Generative AI (GenAI) continues to be the most exciting emerging technology attracting the attention of business leaders and technology experts globally. 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, AI adoption also presents one of the most prominent digital transformation challenges of modern times: managing the increasing volumes of data required to train AI models.
We see evidence of these struggles in our survey data; Companies are legitimately interested in incorporating GenAI into their strategies and operations, but many (39%) admit they have difficulties with implementation and deployment, noting that technical complexity is one of the main barriers to successful adoption.
The appeal of GenAI is strong, but effectively adopting and leveraging any emerging data generation technology depends on a solid storage foundation. Unfortunately, choosing the right one can be complex, filled with decisions about compliance, costs, and a host of potential additional requirements, such as real-time analytics.
Before you set out on your journey, there are a few key areas to consider.
Field CTO for the Storage Solutions and Platforms team, at Dell Technologies.
1. Tackle unstructured data
We expect GenAI models to meet our demanding requirements around better data movement and access. In the past, many organizations (probably most) considered handling unstructured data files, such as images, videos, voice notes, and chat logs, to be a major inconvenience. However, in the contemporary age of AI, this unstructured data has become a potentially invaluable resource for analysis and better decision making. It's also true that unstructured data like this accounts for more than 90% of all data, so storage platforms that can handle its complexity are needed.
Storing this type of data requires a system that can be expanded smoothly and economically. Object storage solutions are often the ideal choice for unstructured data because they include complete metadata and distinct identification, simplifying data access and retrieval. The ideal storage for unstructured data should offer flexibility to accommodate various types of data and optimize access to archived information.
Despite the inherent challenges in management and utilization, unstructured data has immense value. It is a treasure trove of hidden patterns and insights that can propel an organization toward novel and inventive competitive strategies. In today's cutthroat market, leveraging unstructured data could be the key to outshining the competition.
2. Is your data storage aligned with innovation?
With the value and volume of data increasing, 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 type also requires infrastructure that can facilitate new digital experiences for customers while modernizing the internal IT systems necessary to drive innovation. Successful innovation depends on a highly efficient storage system to optimize management, improve privacy and security, and protect against outages.
3. Security and privacy
AI has significantly increased the cyber threat landscape. As more businesses venture into AI adoption, data breaches and privacy issues have become more prevalent than ever, with 48% of organizations identifying cyberattacks as a top threat. While AI can help strengthen data protection, bad actors can also use it for their own benefit.
This dichotomy underscores the need for resilient storage infrastructure that can provide 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 robust incident response plan, so it is crucial to align with security specialists, stay informed on emerging threats, and continually invest in security solutions capable of adapting to the landscape of evolving threats. Data privacy and security are not luxuries; They are integral to a company's reputation and success, particularly in the age of AI.
The path to adoption of 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 handle growing volumes of data, particularly unstructured data, and align with the organization's innovative aspirations.
While GenAI offers a wealth of opportunities, it also expands the cyber threat landscape. Therefore, organizations must prioritize 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 advantage and drive success in today's cutthroat market. The future belongs to those prepared to lead with data as a differentiating asset, and now is the time to start preparing for that future.
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