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Consumers Use AI Assistants but Hesitate to Hand Over Their Wallets

Trusted payments are the key to consumers’ willingness to participate in agentic commerce, Visa said in a Wednesday (Sept. 9) press release. Visa’s research found that 72% of consumers have used an artificial intelligence assistant, but only 23% of U.S. consumers in the United States trust generative AI to handle payments on their behalf, according […] The post Consumers Use AI Assistants but…

Consumers Use AI Assistants but Hesitate to Hand Over Their Wallets

Consumers have embraced AI assistants for shopping and payments, but their trust in letting these agents handle the financial transaction is still limited. Visa's research shows that while 72% of U.S. consumers have used AI assistants, only 23% trust generative AI with their payments. However, when consumers see familiar payment brands involved, their confidence in AI-assisted purchasing increases.

For instance, 61% of consumers would trust Visa to handle such transactions. Trust is crucial for the widespread adoption of agentic commerce, according to Oliver Jenkyn, Visa's group president. "While we're still in the early days, trust will be foundational to driving agentic commerce adoption," he said. PYMNTS Intelligence report revealed that consumers have varying levels of trust in AI agents performing different tasks.

While 56% are comfortable with agents searching and comparing products, and 51% are okay with agents managing loyalty programs, only 35% are willing to let agents access their saved payment credentials. However, most consumers are open to letting agents make purchases if proper safeguards are in place. Another PYMNTS report from January found that while consumers are excited about AI-native commerce, their trust remains firmly rooted in traditional payment credentials and credit card networks.

Visa's executives stated that they are focusing their strategy on becoming the link between AI-driven commerce and the trust it needs to succeed.

Written by urgent.news from PYMNTS's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Read the original at pymnts.com →

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