The beauty tech pioneer: How L'Oréal is transforming work inside out
In a time when enterprise technology is undergoing seismic change, L'Oréal has emerged as a global trailblazer. At the heart of its transformation is a fundamental reimagining of work, not as a sequence of digital tasks, but as an orchestrated, intelligent flow that learns, evolves, and creates value. Tejas
Shah
, CIO of L'Oréal India, is at the forefront of this journey. In a conversation with the ETCIO DeepTalks that dives deep into systems thinking, AI design, and ethical guardrails, Shah opens up about how L'Oréal is not just adopting technology, but embedding intelligence into the very fabric of its operations.
While L'Oréal leads with early adoption of enterprise AI, major competitors like Estée Lauder, Shiseido, and
Unilever
are also making bold strides in integrating intelligence into their digital strategies. Estée Lauder, for instance, has heavily invested in AR-powered beauty apps and virtual skincare diagnostics, and is deploying analytics across supply chains to better predict demand. Shiseido has focused on real-time skin data analysis and personalized skincare solutions through AI-powered consumer apps. Unilever, on the other hand, is leveraging AI not only for product personalization but also to accelerate sustainability insights through digital twins and smart factories. Each of these companies brings a different approach to the AI frontier, but what sets L'Oréal apart is its enterprise-wide orchestration, from internal collaboration to product R&D, ensuring intelligence touches every layer of the organization.
A Beauty Tech Vision: Embedding Intelligence Everywhere
L'Oréal's ambition to become the number one beauty tech company in the world wasn't just a marketing slogan. It was a pivot with purpose. In 2018, the company made a bold declaration that reshaped its investment strategy, operational philosophy, and innovation playbook. It started with a central idea: 'Beauty for each, powered by tech.' This meant serving not just consumers, but employees and the planet, through personalized, responsible, and intelligent solutions.
Beauty Tech for us means beauty for each, powered by tech. Each, refers to our consumers, our employees, and the planetTejas Shah
AI didn't enter L'Oréal's ecosystem in 2023. The company began experimenting with automation and artificial intelligence as far back as 2015. What changed post-2018 was scale and intent. With 115 years of data, the company found a unique edge, its deep knowledge base. This historical data became the training ground for a wide array of AI models that now power everything from personalized hair color recommendations to predictive sales prompts and operational insights.
This vision materializes across multiple enterprise touchpoints:
Product R&D: AI models suggest optimal formulations based on historic and real-time data.Marketing & CX: Virtual try-ons using AI/AR help customers visualize products before purchase.Supply Chain: Intelligent demand sensing ensures the right products reach the right places at the right time.Internal Productivity: With tools like L'Oréal GPT, a custom enterprise LLM, employees are summarizing documents, generating content, and enhancing decisions, responsibly.
Workflows That Think: Redefining Productivity
The use of AI at L'Oréal is not confined to one silo. In R&D, AI helps chemists simulate and test new product formulations. In marketing, virtual try-ons use augmented and virtual reality to allow users to preview products with stunning realism. In operations, intelligent demand sensing boosts forecast accuracy, while in HR and collaboration, tools like L'Oréal GPT and Microsoft Copilot automate workflows, summarize meetings, and enhance knowledge sharing.
One standout innovation is a Teams plugin developed in collaboration with Maybelline. 'Employees working across time zones can launch the plugin and instantly apply digital make-up before joining a video call,' Shah shares. 'It's a simple yet powerful example of how intelligence can be humanized.'
The transformation isn't about layering tools, it's about reimagining workflows. L'Oréal's enterprise systems now come equipped with:
Copilots across Microsoft 365 to assist with meetings, documents, and collaboration.ServiceNow's Now Assist to proactively resolve IT tickets.Maybelline's virtual plugin for Teams, a unique use of AI to enhance digital presence during meetings.
But these tools didn't emerge because traditional systems were broken. As Shah explains, L'Oréal's culture is about 'seizing what begins.' That means actively exploring emerging technologies not just to fix pain points, but to create new possibilities. Still, some longstanding challenges like siloed data, context-blind automation, and limited proactive assistance pushed the company to evolve its approach. AI, with its capacity for contextual awareness, pattern recognition, and scalability, offered a compelling path forward.
The pandemic years were another catalyst. With hybrid work, disrupted supply chains, and changing consumer expectations, the company saw the urgency of having systems that could think and adapt. Employees sought tools that were not only productive but engaging. Customers demanded personalized and green solutions. 'The shift wasn't just digital. It was cultural,' says Shah.
