Everyone is talking about AI. And when it creates measurable value…

… people talk about it even more

Artificial intelligence is discussed every day: on social media, at conferences, in white papers. But when AI produces genuinely measurable impact and a tangible economic result, in euros rather than buzzwords, the conversation moves to another level.

That is precisely what happened with the joint project between Profiter and Phoenix Pharma Italia.

AI and the pharmaceutical supply chain: a concrete case study

Over the course of a year, from June 2024 to June 2025, the two companies conducted a scientific benchmarking exercise on demand forecasting models in pharmaceutical distribution, testing the effectiveness of Profiter's AI model against Phoenix's internal forecasting system across more than 1,000 pharmaceutical lines.

The results were significant:

• Better accuracy in 64% of cases, using WMAPE as the comparison method.

• An average 7.9% reduction in logistics costs across 819 SKUs.

• Annual savings calculated by the client of more than €911,000, on a base of 28,000 SKUs.

The exercise demonstrated how predictive AI in pharmaceutical logistics can generate real economic value, through harmonised data, transparent algorithms and objective measurement.

Press coverage worth more than a thousand slides

The value of the project was recognised not only by analysts and stakeholders across the chain but also by the media. Several authoritative titles in pharmaceutical, healthcare and innovation journalism devoted articles and analysis to the case.

They approached it from different angles, confirming the broad interest — economic, strategic and operational — generated by a project aiming to bring real value to demand management and intelligent forecasting in pharma.

What the press said

• Pharmacy Scanner — "Logistics and advanced AI: a Phoenix and Profiter study that measures the difference". A leading magazine for pharmacists and supply chain managers, with a technical and managerial slant, it focused on the economic measurement of the benefits of artificial intelligence applied to logistics. The article explores the concept of the Total Cost Function and highlights the potential of dynamic pricing as a tool for optimisation in pharmaceutical distribution.

• Ifarma — "Predictive models: AI enters pharmaceutical distribution". This independent title, which looks to the future of the pharmacy, offered a reading oriented towards applied innovation, presenting the exercise as a case that could be replicated in other areas of community healthcare and underlining the concrete impact of AI on efficiency and sustainability.

• Impresa Sanità — "Optimising pharmaceutical demand forecasting with AI". The portal specialising in healthcare innovation gave space to the project's methodology, highlighting its scientific rigour and the importance of the data harmonisation protocol, with an approach that brings out the scalability and interoperability of the model in wider healthcare logistics contexts.

Coverage in other specialist titles

The Profiter-Phoenix case also drew attention beyond the main sector magazines. A number of media outlets, both specialists in digital health and technological innovation and more general titles, picked up the project, confirming its relevance in a broader sense. These included Sanità Digitale, TecnoMedicina, Unità.TV, Rassegna Business, Technoretail and Farmacia Ospedaliera.

That coverage reinforces the validation of the project from a communications perspective too.

When AI is more than a promise

At a moment when artificial intelligence is often described in abstract or speculative terms, the Profiter-Phoenix case is a concrete demonstration of the measurable value of AI in healthcare and pharmaceutical distribution.

The media coverage it received is not simply an indicator of communications success but a validation of the method and the results.

Results and recognition

Our project is not just a case study. It is a replicable best practice, demonstrating how AI-based predictive models can contribute to:

• Reducing operating costs.

• Improving stock management.

• Preventing stockouts.

• Increasing the resilience of the chain.

And when the numbers speak, the press listens. And amplifies.