Jeff Wittich is Chief Product Officer at Ampere Computing
    As the IT landscape continues to evolve, new trends are emerging and are expected to reshape the way businesses approach technology in 2025. From generative AI to data sovereignty, industries across the board will be challenged to rethink their strategies to adapt to new changes in the coming year. Based on key observations and industry signals, here are Ampere's top four predictions for 2025.

Trend 1: From experiment to Execution: Generative AI reasoning takes center stage
    Generative AI is transitioning from a purely experimental tool to a fully integrated solution that can deliver significant business value. While in the past year, the adoption of generative AI has largely focused on chatbots based on public data, the future focus is on applying it to private, secure data sets to create more valuable tools. Businesses in industries such as finance, insurance and e-commerce are gearing up to adopt these technologies to extract valuable insights from proprietary data.
    Deployment flexibility will be critical. As AI workloads expand into a variety of environments - including on-premises deployments, edge and air-gapped isolated hosting facilities - latence-sensitive applications will require infrastructure closer to users, deployed in existing data centers and access points (PoPs). In addition, inference is no longer a standalone workload. Supporting tasks such as retrieval enhanced generation (RAG) and application integration will require powerful general-purpose computing combined with AI-specific resources, while emphasizing efficiency and scalability.

Trend Two: Driving the future: Renewable energy growth adds efficiency
    As the demand for computing surges, so does the demand for electricity. However, grid overload and regional power constraints are forcing industries to seek new solutions. With the emergence of small, regionally distributed data centers, renewable energy sources such as solar, wind, and geothermal are gaining favor. These projects take longer to evolve to meet the immediate needs of the growth in IT infrastructure.
    However, efficiency improvements cannot be delayed. In order to avoid the adoption of new types of non-renewable energy in the short term or to extend their service life, hardware optimization will play a key role in reducing electricity demand. Replacing older, energy-intensive systems with modern, efficient processors can dramatically reduce energy consumption and make existing infrastructure more sustainable. This shift in efficiency is essential to strike a balance between increasing energy demand and environmental stewardship responsibilities.

Trend 3: Density Growth: Unleash the full potential of every rack and data center
    Given the rapid growth in demand for AI computing, large-scale density has become the new benchmark for computing efficiency. Building solutions is no longer limited to the node level, but extends to the rack and data center level. This means that enterprises are maximizing the workload per rack by taking full advantage of existing hardware. Unlike traditional systems, which often underutilize resources due to inefficiencies, modern architecture is designed to eliminate waste and increase average utilization across rack and data center scales, while avoiding the negative effects of unpredictability.
    At the solution level, the challenge of density optimization is not limited to AI-only workloads. Certain AI workloads, particularly inference workloads, are driving infrastructure changes to accommodate mixed-use environments, and universal compute density is just as important. In software engineering organizations, more efficient virtualization and containerization technologies combined with more efficient containers and PAC (power aware coding) practices will enable better resource allocation, enabling enterprises to achieve higher utilization without sacrificing performance.

Trend 4: Sovereignty and Security: The rise of enterprise AI
    Data sovereignty and security will have a significant impact on AI deployment strategies in 2025. Enterprises are increasingly recognizing the value of proprietary data sets and seeing them as competitive assets. This shift means that AI inference workloads will not only run on hyperscale public clouds, but also in more secure environments such as private clouds, on-premises data centers, or private hosted facilities.
    The risk of data breaches and AI algorithm tampering highlights the need for secure, isolated infrastructure. As businesses compete in AI-driven innovation, the ability to protect intellectual property and sensitive information will be critical to success. In addition, this trend will expand the role of enterprise-owned computing resources, creating a more decentralized and secure AI ecosystem. This need for sovereignty and security, combined with the need to place computing resources closer to users, will decentralize computing resources and give rise to more compute-heavy edge architectures.

About Ampere Computing
    Ampere Computing is a modern semiconductor company dedicated to shaping the future of cloud computing and has introduced the world's first cloud-native processor. Built for the sustainable cloud, Ampere cloud-native processors combine the highest performance and best performance per watt to help accelerate the delivery of multiple cloud applications and deliver industry-leading performance, power efficiency and scalability to the cloud.