How Businesses Are Managing AI Agents on Their Platforms

Adsroid Blog
This article examines how companies like Walmart, Chase, and Bank of America respond to AI agents acting on behalf of customers, highlighting strategies from blocking to dedicated agent profiles.

Summarize with AI

Connect Claude to your Ad Accounts in less than 5mn

Discover the most powerful advertising MCP and unlock 220+ tools to analyze, optimize and manage your campaigns with AI.

AI agents acting on behalf of users are becoming more common, influencing how businesses must adapt their digital platforms. These agents can perform tasks like shopping, booking, or managing accounts, raising unique challenges around identity, security, and trust.

Current Business Approaches to AI Agent Access

Businesses are adopting different policies for letting AI agents interact with their systems. JPMorgan Chase has chosen a restrictive approach, blocking access to prevent unauthorized agent activity, as CEO Jamie Dimon indicated during a recent earnings call. Other companies like Charles Schwab and Delta Airlines are similarly cautious, restricting AI agents to protect user data and system integrity.

Conversely, Bank of America has positioned the responsibility on customers, advising them against sharing login credentials with AI agents but warning that any activity through shared access is the customer’s accountability. This approach highlights the risks users face when granting AI agents direct access without safeguards.

Walmart is pioneering a more nuanced solution with its introduction of Agent Profiles, a dedicated framework within customer accounts that allows AI agents to act on the customer’s behalf under regulated conditions. By giving each AI agent a separate profile, Walmart ensures transparency and control over agent activities, differentiating between the user’s direct actions and those performed by AI.

The Significance of Separate Agent Profiles

With separate profiles, businesses can track and manage AI agent behavior distinctly from the human user. Walmart’s system enables setting spending limits and requires approval for purchases, mitigating risks of unwanted transactions. Agents also receive the same pricing information as customers, maintaining fairness and consistency.

This model recognizes the unique nature of AI agents who may browse many more pages or make decisions the human user might not consider, all while acting with the user’s authority. Differentiating agents from users supports better analytics, fraud prevention, and customer experience.

Technical and Security Considerations

AI agents generally operate by signing in with a customer’s credentials, which raises concerns about identity verification and authorization. Emerging specifications, such as the Personal Agent Protocol currently in development by over 40 companies including Meta, aim to standardize how AI agents identify themselves to platforms.

This protocol recommends agents use methods like Web Bot Authentication to prove which organization powers them, allowing businesses to validate and monitor agent activity. Some AI agents, like Meta’s Muse, have already started signing requests with such identities without public announcement.

Security vendors and website operators must evaluate their infrastructure’s ability to distinguish AI agents from humans. Automated bot defenses might inadvertently block beneficial AI traffic or let malicious agents slip through. Preparing systems for agent-aware access controls is critical as agent usage scales.

Industry Impact and User Perspectives

Companies like DoorDash have reported only a few hundred AI agent orders so far within hundreds of millions of total transactions, suggesting that large-scale AI agent adoption is still in its early phases. This window allows businesses to design policies before AI agents become mainstream online users.

“Businesses that proactively implement agent-aware systems will establish trust and competitive advantage as AI agents proliferate,” stated a cybersecurity analyst at a leading consultancy.

The ability to control agent actions through profiles or spending limits may become essential for protecting customers and platforms alike. Customers also benefit from clear visibility on what their AI agents are authorized to do, reinforcing trust in these new digital helpers.

Balancing User Convenience and Security

The challenge lies in enabling AI agents to efficiently perform tasks without compromising security or user control. Systems like 1Password for Agents demonstrate how password managers can securely relay login information without exposing credentials to AI agents, further enhancing protection.

Adopting agent profiles or authentication protocols can mitigate risks associated with account sharing or unauthorized access, providing a more scalable framework than outright blocking agents.

For businesses unsure of the best approach, it is advisable to conduct thorough assessments of their bot management policies and prepare to create agent-specific access controls tailored to their operational and customer needs.

Get Alerts When Competitors Launch New Ads

Ad Radar automatically monitors your competitors across Google, Bing and Meta. Get alerted when a new ad appears for your tracked keywords, so you can spot new offers, messaging and opportunities without constantly checking.

Preparing for the AI Agent Era

Businesses must take proactive steps to adapt to AI agents. They should assess how current security and bot filtering tools interact with AI-driven traffic, which can be indistinguishable from human activity or exploit existing vulnerabilities.

Deciding on a clear policy regarding AI agents—whether blocking them, delegating responsibility to customers, or implementing agent profiles—allows businesses to maintain control and protect their customers. Monitoring and updating systems to recognize signed AI agent requests will soon become a critical operational capability.

For companies seeking to leverage AI agents for improved automation and customer engagement, integrating AI-friendly features is important. Tools that enable secure authorization and transparent tracking of AI agent activity can unlock new levels of service innovation while maintaining compliance and risk management.

Those interested in how AI agents influence paid media and ad performance can explore the diagnostic approaches to Meta ad campaigns demonstrating AI’s broader marketing impact. Additionally, businesses can learn from strategies to generate demand with measurable results using AI-based automation tools.

Turn On Copilot. Let AI Optimize Your Ads 24/7.

Your AI agent works in the background, continuously watching your campaigns and finding ways to improve them. When it spots an opportunity, it tells you what to do, and you simply approve the action.

Conclusion

The evolving presence of AI agents on digital platforms challenges traditional notions of user interaction and security. Businesses like Walmart are leading the way with innovative solutions such as separate agent profiles, balancing convenience and risk mitigation.

Others favor stricter controls or place responsibility on the user, but overall, readiness and adaptability will dictate future success. Establishing standards and protocols for agent identification, as well as improving security layers, can enable safe and efficient AI agent engagement.

For enterprises looking to stay ahead, adopting agent-aware systems and exploring automated solutions like those provided by Adsroid’s AI-powered marketing platform can facilitate integration of AI agents while safeguarding customer trust.

As AI agents increasingly shape e-commerce and digital services, businesses that understand these dynamics will be positioned to innovate and lead in the new era of agentic commerce.

Share the post

X
Facebook
LinkedIn

About the author

Picture of Danny Da Rocha - Founder of Adsroid
Danny Da Rocha - Founder of Adsroid
Danny Da Rocha is a digital marketing and automation expert with over 10 years of experience at the intersection of performance advertising, AI, and large-scale automation. He has designed and deployed advanced systems combining Google Ads, data pipelines, and AI-driven decision-making for startups, agencies, and large advertisers. His work has been recognized through multiple industry distinctions for innovation in marketing automation and AI-powered advertising systems. Danny focuses on building practical AI tools that augment human decision-making rather than replacing it.

Table of Contents

Your Google and Meta Ads on Autopilot

Let AI handle the work.

Adsroid analyzes your campaigns, finds opportunities and takes action to improve performance, while you stay in control.

Latest posts

How Reddit Reviews Collect and Analyze Community Product Feedback

Reddit Reviews aggregates user feedback on products to highlight key pros, cons, and comparisons. This guide examines how it benefits consumers and marketers despite noted trust limitations.

Why GA4 and Google Ads Conversions Don’t Match (and Which Number to Trust)

GA4 and Google Ads rarely show the same conversion numbers, and that's not a bug. This guide explains exactly why the numbers differ and which one to trust for each decision.

GA4 MCP Server: Ask Your Google Analytics Data Questions in Claude or ChatGPT

Yes, Claude and ChatGPT can read your Google Analytics data through a GA4 MCP server. Learn how specialized GA4 tools answer analytics questions in plain English without building reports.