Every workflow, from emails to sales enablement, is becoming intelligent, connected, and more contextual,' says Shah. 'We've moved from isolated automation to systems that understand the who, what, and why behind every task.
Architecture Principles Rooted in Purpose
To anchor this transformation, L'Oréal put in place 12 global architecture principles. These include user-centricity, extended enterprise readiness, a single source of truth for data, and privacy-by-design. The company also emphasizes sustainable and secure infrastructure. 'We want to avoid tech debt. That's why governance, though sometimes seen as policing, is actually strategic foresight,' Shah explains.
Our 115-year-old dataset is a competitive edge. When we train on it, we make sure it doesn't become part of a public commons. We internalize when it mattersTejas Shah
One critical strategic choice L'Oréal made was to internalize its AI models in high-stakes use cases. For example, L'Oréal GPT is a proprietary large language model trained not only on global models like OpenAI but also on internal company data, safeguarded through enterprise-grade privacy policies. This approach ensures that L'Oréal's competitive intelligence doesn't get generalized into publicly available models.
The results have been tangible. Around 70% of employees in India now use L'Oréal GPT at least once a month. The Microsoft Copilot suite is helping summarize meetings, draft emails, and speed up documentation. Sales teams using AI-assisted recommendations have shown measurable uplift in performance. More shelf availability. Better promotion effectiveness. Higher customer satisfaction.
Measurement is key. L'Oréal defines KPIs at both the macro and micro levels. For general tools, adoption and usage rates serve as proxies for impact. For specific use cases, like AI-driven sales assistants, metrics like revenue uplift, time saved, or customer experience improvement are tracked rigorously. 'We know exactly what each AI initiative is meant to achieve,' says Shah.
Balancing Innovation, Governance & Trust
Yet with power comes responsibility. Ethical AI is a core tenet at L'Oréal. A dedicated GenAI task force oversees global strategy, while every solution passes through a design authority that vets for sustainability, data privacy, security, and ethical compliance. The company also conducts Privacy Impact Assessments and follows six pillars of responsible AI: human oversight, safety, transparency, fairness, sustainability, and accountability.
This isn't theory, it's practice. For instance, L'Oréal prohibits the use of model images in its AI-based beauty trials to avoid racial or aesthetic bias. The company also tracks the carbon footprint of its AI systems, committing to green tech as part of its innovation agenda.
'We don't use model faces in any of our AI try-ons. That's a deliberate choice to ensure diversity and prevent bias,' Shah notes. 'Ethical, explainable, and sustainable AI isn't an option, it's a responsibility.'
People at the Center: Upskilling & Change Management
To ensure successful adoption, L'Oréal invested in people as much as platforms. Mandatory learning programs such as 'Data for All,' 'AI for All,' 'Cybersecurity for All,' and 'Ethical AI' are built into onboarding and ongoing training. These programs are refreshed regularly and tracked by HR. The company also uses community-specific approaches for onboarding external users like salon partners. Stylists in top salons now use apps that scan scalp conditions and recommend personalized treatments using AI.
'Change agents, user experience managers, and empathetic communication are crucial,' Shah adds. 'There is no one-size-fits-all. Gen Z wants sleek tools, while veterans need coaching. Change management has become a serious capability.'
Looking Ahead: The Agentic AI Era
As for the future, Shah is looking at agentic AI, the next evolution where systems will not just recommend decisions but execute them. Imagine an AI that approves purchase orders within defined guardrails or auto-responds to customers with full autonomy. 'We're entering a phase where AI won't just support work. It will do the work,' he says.
'Can an AI autonomously approve a purchase order based on business context and policy? That's where we're headed,' Shah says. 'The future is self-adapting, value-generating workflows.'
The CIO's Evolving Role: From IT to Value Realization
This shift redefines the role of the CIO. 'We're not just IT partners anymore. We're value creators. It's not enough to implement a tech project. We have to ensure it delivers ROI,' says Shah. He believes CIOs should own not just execution but the outcomes, measured in terms of business impact, productivity, and user satisfaction.
Shah's closing advice to peers is to focus on three things: create value, act fast, and learn faster. 'Don't wait to perfect your use case. Pilot quickly. Fail if you must. But move forward with learning and conviction.'
At L'Oréal, the future isn't about adding more tools. It's about making work intelligent, contextual, and beautifully human.
Digital sprawl is easy. Digital intelligence is hard. But that's our responsibility, to transform isolated tools into orchestrated intelligence.Tejas Shah
(With Inputs from Aakansh Gupta)
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