Could AI solve Europe’s packaging compliance problem?

In a recent commentary, Neil Smith, CPG president of Schneider Electric, stated that manufacturers need to focus on data transparency through the supply chain as Europe’s new packaging regulation takes effect this month. Beginning August 12, 2026, the EU’s Packaging and Packaging Waste Regulation (PPWR) requires every food and beverage product entering the EU market to carry a signed Declaration of Conformity, and packaging that comes into direct contact with food now needs PFAS forever chemical tracking, too.

The timing is tough. Schneider Electric research, cited by Smith, shows that compliance already costs European food and beverage manufacturers 13.7% of a product’s final price — more than labor (12.2%) or manufacturing margin (8.0%). The UK and Ireland show a similar pattern, at 12.8%.

That was already true before this summer’s heat waves cut European grain harvest prospects by roughly 9 million tons and French vegetable growers began warning of shortages. USDA now forecasts EU grain imports rising from 26.5 million to 28.4 million tons this year — meaning Europe is leaning harder on imports right as those imports face tighter compliance checks.

Smith argues the core problem is how supply chain data gets collected: mostly supplier by supplier, still largely by hand. Closing that gap into a single traceable digital thread via connected, artificial intelligence (AI)-enabled industrial data platforms is, in his view, the fix. Right now, only about a third of European food and beverage manufacturers say AI plays a significant role in PFAS or packaging compliance. The UK and Ireland lead the region, with 49.2% citing AI as significant or critical for PFAS compliance and 55.6% for packaging compliance.

In related Schneider Electric research, the 2026 Industrial AI in CPG Survey, 1,453 global executives found that manufacturing inefficiencies already cost 20.3% of final product cost, with losses expected to climb toward 29.14% by 2030. AI adoption still lags expectations — just 13% of manufacturers call AI core to operations today, versus 37% expected by 2030 — with skills gaps (43%), legacy automation (37.5%), and poor operational data (36.3%) cited as the top barriers, ahead of compliance concerns.

Smith’s takeaway: treat traceability as an investment in competitiveness, not a one-time compliance scramble. Manufacturers building that digital infrastructure now will be positioned for what’s next; those still chasing PFAS paperwork, supplier by supplier, will keep paying for it in the product’s price.