AI and the UK Cosmetics Industry: Is Its Value More Than Skin Deep?

In 2017, the UK cosmetics industry reached an impressive £9.8 billion in value. Although it has since declined slightly to £8.49 billion, it remains strong. This downturn stemmed from the impact of COVID-19, coupled with Brexit’s effects on trade with the EU—a significant supplier and customer. The UK imports around £4.5 billion in cosmetics and toiletries from the EU, while exports, valued at £5.3 billion, go primarily to Europe.

As one of Europe’s leading cosmetics consumers, the UK also has a history of innovation, especially in tech integration. For example, Rihanna’s 2017 launch of Fenty Beauty challenged industry norms by offering 40 foundation shades, inspiring brands like Estée Lauder, L’Oréal, and Simple to embrace inclusivity and diversity. Today, “beauty tech” is flourishing, blending cosmetics with tech-driven tools like L’Oréal’s Perso (a personalised skincare device) and spray-on dresses showcased by celebrities like Bella Hadid.

At the forefront of this innovation is artificial intelligence (AI), which leverages digital tools to deliver increasingly tailored user experiences. The UK now boasts over 400 cosmetics firms offering digital services, collectively raising over £1 billion in equity investments over the past decade. Start-ups like Dcypher (2014), Klira (2021), and Skin+Me (2018) exemplify this trend, using AI to develop personalised skincare solutions based on customer-specific data.

While the future looks promising, there are also challenges ahead. Some potential downsides of AI include:

• Job Displacement: Automation through AI could lead to job losses in manufacturing and customer service roles, affecting positions involving routine tasks.
• Privacy Concerns: AI often relies on large data sets to improve algorithms, which may involve collecting personal data. This raises privacy concerns, especially given data protection laws like GDPR.
• Algorithm Bias: AI can sometimes reflect biases found in training data, leading to inequitable outcomes. In cosmetics, this could mean limited product recommendations for certain demographic groups.
• Consumer Trust: If AI seems intrusive or manipulative, consumers may lose trust in the brand, which could harm a company’s reputation.
• Environmental Impact: AI’s data processing demands high energy use and substantial water resources to cool data centres. This adds a hidden environmental cost to AI applications in the cosmetics industry.
• Regulatory Challenges: As AI grows, so do regulatory requirements. Companies must ensure compliance with new rules around product safety, advertising claims, and data use.

Bias in Algorithms

Algorithm bias deserves particular attention. Recent cases, such as Amazon’s biased hiring algorithms and COMPAS’s racial profiling in predictive policing, illustrate how biases embedded in AI can lead to negative consequences. In finance, a UC Berkeley study revealed that algorithmic bias in lending led to higher interest rates for Latino and African American borrowers, collectively costing them $765 million annually. Companies have an ethical duty to prevent such biases, as they can erode trust and perpetuate inequality.

The Job Displacement Debate

Job displacement is another concern often raised with AI. While it may disrupt current roles, historical trends suggest that new technology typically creates new job opportunities. Computers, once feared for their potential to replace jobs, ultimately generated countless new roles in tech, logistics, and customer service. AI could follow a similar path, enabling workers to shift to more creative or strategic roles over time.

Environmental Concerns and ESG

AI’s environmental footprint is a growing concern. High energy consumption and significant water use are required to power and cool data servers. As water scarcity intensifies, these demands will need to be balanced with environmental responsibility. With the rise of ESG (Environmental, Social, and Governance) frameworks, customers and partners are increasingly choosing to work with businesses that prioritise sustainability. Ignoring AI’s environmental impacts may damage reputations, as companies that neglect ESG commitments risk losing trust and customer loyalty.

Levelling the Playing Field for SMEs

AI may also create a divide between larger and smaller companies. Large corporations have the resources to invest heavily in AI, whereas smaller businesses might struggle to keep up. Limited access to AI could reduce competitiveness and contribute to reputational risks if biased AI systems are deployed without proper oversight. Ensuring access to responsible AI technology across the industry can help address these disparities.

A Call for AI Standards and Regulation

Given AI’s broad reach, companies must uphold high standards for ethical AI use, covering areas like data privacy, algorithm testing, and environmental impacts. The lessons from internet and social media regulations—often introduced too late—highlight the importance of acting proactively. To avoid repeating those missteps, we need strong regulatory frameworks now, such as the EU’s pending AI Act. Acting early will support responsible AI development and benefit both the cosmetics industry and consumers alike.

AI’s role in the UK cosmetics industry is transformative, promising personalised products and efficient processes. However, it is crucial for companies to navigate these benefits responsibly, ensuring that AI enhances rather than undermines trust, equity, and sustainability.