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Software is eating the world and now it has recently begun smelling it as well. The fragrance industry is starting to go through deep.

Software is eating the world and now it has recently begun smelling it as well. The fragrance industry is starting to go through deep digital transformation processes that address its core competencies, and naturally so, is thus very affected by artificial intelligence (AI). In contrast to information-based industries such as finance and insurance, fragrance took longer to undergo digital transformation because entry barriers for startups and innovation, in general, are higher. CapEx (capital expenditures) involving chemical compounds and labs, together with higher OpEx (operational expenditure) for interdisciplinary talent, make it less susceptible to disruption.

Fragrance is more difficult to digitize because there is less academic applied olfaction research work offering technologies ripe for commercialization; and because olfactory nomenclature is limited and less articulated than other senses. The latter not only creates difficulties in generating data sets for AI but also makes it challenging to have AI talent reach the profound subject matter understanding that is so necessary to develop adequate solutions. In addition, the widely common (and justified) perception of perfumery as an art and craft creates a basic distrust for AI solutions in fragrance.

AI in Fragrance

Nonetheless, AI is beginning to penetrate fragrance. Similarly to other industries, it started from applications that are not unique to fragrance, such as analyzing consumer behavior as recorded in e-commerce transactions and social media for the purpose of creating fragrance products that sell better. But also recent years innovations in machine learning, bioinformatics, and drug discovery have posed an opportunity to develop AI models that touch the core of fragrance design and formulation and can actually make computers sense and articulate olfactory perception. Publicity of such innovation made stakeholders in fragrance more open to risk resources for progress. The integration of AI in core fragrance capabilities manifests in several types of applications: formula-to-brief recommendation, formulation, sensing, and new molecule design. The formula to-brief recommendation is the ability to match existing fragrance formulas to new briefs. It enables fragrance houses to match formulas out of their 50,000+ formula portfolios to new customer briefs that could benefit existing non-exclusive formulas and enable fragrance houses to continue monetizing them.

Originally published on Perfumer & Flavorist

By Adam Shahaf, VP Business Development, Moodify

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