Hybrid Cloud Emerges as Key to Unlocking the Power of Generative AI

Enterprise Infrastructure for Generative AI: A Foundation for Success

Generative AI, or GenAI, represents a transformative technology with the potential to revolutionize how businesses operate and compete. Most organizations are already exploring its potential, with 97% viewing GenAI initiatives as a top-five priority. However, unlocking the true power of GenAI requires a strong foundation—robust and secure data infrastructure that can drive GenAI success, according to Enterprise Infrastructure for Generative AI: A Foundation for Success, a new report from Hitachi Vantara based on a survey by the Enterprise Strategy Group.

Download a copy of the eBook:

Enterprise Infrastructure for Generative AI: A Foundation for Success

Beyond examining the technology landscape and key trends, we place particular emphasis on the decisions surrounding data, models, and most importantly, the infrastructure that underpins successful GenAI implementations. Security, cost, and data quality are some of the biggest challenges and concerns organizations face when it comes to storing and managing data related to GenAI initiatives.

The global survey of enterprise IT leaders, line-of-business leaders, and data-centric practitioners/management enabled a comprehensive view of GenAI initiatives from strategy and decision making, infrastructure and implementation, to operations and ongoing management in production.

The respondents represented organizations based in North America and Western Europe across all public- and private-sector industries, including financial services, tech/telco/media and entertainment, manufacturing, and healthcare/life sciences.

GenAI Adoption on the Rise

Despite being a relatively new technology, GenAI adoption is widespread. Most organizations are already using GenAI for at least one use case. Additionally, 90% believe GenAI will improve operational efficiency and employee productivity, potentially leading to a competitive advantage. While GenAI is a priority, organizations face a diverse set of challenges. Cost, data quality, and integration needs are hurdles, but security remains the top concern for 38% of respondents. Data privacy, confidentiality, potential misuse, and unauthorized access are also key security challenges.

However, while some view security concerns as a challenge, there is a growing trend of embracing the potential of GenAI to enhance certain security measures and tasks, such as providing advanced threat detection and enhancing automated response systems. Which makes finding the right balance between security challenges and potential benefits crucial for GenAI decision-makers.

Hybrid Cloud Emerging as the Preferred Solution

A balanced approach is preferred for the underlying GenAI infrastructure. While 37% believe their current infrastructure is sufficient, this may change as GenAI adoption matures. Hybrid cloud, a combination of on-premises and public cloud, is the clear favorite, with 78% of respondents using it for building and deploying GenAI solutions. This preference extends to data pipelines used for moving and managing data. This also suggests the need for hybrid cloud data platforms to manage a vast variety of data types including structured and unstructured, and to deliver on the performance and security needs amplified by the anticipated role (86%) of retrieval-augmented generation (RAG).

Organizations also prioritized key criteria for evaluating and selecting GenAI infrastructure vendors. Some technical criteria, such as fast performance and low latency, are all but expected at this point. However, a few criteria stuck out: Reliability and availability of solutions with minimal downtime maintains a top spot at 35%, followed by the need for hybrid cloud support (33%). Notably, there also is a demand for environmental sustainability and energy-efficient storage solutions (25%), highlighting growing sustainability concerns around AI.

IT Leadership Steering the GenAI Ship

While influence in GenAI decisions spans a wide variety of roles and departments, IT leadership is taking the lead. IT operations and technical executives are top stakeholders influencing purchase decisions, with 38% and 39% of respondents, respectively. IT also serves as the primary budget holder for GenAI initiatives. This shift in decision-making authority raises questions for business leaders who traditionally managed their own budgets for technology purchases. Unclear ownership and budgetary control can be roadblocks for GenAI adoption.

Organizations are taking a more generic and affordable approach to GenAI. Most (96%) prefer alternatives to proprietary large language models (LLMs) to get started. However, they expect to use proprietary models more in the long term to achieve competitive differentiation.

Incorporating enterprise data is seen as a key business differentiator for GenAI. The desire for improved accuracy tops the list of reasons for using the most relevant and recent data, followed by keeping pace with technology, regulations, and evolving data patterns. Managing data is essential for maintaining accuracy as data and business conditions change.

Automation and Optimization Leading Use Cases

Organizations are using Generative AI (GenAI) in innovative ways to achieve their goals. Leading use cases focus on automating and optimizing processes, data analysis, and cybersecurity. However, the specific applications of GenAI vary significantly by industry. For example, in healthcare, multimodal GenAI can analyze medical images with high accuracy, aiding in disease diagnosis. In finance, GenAI can help explain unusual patterns and predict potential fraud, enhancing fraud detection.

As GenAI technology matures and organizations gain trust in its accuracy, we can expect a surge in the number of potential use cases across various industries. As organizations pursue GenAI, they see several areas of the business where they believe it could help; the most common is in improving operational efficiency.

Building a Strong Foundation for GenAI Today

Generative AI holds immense potential to transform businesses. By understanding the challenges and opportunities and building a strong foundation that includes a secure and scalable data infrastructure, organizations can unlock the true power of GenAI. The report by Hitachi Vantara provides valuable insights to help you navigate the GenAI landscape. If you're considering incorporating GenAI into your business strategy, download the full report now: Enterprise Infrastructure for Generative AI: A Foundation for Success.

Additional Resources

• EXECUTIVE BLOG: A New Approach to Enterprise AI
• TECHNOLOGY REVIEW: MIT: AI-based Data Analytics Enable Business Insight
• RESEARCH REPORT: Enterprise Infrastructure for Generative AI: A Foundation for Success