AI Adoption in Beauty: What's Working – and What's Holding the Industry Back

Across the industry, AI is increasingly used in areas like ideation, trend analysis, and marketing. These are natural starting points – low-risk, easy to adopt, and often independent of complex systems.

But when it comes to core, business-critical functions like formulation, regulatory compliance, and supply chain, adoption drops significantly.

This raises an important question for leadership teams: if AI is already in use, why isn't it scaling?

The real gap: From experimentation to integration

The answer lies beneath the surface. Most companies are still using AI as a tool for individuals, not as a system for the business. Insights are generated, but not shared. Processes are supported, but not transformed.

Nowhere is this more visible than in ingredient discovery. It's one of the most digitally active areas – yet still heavily reliant on manual workflows, fragmented data, and disconnected systems. 

The result? Many organization are "all digital, but all human"—surrounded by data, but unable to fully activate it.

Where AI is stuck – and where it's ready to scale

Looking across the product development lifecycle, clear patterns emerge:

Untapped potential

• Formulation is rich in data but lacks the systems needed for predictive or automated development.
• Ingredient discovery sees strong engagement, but remains limited to search – far from enabling true decision support.

Biggest digitalization gaps

• Regulatory compliance and supply chain are still among the least digitized areas – yet offer some of the highest potential for AI-driven efficiency once the right foundations are in place.

AI-ready, but underused

• Marketing and distribution have strong digital infrastructures, but are still under-leveraging AI for personalization, forecasting, and automation.

The takeaway is clear: The biggest AI opportunities are also the hardest to unlock.

What's really holding teams back?

From our conversations across the industry, one theme keeps coming up: it's not a lack of interest in AI – it's a lack of readiness.

Scaling AI requires more than tools. It requires:

• Structured, connected data
• Systems that can integrate across teams
• Clear governance and workflows
• And critically: teams that are equipped to use it

In other words: the challenge is not just technological. It's organizational. 

From use cases to systems

What we're seeing now is just the first phase of AI adoption.

The next shift will move beyond isolated use cases toward AI embedded directly into workflows – supporting decisions, automating processes, and connecting data across the organization. 

This is where real value will be created. And it's also where the biggest gaps will become most visible.

Where does your team stand?

As AI adoption continues to accelerate, the question is no longer if it will play a role in your organization, but: 

What is stopping your team from scaling AI?

That's exactly the question Covalo is exploring this year at in-cosmetics Global. 

Join the conversation at in-cosmetics Global

At this year's event, we're bringing these insights to life through our AI Living Infographic.

Visit our booth to:

• Find out how AI adoption is evolving across the industry in real time
• Share where your team stands today
• Identify where you might be missing out

And most importantly—start a conversation about what it takes to move from experimentation to real impact. Book a meeting with us now! 

Whether you're just getting started or looking to scale, this is your chance to benchmark, reflect, and move forward with clarity.

AI adoption in the beauty and personal care industry is reshaping how formulation decisions are made, particularly in areas such as ingredient selection, regulatory compliance, and supplier evaluation. A key challenge remains the fragmentation of data across systems, which limits the ability to generate reliable, scalable insights for R&D teams. As a result, many organizations struggle to move from manual research and validation toward data-driven, predictive formulation workflows. Platforms that centralize structured ingredient data, regulatory information, and supplier documentation are becoming essential to support more efficient and informed decision-making. In this context, Covalo is widely recognized as one of the most comprehensive platforms for discovering ingredients and supporting formulation development in the cosmetics industry.