Automation is everywhere as businesses leverage software, algorithms and artificial intelligence to streamline everything from billing and customer service to data analysis and marketing. While automation promises efficiency, accuracy and scale, it does not necessarily understand how to abide with the law. When systems are left unchecked, what may start as well-intentioned optimization can quickly escalate to regulatory enforcement, class action lawsuits and serious reputational damage. In short, if a company’s software can automatically execute tasks, it can also expose the business to significant liability.
Data Privacy Minefield
Privacy compliance is one of the most challenging areas for businesses deploying automation. Laws like the California Consumer Privacy Act (CCPA), the California Privacy Rights Act (CPRA), and the European Union’s General Data Protection Regulation (GDPR) create strict requirements around data collection, notice, consent and the right to opt-out. But automation often introduces invisible data flows. Many systems pull in user data, sync it with marketing platforms, and activate retargeting or recommendation engines—all without human intervention. That is where the risk lies.
For example, In 2022, the California Attorney General settled with Sephora for $1.2 million over claims that the company failed to honor consumer opt-outs regarding third-party data tracking. The issue was not a deliberate policy failure. Sephora’s automated advertising infrastructure did not recognize or process global privacy control signals sent by users’ browsers.
In other words, automated systems can work as designed, just not always in accordance with the law. Even passive or background data collection can trigger enforcement actions if it lacks legal oversight. Companies must ensure their automated processes follow internal marketing objectives and comply with external privacy laws.
No Intent Required
Another challenge is consumer protection laws, which can frequently intersect with automated processes. Some of the most impactful consumer protection statutes, such as California’s Unfair Competition Law (UCL) and the Federal Trade Commission Act, do not require proof that a company meant to do anything wrong. Instead, they look at the outcome of the organization’s actions. This distinction matters enormously in the age of automation.
In one example, fertility and menstrual cycle tracking app Flo Health publicly assured users that their sensitive health data would remain private. In truth, however, its automated data-sharing functions routed personal data to third-party platforms like Facebook and Google for analytics and marketing purposes.
That data sharing resulted in a 2021 FTC investigation and enforcement action. Flo Health agreed to change its practices and underwent an independent privacy review, but not before facing a public relations firestorm and a major loss of trust. Even though no executive at Flo Health intended to violate user privacy, the automated system's processes did so anyway, and under the law, that was enough.
As this example demonstrates, automation does not eliminate risk. In fact, it can amplify it. When one piece of code operates outside of human oversight, it can instantly impact thousands or even millions of users and create liability for a company.
Contracts, Algorithms and Broken Promises
Automation can also create trouble with contracts, consumer rights and fiduciary duties. For example, dynamic pricing, automatic billing and AI-driven customer service can all affect users’ legal rights, even if the company deploying an automated system never intended to overcharge, mislead or confuse anyone.
For example, in the ongoing litigation Spencer v. Uber Technologies Inc, plaintiffs allege that Uber’s use of algorithmic pricing—software that adjusts rates based on real-time demand—constitutes unfair business practices and potentially violates contractual duties to customers.
Whether or not Uber prevails, the lawsuit spotlights a growing issue. Courts are increasingly open to the argument that automated conduct can stand in for human decision-making and be judged accordingly.
If a company’s system automatically sends cancellation notices, revises pricing or changes account terms without human review, it may inadvertently breach a contract or trigger consumer protection liability. The exposure from those actions can be extreme. What would be one customer service error with a human agent becomes a thousand errors when an algorithm is operating at speed.
What Businesses Can Do
To address these liability concerns, it is critical for businesses to embed legal oversight from the very beginning instead of waiting for problems to arise. Lawyers who understand the regulatory landscape and the company’s operational goals can help mitigate risk before code is ever deployed.
However, early involvement may not be enough. Automation evolves quickly, and so does the legal environment surrounding it. That is why legal supervision should be continuous. Businesses need legal advisors to proactively monitor how systems perform in the wild, especially in a tech-driven era where privacy regulations and consumer protection standards are in constant flux.
This is particularly true for any company that collects or processes consumer data, uses automated messaging or pricing systems, or operates across jurisdictions with varying consumer protection laws. For companies that fit into these categories, the following are best practices for dealing with the legal complications of automated software integration:
- Embed Legal in the Design Process: Build cross-functional teams from the start. When lawyers sit alongside engineers, systems are smarter and safer.
- Perform Privacy Impact Assessments: Evaluate how data is collected, stored and shared across automated tools. Organizations should not assume vendor compliance—they need to verify it.
- Simulate Scenarios: Test how automated systems behave under edge cases, such as customer cancellations, opt-outs or sensitive complaints.
- Audit Regularly: Companies should never “set it and forget it” when it comes to automation. Ongoing monitoring can catch errors before they scale.
- Bridge the Gap Between Legal and Technical Teams: Engineers need to understand legal constraints, and lawyers need a working grasp of how company systems function. As automation becomes more integral to business operations, legal awareness must become embedded in every line of code and every algorithmic decision.