Generative AI (GenAI) remains the most exciting emerging technology gripping the attention of global business leaders and tech experts. Its potential has inspired leaders; according to our recent AI pulse survey of IT decision-makers, a considerable 75% report that they believe GenAI will have a significant or transformative influence on their organizations. However, the adoption of AI also presents one of the most prominent digital transformation challenges of modern times: managing the ever-expanding volumes of data needed to train AI models.
We see evidence of these struggles in the data from our survey; businesses are rightfully keen to embed GenAI into their strategies and operations, but many (39%) admit struggling with implementation and deployment, reporting technical complexity as one of the main barriers to successful adoption.
The allure of GenAI is strong, but adopting and effectively leveraging any emerging data-generating technology hinges on a robust storage foundation. Unfortunately, choosing the right one can be complex, fraught with decisions around compliance, cost, and the myriad of potential additional requirements such as real-time analytics.
Before starting the journey, there are a few key areas to consider.
Field CTO for the Storage Platforms and Solutions team, at Dell Technologies.
1. Addressing unstructured data
We expect GenAI models to meet our challenging requirements around better data movement and access. In the past, many (probably most) organizations considered handling unstructured data files such as imagery, videos, voice memos, and chat logs as a significant inconvenience. However, in the contemporary age of AI, such unstructured data has evolved into a potentially invaluable resource for analysis and enhanced decision-making. It is also true that unstructured data like this makes up over 90% of all data, so storage platforms that can handle its complexity are needed.
Storing this type of data necessitates a system that can expand seamlessly and economically. Object storage solutions are often the go-to for unstructured data because they include comprehensive metadata and a distinct ID, simplifying data retrieval and access. The ideal storage for unstructured data should offer flexibility to accommodate various data types and streamline access to archived information.
Despite its inherent challenges in management and utilisation, unstructured data holds immense value. It’s a treasure trove of concealed patterns and insights that can propel an organisation towards novel and inventive competitive strategies. In today’s cutthroat marketplace, leveraging unstructured data could be the key to outshining the competition.
2. Is your data storage aligned with innovation?
With the increasing value and volume of data, organizations are retaining more information to improve customer loyalty and bring new services to the market. By strategically investing in storage infrastructure, organizations can better evolve into digital innovators by using data to their advantage. Innovation of this ilk also requires an infrastructure that can facilitate new digital experiences for customers while also modernizing the internal IT systems needed to power innovation. Successful innovation relies on a highly efficient storage system to streamline management, enhance privacy and security, and safeguard against disruption.
3. Security and privacy
AI has increased the cyber threat landscape significantly. As more companies venture into AI adoption, data breaches and privacy issues have become more prevalent than ever, with 48% of organizations identifying cyberattacks as a primary threat. While it’s true that AI can help bolster data protection, bad actors can also use it to their own advantage.
This dichotomy underscores the necessity for a resilient storage infrastructure that can deliver recovery in the event of a breach. Organizations operating today need advanced solutions that improve storage efficiency, strengthen cybersecurity, and provide flexibility to scale capacity and performance seamlessly.
Of course, having a resilient platform does not eliminate the need for a solid incident response plan, so it’s crucial to align with security specialists, remain informed about emerging threats and continuously invest in security solutions capable of adapting to the evolving threat landscape. Data privacy and security aren’t luxuries; they are integral to a business’s reputation and success, particularly in the age of AI.
The journey towards adopting Generative AI (GenAI) is undeniably complex, but its potential to transform businesses is immense. The foundation of this transformation lies in the right storage solution—one that can manage the burgeoning volumes of data, particularly unstructured data, and align with the organization’s innovative aspirations.
While GenAI brings a wealth of opportunities, it also expands the cyber threat landscape. Hence, organisations must prioritise security and privacy by investing in resilient storage infrastructures and robust incident response plans. Collaborating with security experts and staying abreast of evolving threats is not an option but a necessity in this digital age.
The path to becoming an innovator using GenAI is not without its challenges. However, with strategic investments in storage infrastructure, effective management of unstructured data, and a strong focus on security, organizations can harness the power of GenAI to gain a competitive edge and drive success in today’s cutthroat marketplace. The future belongs to those who are ready to lead with data as a differentiating asset, and the time to start preparing for that future is now.
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