Online shopping has become a part of daily life for millions around the world. But the process from choosing a product to payment, fraud checks, and sometimes returns, is still far from seamless. With the rise of agentic AI, a new kind of artificial intelligence designed to take autonomous actions on behalf of users, companies are pushing to automate and simplify these complex transaction lifecycles. But the big question remains: can this technology handle an entire transaction from beginning to end?
Udit Agarwal, a product manager and researcher who closely studies intelligent agents and automation trends, believes we are still a few steps away. “Agentic AI has come a long way, but we are not at the point where it can run the full lifecycle independently,” he says. Agarwal, who has worked with early-stage AI product development teams and written extensively about AI adoption in commerce, emphasizes that while AI can assist in specific phases, true end-to-end autonomy is still a work in progress.
“For instance,” he explains, “on platforms like Craigslist or Facebook Marketplace, AI has the potential to negotiate, respond to inquiries, or flag suspicious offers. That’s promising, but once you include fraud detection, payment clearance, customer communication, and returns, it becomes a much more complex chain. And that’s where agentic AI still needs supervision.”
Today’s transactions often require multiple levels of approval and trust, especially when handling sensitive data or financial actions. Agarwal points out that building trust is central to how these AI agents are adopted. “Nobody wants an AI agent making blind decisions with their money,” he says. “Users want control. They want to step in if something feels off. So, the real challenge is designing an AI Agent that feels like an assistant, not a risk.”
Agentic AI shines when it comes to automating repetitive tasks, things like filling out forms, verifying addresses, or tracking deliveries. “It’s not just about doing things faster,” says Agarwal, “It’s about removing the small frictions in online commerce. If AI can take care of the dull, time-consuming parts, customers and sellers can focus on what actually matters—value and experience.”
In addition to automation, agentic AI could also play a more predictive role. These systems can help flag potential issues before they become problems, like identifying mismatched payment details or risky behavior that suggests fraud. “Proactive AI is where a lot of exciting work is happening,” the professional adds. “Imagine your shopping agent warning you, ‘Hey, this seller has a pattern of late shipments,’ before you even hit buy. That’s real value.”
Tech giants like OpenAI and Perplexity are already exploring this direction. OpenAI, for example, recently introduced a feature allowing users to shop within ChatGPT’s interface, demonstrating how integrated and conversational commerce might look in the near future. However, these AI agents still face resistance from existing fraud detection systems, CAPTCHA challenges, and bot filters that are designed to stop automation, not work with it.
For now, the technology still needs to be paired with human oversight. “Think of it like co-piloting,” suggests the expert. “The AI can handle a lot of the dashboard, but the human still needs to be in the loop, at least until the system proves itself over time.”
So, can agentic AI manage the entire customer transaction lifecycle right now? Not quite. But progress is clearly underway. These digital agents are becoming more capable and more trusted with each iteration.
For shoppers and sellers alike, it means that they may not be far from a world where intelligent assistants handle purchases, process refunds, and protect users, all with minimal input. Until then, the key lies in gradual rollout and careful design. As the technology matures, online transactions are poised to become easier, faster, and more secure, with AI playing a supporting, if not yet leading, role.
