes)

Introduction [AO1] Artificial intelligence (AI) means software that performs tasks that normally need human judgement, such as writing text, answering customers or spotting patterns in data. Competitiveness is a firm’s ability to win customers profitably against rivals, through lower costs or a better offer. Workforce disruption covers job losses, changed roles, retraining and lower morale. The question sets a long-term gain against what is mostly a short-term cost. So the answer turns on whether the gain lasts and whether the cost can be managed.

Paragraph 1: AI can lower costs and lift service quality [AO1/AO2/AO3] AI is spreading quickly through UK firms. The ONS (Office for National Statistics) found that around 35% of businesses with 10 or more employees used at least one AI technology in June 2026, up from around 12% in autumn 2023 [1]. By September 2026 the figure was 38% [2]. Use is highest in information and communication, at 58% [1].

For a service firm, labour is usually the largest cost. If AI drafts routine documents or answers simple customer queries, the same staff can handle more work. So the cost per client falls. This supports a cost-leadership position in Porter’s generic strategies. The firm can cut prices or keep prices and widen its margin. AI can also support differentiation. Faster replies and 24-hour service raise customer satisfaction, so retention rises and revenue becomes more predictable.

Examiner note: this is a full chain: AI → more output per worker → lower unit cost → pricing choice → market share or margin. Each step is joined with “so”. That is what lifts AO3 out of the middle band.

Paragraph 2: but an advantage everyone can buy is not an advantage [AO3/AO4] The question says “long-term”. Here the case is weaker. Most AI tools are bought off the shelf. If a rival can buy the same tool next month, any cost saving is quickly competed away. The resource-based view of strategy says a lasting advantage must be hard to copy. AI that anyone can rent does not meet that test. So, for many service firms, AI becomes a “cost of entry”: they must adopt it to avoid falling behind, not to get ahead.

The ONS data also shows that adoption is wide but shallow. The average adopting business used about 1.6 AI technologies in June 2026, and only 10% reported extensive use [1]. Shallow use rarely changes a firm’s cost base enough to change its market position. So the competitive gain so far is more likely to come from small time savings than from a new business model.

Examiner note: evaluating the wording of the question (“long-term”) is a top-band habit. It shows the student is answering this question, not a general AI essay.

Paragraph 3: the workforce disruption is smaller, and different, from the headlines [AO2/AO3] Many students assume AI means mass redundancy. The current evidence does not support that. Among UK businesses using AI to improve operations, 63% reported no change in headcount, 6% a decrease and 1% an increase [1]. Around 10% reported automating or replacing roles with AI [1]. Administrative and clerical roles are the most affected, reported by 38% of AI-using firms with 10 or more employees in September 2026 [2].

So the main disruption is job redesign, not job loss. Staff must learn new tools and some tasks disappear. This can still hurt motivation. Using Herzberg, job security is a hygiene factor: if staff fear for their jobs, dissatisfaction rises and productivity can fall. Yet AI can also remove dull tasks and add more responsible work, which Herzberg treats as a motivator. Which effect wins depends on how managers handle the change.

Paragraph 4: change management decides the outcome [AO3/AO4] Lewin’s force field analysis helps here. Driving forces include cost pressure and customer demand for faster service. Restraining forces include fear, lack of skills and cost. The ONS found that only 11% of businesses with 10 or more employees had trained more than half their workforce on AI [1]. That is a large restraining force. A firm that invests in training lowers resistance and gets more value from the tool. A firm that installs software and cuts staff may save money in year one, but it risks losing the know-how that made its service good.

Kotter’s model points the same way: communicate a clear reason for change, then show early wins. In a law or accountancy practice, for example, an early win might be AI-drafted first versions that staff then check. This is illustrative, but it shows staff that the tool makes their job easier, not redundant.

Examiner note: using a change model to evaluate, not just describe, is the step most scripts miss. The model is used to explain why outcomes differ between firms.

Paragraph 5: it depends on the type of service [AO4] The balance changes with the service. In high-volume, standardised services such as call centres or claims handling, AI can replace a large share of tasks. The cost gain is big, but so is the disruption. In personal, judgement-based services such as healthcare, teaching or advisory work, clients pay for trust. AI supports staff rather than replacing them. So the disruption is smaller, but so is the cost gain. The strongest competitive case is where a firm combines AI with its own data or expertise that rivals do not have. That is hard to copy, so the advantage can last.

Judgement [AO4] On balance, adopting AI is more likely to improve a UK service firm’s long-term competitiveness than to disrupt its workforce, but the gain is not automatic. Current ONS evidence shows modest job losses so far, so the disruption is mainly reskilling, which can be managed. The competitive gain is less certain than it looks, because off-the-shelf tools are easy for rivals to copy. The judgement therefore depends on three things: how deeply the firm uses AI, whether it trains staff so they work with the tools, and whether it uses AI to build something rivals cannot buy. A firm that meets all three gains a lasting edge. A firm that adopts AI only to cut staff gets a short-lived saving and a demotivated workforce.

Suggested diagram: Lewin force field: driving forces (cost pressure, customer demand for speed, rival adoption) against restraining forces (skills gap, job fears, cost of tools, data risks). Annotate which forces training reduces.

A* differentiators - Dated ONS figures, used to test a claim rather than decorate it. - Evaluates “long-term” directly: an advantage anyone can buy does not last. - Separates job loss from job redesign, with evidence. - Uses Lewin or Kotter to explain why results differ between firms. - Judgement names three conditions, not “it depends”.

Sources

1. ONS, Artificial intelligence in UK businesses: 2023 to 2026, 20 July 2026 (BICS data, 15–28 June 2026). https://www.ons.gov.uk/businessindustryandtrade/business/businessservices/articles/artificialintelligenceinukbusinesses/2023to2026
2. ONS, Business insights and impact on the UK economy: 8 October 2026 (BICS wave 165, September 2026). https://www.ons.gov.uk/businessindustryandtrade/business/businessservices/bulletins/businessinsightsandimpactontheukeconomy/8october2026/pdf