Businesses deploying autonomous artificial intelligence agents are discovering a critical dependency that has little to do with the algorithms themselves. The quality and management of underlying data, it turns out, now determines whether these systems deliver value or descend into chaos. According to NetApp, a company specializing in enterprise storage and cloud data services, organizations are often getting ahead of themselves by focusing on AI models before establishing a solid data foundation.
Kirsty Biddiscombe, the EMEA Business Lead for AI, ML, and Data Analytics at NetApp, argues that the potential of agentic AI has been underhyped, not overhyped. She points to its capacity to automate complex and time-consuming tasks, thereby boosting productivity. From managing business travel to streamlining operations in finance and healthcare, autonomous agents promise significant efficiency gains. However, successful deployment hinges on a strategic, use-case-specific approach rather than a broad, unfocused implementation. The key, she insists, is to first address the data infrastructure.
The State of Agentic AI Adoption
Many organizations are eager to harness the power of agentic AI, but they often overlook the foundational requirements. NetApp’s own experience with AI implementation has demonstrated its potential, leading to a 71% increase in task completion rates and a 99% improvement in forecasting accuracy. These results underscore the transformative power of AI when implemented correctly. Biddiscombe cautions that businesses must approach AI strategically to realize a return on their investment. The initial step should always be to identify specific use cases where AI can deliver the maximum impact and alleviate organizational pressures.
A Strategic, Not Hasty, Approach
Instead of deploying AI across all operations simultaneously, a more measured strategy is advisable. By starting with a few high-impact areas, businesses can streamline workflows, accelerate decision-making, and free employees from repetitive tasks. For example, AI can handle mundane data entry, allowing staff to concentrate on more strategic and creative work. Furthermore, AI can play a crucial role in cybersecurity. NetApp’s AI-powered ransomware solution automatically detects and responds to threats, enabling IT teams to focus on higher-value activities instead of constant firefighting.
Data as the Linchpin of Success
In the context of agentic AI, data is not just an important component; it is the entire foundation. With fewer human checkpoints in automated systems, the quality of an organization’s data becomes the determining factor between a successful outcome and a process failure. A single incorrect data point can have significant consequences. Biddiscombe illustrates this with a travel example: erroneous data could send a traveler to the wrong airport. When this scenario is scaled to critical sectors like healthcare, the stakes are much higher, as inaccurate data could adversely affect a patient’s treatment. Therefore, secure, clean, and accessible data is the bedrock of any successful AI adoption.
The Imperative of a Unified Data Infrastructure
To enable agentic AI to function effectively, businesses require data that is unified, reliable, and fast. This necessitates breaking down data silos and consolidating information from edge devices, on-premises systems, and cloud environments into a single, cohesive infrastructure. This unified system must be scalable to accommodate business growth. AI workloads demand high-throughput, low-latency storage systems to perform optimally. When combined with cloud-native technologies and hybrid deployments, organizations can achieve the necessary scalability, security, and compliance.
Building a Future-Ready Foundation
NetApp’s solutions are designed to integrate data from a wide range of sources, which facilitates the creation of customized AI applications. This integration enhances the relevance and accuracy of AI-generated responses. By implementing these data management strategies, businesses can position themselves to thrive with agentic AI. The goal is to create an “Intelligent Data Infrastructure” that unifies file, block, and object storage, eliminates silos, and supports the next generation of technologies. This infrastructure ensures that AI is limited only by an organization’s imagination, not by its technical framework.
Practical Steps for Businesses
For businesses looking to leverage agentic AI, the path forward involves a focus on hybrid cloud data access, streamlined management, and robust security. NetApp’s native cloud storage services integrate seamlessly with major cloud providers, eliminating the need to duplicate or move datasets. This allows companies to concentrate on extracting insights from their data rather than on the complexities of data management. Built-in ransomware protection, encryption, and access controls are also essential to safeguard against sophisticated cyber threats.
Partnerships and a Vision for the Future
NetApp collaborates with technology leaders like Nvidia, Intel, Lenovo, and Cisco to provide access to cutting-edge AI technologies, ensuring that organizations can be “AI-ready.” These partnerships are crucial for developing comprehensive solutions that address the multifaceted challenges of AI implementation. Biddiscombe’s vision of the future is one where agentic AI is a commonplace reality, seamlessly handling tasks like booking flights, managing diaries, and even coordinating driverless vehicles. This future, however, is entirely dependent on the quality and management of the data that fuels these intelligent systems. The potential to unlock hours of productivity and foster healthier, more balanced work lives is immense, but it all begins with a solid data foundation.
