- Companies are integrating artificial intelligence (AI) into their datasets to enhance efficiency and productivity.
- The majority of businesses prefer AI models that are conceptual in nature, with some components located on-site.
- Internally managing AI helps companies develop tailor-made solutions to meet their specific needs.
It is now more common to encounter individuals using conceptual AI than those who are not. Nevertheless, some businesses are just starting to leverage this technology. From enhancing customer service to exploring sales opportunities, the widespread adoption of AI can benefit businesses. However, for organizations to fully grasp the potential of AI, they must address a significant concern: data sovereignty.
Data plays a crucial role in optimizing AI capabilities. Yet, utilizing common tools to access sensitive organizational data stored on public clouds can pose security and privacy risks. This is one reason why 82% of businesses prefer generative AI models developed on-premises or through a hybrid approach, as indicated in a recent study by Dell Technologies.
The positive news is that organizations do not necessarily need to construct complex language models from the ground up to achieve success. Pre-built AI designs can be implemented in secure environments where data is safeguarded by enterprise-grade antivirus software to enhance security. Moreover, by fine-tuning or customizing off-the-shelf AI models, organizations can achieve cost-effectiveness and resource optimization.
AI for Various Applications
AI is poised to revolutionize several key industries and job functions. In fact, a 2023 report from McKinsey Digital highlights four primary areas ripe for AI transformation in the near future: consumer enterprises, sales and marketing, IT operations and development, and research and development.
The report also outlines 63 distinct use cases where AI can be applied to address organizational challenges, enhancing business outcomes, boosting productivity, or both.
Numerous tasks are already being executed across diverse sectors using AI, including:
- Content creation, such as generating product descriptions or delivering personalized responses to customer inquiries.
- Natural language processing to interact with vast amounts of data in a more intuitive manner.
- Streamlining software development processes for greater efficiency.
- Providing 24⁄7 access to assistance and information through virtual assistants for clients and end users.
- Conducting design and data analysis, enabling predictions for research studies like drug discovery and other R&D initiatives.
- Automating document processes to summarize and contextualize information for marketers, business owners, and other audiences.
Benefits of Implementing Artificial Intelligence in Data
Integrating AI into an organization’s data, rather than vice versa, offers substantial advantages for each use case, including heightened security through better management of sensitive information. According to Nicholas Brackney, a generative AI and cloud advocate at Dell Technologies, this advantage alone could be a decisive factor for many organizations.
Brackney emphasized, “The moment a trade secret is exposed, it loses its protective value,” underscoring the risk of inadvertent exposure through certain public AI tools on public cloud platforms.
Data sovereignty stands out as a primary motivator for on-premises deployments. Organizations face challenges related to intellectual property, such as safeguarding trade secrets, while also complying with strict privacy and regulatory mandates. By managing these issues internally, businesses gain more control over data access and model operations.
In addition to security considerations, internal AI implementation enables organizations to leverage smaller, more focused models, facilitating rapid iteration of new solutions. This translates to a higher return on AI investment.
Operations can benefit from real-time insights derived from customized solutions that eliminate the need for cloud round-trips. Retail outlets and manufacturing facilities, for instance, can leverage real-time data and insights made possible by integrating AI into their datasets.
Furthermore, tailored AI solutions designed for specific use cases can yield hidden cost savings, as smaller models can operate on individual PCs or workstations.
Many businesses have only begun to tap into the potential of AI adoption and utilization. By formulating a robust data strategy, organizations can enhance control, maximize returns on investment, and mitigate risks as they embark on their AI journey.
Learn more about how Dell Technologies’ suite of solutions and services can assist in incorporating AI into your data. This content was produced by Insider Studios in collaboration with Dell Technologies.
