Across Europe and the UK, product safety incidents are rising, regulators are tightening standards and businesses are under pressure to respond faster and more accurately than ever before. At the same time, AI is being adopted by brands at scale. As of 2025, 78% of companies worldwide report using AI in at least one business function, a marked increase on previous years and a sign of widespread operational adoption across sectors.
Despite the hugely influential prevalence of these trends, one area of operations that has yet to truly experience the AI revolution is product recalls. You don’t need to look back far to see a news report of a contaminated or faulty product and all of us who hit the supermarkets in a pre-Christmas shopping spree will have seen the paper notices taped to the walls and tills.
A shifting recall landscape and the rise of AI
Product recalls are no longer sporadic events. Indeed, recalls across the EU and UK reached thousands of individual events in 2025, keeping the year on track for new records despite slight quarterly dips. The food and drink sector alone recorded more than 1,300 recalls in one quarter, illustrating how safety issues are spreading across categories and pushing regulators and businesses to act.
What does this mean for recall management? Simply put, the scale and cadence of recalls demand smarter tools and sharper execution. Brands that fail to integrate modern technologies risk delay, inefficiency and reputational damage.
AI ready, recall ready: operational priorities for 2026
With that context in mind, here are six practical areas where AI will matter most to teams preparing for, responding to and learning from recalls in 2026.
- AI as the recall cost engine – For many large organisations, recalls represent a major financial risk. A single recall can cost millions in direct expenses before reputational damage is factored in. When AI is used to automate manual processes, manage documentation and handle incoming enquiries, it is not a luxury. It becomes a cost-control mechanism. In 2026, recall leaders will start by asking a simple question: how much of this process is being done manually, and why? AI that reduces paperwork, call volumes and data handling can cut costs dramatically. Early adopters will benchmark spending and performance against automated alternatives.
- The rise of the ‘unknown’ customer – Many recall exercises fail because too many affected customers remain unreachable. Legacy systems scatter contact details and leave gaps in the customer journey. In 2026, brands will increasingly use connected data, QR-enabled journeys and AI-driven triage to turn previously unknown buyers into reachable contacts. The competitive edge will go to organisations that use these techniques to find and notify the right people quickly, verifying that actions were taken and closing the loop with clear evidence.
- The end of the paper notice – Printed recall notices and posters are still widespread, but they are increasingly ineffective. They assume customers will notice, read and act on static information. That is no longer a tenable strategy in an always-on digital environment. From mobile alerts to dynamic web content and real-time chat responses, brands that treat recalls as customer journeys rather than bulletin board exercises will be in a stronger position. AI has a central role here, powering both reach and personalisation.
- Smarter analytics for risk prediction – AI can digest patterns from supply chains, quality control logs and regulatory data to highlight risk signals long before a recall is triggered. In 2026, we will see more organisations embed predictive analytics into their safety monitoring frameworks. This approach shifts recall management from reactive to proactive, identifying weak links before they cause harm.
- Integrating human expertise with machine speed – No matter how advanced the algorithms, humans remain essential. AI will accelerate data handling, but expert oversight will be needed to validate decisions and interpret insights. The best recall teams in 2026 will be comfortable working in hybrid environments, where machines handle scale and humans handle judgement.
- Data governance and compliance built in – As AI becomes more embedded in recall processes, compliance and traceability must be built into systems from the ground up. Organisations will need clear rules on data usage, auditing and accountability to avoid legal and ethical pitfalls. This is especially important when AI generates automated notifications or prioritises actions that have regulatory consequences.
AI will protect customers…and the bottom line
The next phase of recall readiness will be defined not by whether organisations use AI, but how they use it. In an environment where safety incidents are frequent, scrutiny is high and customer expectations continue to rise, brands that embed intelligent systems into recall operations will protect both their customers and their bottom line.
2026 will not be the year of AI hype. It will be the year AI earns its place at the heart of recall strategy.
