In the ever-evolving world of artificial intelligence, large language models (LLMs) like OpenAI’s ChatGPT have been heralded as game-changers for countless industries. From automating customer service to writing essays, their applications are vast and versatile. But when it comes to the critical task of validating addresses, LLMs may fall short in a potentially damaging way.
The Problem with Probabilistic Address Validation
Experts consistently caution that answers generated by LLMs may not always be accurate. This is because these models, including ChatGPT, are prone to information hallucination—the generation of false information with absolute confidence. As a result, an LLM might validate what appears to be a perfectly plausible address, complete with city, street name, and postal code. However, that address could very well be fictional.
LLMs generate responses based on probabilistic determinations: they predict the most likely sequence of words or phrases that would fit a given context. While this makes them great at producing natural-sounding sentences, it also means they lack the fundamental ability to fact-check. When a LLM “validates” an address, it’s often just guessing. For mission-critical applications like delivery logistics, compliance, and fraud prevention, guessing simply isn’t good enough.
A Real-World Test
To illustrate this, we asked ChatGPT to validate the address ‘923 Garcia Road in Santa Barbara, CA’. It confidently replied that the address existed—even though it does not.
We then tested the same address using Microsoft’s CoPilot and received conflicting answers. One response stated that the address existed, while another recommended using a reliable online tool to verify the address.
These inconsistencies highlight the inherent limitations of LLMs and underscore their unsuitability for tasks requiring authoritative, fact-based validation.
Why Fake Addresses Are Bad for Business
The consequences of relying on fake or inaccurate addresses are more than just embarrassing—they’re costly. Invalid addresses result in undelivered packages, frustrated customers, wasted time, and unnecessary expenses. For industries like e-commerce, insurance, and banking, these errors also open the door to fraud, regulatory non-compliance, and reputational damage.
The Speed Factor
In today’s fast-paced digital landscape, time is critical to user experience. LLMs like ChatGPT or Microsoft’s CoPilot take approximately 3 seconds per address validation, introducing a noticeable delay in workflows that demand real-time results.
In contrast, dedicated address validation services like Service Objects’ Address Validation – US achieve results in just 0.8 seconds—a nearly fourfold improvement. For businesses managing large volumes of customer data or processing high-speed transactions, like ecommerce, these milliseconds add up, significantly impacting efficiency and customer satisfaction.
Energy Efficiency Matters—and Its Costs
Beyond speed, energy consumption is a growing concern. Wired tells this story well, “AI’s Energy Demands Are Out of Control. Welcome to the Internet’s Hyper-Consumption Era”. Every lookup with an LLM consumes around 3 Wh of power, a substantial draw when scaled across millions of queries. Address validation services like Service Objects, on the other hand, consume only ~0.08 Wh per lookup, making them far more efficient.
This difference in energy consumption has broader implications beyond environmental impact. As AI-powered services grow in popularity, their reliance on significant computational resources and power will inevitably lead to higher operational costs. These costs will ultimately be passed on to users, making LLM-based services more expensive over time.
In industries like e-commerce and logistics, where margins are already tight, such inefficiencies could have a profound impact on profitability. By contrast, solutions like Address Validation – US, which optimize both energy usage and accuracy, offer a cost-effective and sustainable alternative for businesses looking to scale without skyrocketing expenses.
True Address Validation: The Smarter Alternative
When it comes to ensuring accurate, deliverable, and legitimate addresses, the solution isn’t a probabilistic LLM—it’s authoritative data. That’s where Service Objects’ Address Validation – US service steps in.
Unlike LLMs, our address validation engine doesn’t guess or hallucinate. It cross-checks addresses against authoritative datasets such as the USPS and enhances accuracy by integrating non-address data like authoritative map and phone datasets. These datasets often include customer names and their corresponding addresses, allowing the system to further validate addresses and increase match rates and confidence in the results.
This capability ensures not only accuracy but also the ability to validate complex or incomplete addresses, overcoming challenges where standard postal data may fall short.
Even tools like Microsoft’s CoPilot—a valuable resource for developers—cannot determine whether an address is real or fake. In fact, CoPilot itself advises users to integrate a specialized service like Address Validation – US to confirm address authenticity.
The Bigger Picture: Accuracy, Speed, and Sustainability
The demands of modern business extend beyond accuracy and speed—sustainability is increasingly at the forefront. With Service Objects’ Address Validation – US, businesses can confidently validate addresses in real time while consuming a fraction of the power required by LLMs. This not only saves operational costs but also reduces the environmental footprint of data validation processes.
As AI services continue to expand, the energy required to power them will escalate, creating a major bottleneck for both scalability and cost-efficiency. Businesses that rely heavily on computationally intensive AI models like LLMs risk being burdened by rising energy costs and an unsustainable cost structure. Dedicated solutions like Address Validation – US bypass this issue, delivering reliable results without the environmental or financial overhead.
Conclusion: Putting Accuracy First
When you need to validate addresses for tasks like fraud prevention, regulatory compliance, or efficient delivery logistics, accuracy, speed, and sustainability are non-negotiable. While LLMs like ChatGPT and CoPilot are groundbreaking tools in their own right, they are fundamentally unsuited for accurate address validation.
By relying on tools designed for precision, not prediction, Service Objects empowers businesses to stay one step ahead, ensuring that fake addresses never make it onto the map—efficiently, accurately, and responsibly.
