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By Stuart Hubbard | August 15, 2025
Why Your Frontline Data Could Be the Key to Unlocking AI’s Full Potential
Artificial intelligence is often hailed as a game-changer for businesses across industries. It powers everything from personalized shopping recommendations to supply chain optimization. However, as AI continues to advance, it faces a critical challenge: access to data. The availability of high-quality, diverse datasets – essential for training AI models and enabling Agentic AI – is becoming increasingly scarce.
Recent studies reveal that restrictions on web data, which is a major source for AI, have increased dramatically, with 25% of high-quality sources becoming restricted between April 2023 and April 2024. Some experts even warn that the supply of usable human-generated public text could dry up within the next decade.
But before you start worrying about the future of AI, let me offer a different perspective. The data we need isn’t disappearing. It’s hiding in plain sight. I’m talking about your frontline data: the information generated every day in your operations, by your employees, machines, workflows, and even your CCTV cameras. If you’ve been overlooking this goldmine, now’s the time to rethink your approach.
What Makes Frontline Data So Powerful?
Frontline data is unique because it reflects what’s happening in the heart of your business in real-time. It’s generated during daily operations, capturing the details of workflows, environments, and interactions that are central to how your organization functions. This makes it practical and relevant in ways that other datasets often aren’t.
Take retail as an example. Data on shelf inventory, shopper behavior at checkouts, or workforce scheduling provides insights that can optimize inventory management, improve staffing efficiency, and even anticipate customer needs. In logistics, information about delivery routes, parcel dimensions, or proof-of-delivery photos can help fine-tune operations and enhance customer satisfaction. Manufacturing data, such as records of defects or equipment performance, can be used to predict maintenance needs and improve product quality.
This kind of data is already helping businesses enhance efficiency and make more informed decisions. With the adoption of agentic workflows, it will become even more essential for boosting productivity by augmenting your workforce. Its value is further amplified in light of the limitations of traditional AI datasets, which frequently suffer from inaccuracies or biases. Frontline data, on the other hand, is grounded in real-world operations, making it a more reliable and actionable source of insight.
Turning Frontline Data into Actionable Insights
Of course, having data and knowing how to use it are two very different things. Frontline data is often unstructured, scattered across devices, or buried in systems that don’t talk to each other. The challenge lies in capturing it effectively and transforming it into something useful.
Technologies like mobile computers, RFID readers, and smart cameras can make this process easier. For instance, RFID systems can capture large amounts of accurate data quickly, which can then be analyzed to improve inventory tracking, identify quality issues, or plan for different scenarios. Smart cameras and sensors can collect contextual data, such as environmental conditions or equipment usage, and identify inefficiencies or predict when maintenance will be needed.
But gathering data is just the first step. The real value comes from integrating it into a broader strategy. This could mean using AI-powered tools to identify patterns and trends, or creating digital twins – virtual models of physical operations – to simulate and optimize workflows. The goal is to move beyond simply collecting data and start using it to make better, more informed decisions at the edge and in real-time.
The Responsibility of Using Frontline Data
As businesses start to explore the potential of frontline data, it’s important to approach it thoughtfully. Data collection and use come with ethical responsibilities, especially when it involves sensitive information about employees or customers. Privacy, security, and fairness should always be top of mind.
Establishing clear guidelines for data use is a good place to start. This might include anonymizing sensitive information, ensuring compliance with privacy regulations, and monitoring for bias in AI models. Transparency is also critical. People need to trust that their data is being handled responsibly, and businesses that prioritize ethical practices will be better positioned to maintain that trust.
Discuss the New Era of AI and Data at the Frontline AI Summit
The challenges facing AI today, such as data scarcity and quality concerns, might seem daunting, but they also present an opportunity. By turning to the wealth of data generated on the frontline, businesses can create more intelligent, efficient, and adaptive systems.
For industries like retail, logistics, and manufacturing, the potential is enormous. Frontline data can unlock new ways of working, from optimizing workflows to enhancing customer experiences. As the technology for capturing, analyzing, and integrating data continues to evolve, the possibilities will only grow.
The question isn’t whether frontline data will play a role in the future of AI; it’s how businesses will choose to leverage it. Don’t miss the chance to be part of the conversation, connect with others, and discover how AI can help you and your team thrive in the ever-changing world of work at our inaugural Frontline AI Summit, being held September 18 in Nashville, Tenn. I look forward to continuing the conversation with you there.
For more information, visit https://zebraevents.cventevents.com/event/FrontlineAISummit/summary.
