Retailers prioritize customer experience (72%) and revenue impact (71%) as their primary indicators of success.
Key takeaways
- Trust is the ultimate currency in AI scaling. Fragmented data and inconsistent AI outputs create massive reputation risks that can lead to immediate customer churn. Retailers are resolving this by prioritizing established, low-friction use cases to build fluency before moving to high-stakes interactions.
- Performance consistency dictates global success. Delivering AI at a global scale is difficult due to latency and regional reliability issues; teams are adopting cloud native platforms and edge providers to ensure a seamless, high-speed user experience across all geographies.
- Operational silos hinder AI ROI. Limited internal expertise and legacy systems often stall deployment; retailers are overcoming these resource constraints by leveraging strategic partnerships with specialty AI providers and global systems integrators to bridge the talent gap.
- Proactive governance is a prerequisite for deployment. Security and regulatory concerns often act as a bottleneck for innovation; by establishing visibility into data flows and API behavior early, organizations can scale their AI applications without compromising compliance or brand integrity.
- Strategic alignment prevents resource exhaustion. Implementing AI without defined goals leads to “flying the plane as it’s built” with no clear direction; retailers are focusing on measurable outcomes like revenue impact and customer experience to gain organizational buy-in and focus efforts.
Frequently Asked Questions (FAQ)
The most common applications include automated customer Q&A (82%), visual product search (77%), and personalized recommendations (74%).
Security is cited as the leading challenge by 65% of respondents, followed closely by compliance and regulatory requirements at 52%.
Retailers are leaning on external partners, specifically public cloud platforms (58%), specialty AI providers, and global systems integrators to fill infrastructure and talent gaps.
Edge partners are essential for enabling the low-latency experiences required for real-time interactions, such as search, assistance, and recommendations.
Approximately 57% of retailers expect their customer-facing AI strategies to function at a global scale in the long term.
Nearly half (48%) of retailers are concerned that inaccurate or mishandled AI outputs will lead to a loss of customer trust, harm to brand reputation, and increased churn.
Retailers should adopt a phased deployment model, starting with proven, low-friction applications to validate performance before expanding globally or into complex workflows.