As we approach 2025, the technological landscape is poised for significant transformation driven by advancements in artificial intelligence (AI) and DevOps practices. Organizations that embrace these innovations, while addressing security and talent challenges, will distinguish themselves as leaders in an increasingly digital world. As AI continues to integrate into various operations, and DevOps practices evolve, 2025 will be a transformative year for businesses in technology development, deployment, and management. The convergence of AI and DevOps will usher in advancements that redefine the digital ecosystem, focusing on scaling AI with innovative infrastructure and refining development processes to meet the demands of faster, more secure technology deployments. This article explores the anticipated advancements and evolving trends in AI, DevOps, and data management solutions that will shape the future.
AI and Data Management Solutions
One of the key themes for 2025 is the critical importance of managing data and infrastructure that support AI workloads. As AI continues to integrate into various operations, managing distributed data environments and addressing the skyrocketing demands for Graphics Processing Units (GPUs) will drive significant innovation. Efficient data access across distributed environments will be crucial, minimizing data movement and duplication to optimize performance and cost. Christian Buckner, Senior Vice President of Analytics and IoT at Altair, projects a more grounded approach to generative AI as it matures. Buckner suggests that the initial hype will subside as generative AI technology evolves to meet specific business needs through more advanced foundation models, tools for integrating AI into operations, and platforms to create AI agents that automate business processes and provide direct insights to users.
Another key player in this landscape, Haoyuan Li, Founder and CEO of Alluxio, highlights the urgency of addressing data access challenges. With the costs of AI model training on the rise, enterprises must maximize GPU utilization, which is a primary design goal for modern data centers. This will drive innovations in hardware and software to support high bandwidths and reduce checkpoint-saving times. Li emphasizes that efficient management of data access across distributed environments will be crucial while minimizing data movement and duplication. As businesses grapple with the rising costs of AI model training, maximizing GPU utilization becomes essential for optimizing performance and cost-efficiency. In summary, as the integration of AI into various operations continues, managing distributed data environments and addressing the skyrocketing demands for GPUs will drive significant innovation by 2025.
AI Security and Data Governance
The adoption of AI brings increased risks, including covert malware within AI models and compliance challenges, particularly in HR applications. By 2025, AI security and data governance will be critical as there will be a strong focus on thoughtful oversight and robust data governance. One transformative tool in this area will be knowledge graphs, which help bridge the gap between generative AI and end-users by providing a semantic layer that makes enterprise data ecosystems more understandable. Christian Buckner articulates that knowledge graphs will create logical connections between previously siloed data sources, enabling generative AI models and business users to generate real insights from data. This capability will be essential for organizations to harness the full potential of their data while maintaining security and compliance.
Michael Lieberman, CTO and co-founder of Kusari, warns of the increased difficulty in detecting AI-related threats. He predicts that as AI technology advances, there will be an uptick in covert attacks involving free models that contain malware, potentially introducing backdoors or harmful behaviors. To address these risks, robust data governance and security measures will be critical. Moreover, Krishna Subramanian, Co-founder and COO of Komprise, foresees the maturation of unstructured data governance processes as essential to prevent corporate data leakage and misuse while avoiding erroneous AI results. Automated workflows for data classification and orchestration will become indispensable in managing data efficiently at scale. As AI and data governance practices evolve, addressing security challenges and leveraging innovations like knowledge graphs will be crucial to enable organizations to harness the power of AI safely and effectively.
DevOps and Cloud-Native Development Trends
As software development accelerates, several DevOps trends will shape the IT landscape in 2025, positioning organizations to create more efficient and agile systems. GitOps, which treats Git as a central source of truth for managing infrastructure and application configurations, will become a pivotal practice. GitOps provides visibility and enables automated testing and provisioning, streamlining operations and improving efficiency. Christian Buckner emphasizes the rise of agentic AI in transforming data analytics. AI agents will automate insights and recommendations, reducing the need for business leaders to pose specific questions, helping organizations uncover deeper connections within their data, and facilitating more strategic decision-making. Moreover, Derek Ashmore, Application Transformation Principal at Asperitas, foresees the expansion of platform engineering. This approach equips developers with pre-configured tools to speed up application development, streamlining processes significantly. Platform engineering can be metaphorically described as giving software teams a complete car rather than a collection of parts.
Additionally, the implementation of AIOps, which bolsters operations necessary for AI development and deployment, will dominate DevOps strategies in 2025. As AI transitions from experimental to operational phases, implementing policy-based governance and infrastructure static code analysis will become essential to ensure security and compliance within increasingly complex environments. AIOps facilitates continuous monitoring and management of applications and systems using AI, thus optimizing operational efficiency. Scott Wheeler, Cloud Practice Lead at Asperitas, predicts that zero-trust security models will become foundational across IT landscapes. These models will replace outdated authentication methods and become the default standard for securing applications and services, adding an extra layer of protection against threats. Finally, serverless computing is set to gain traction by allowing developers to concentrate on application logic without managing underlying infrastructure. Though not suitable for all use cases, serverless computing remains a highly attractive option for scalable, event-driven applications, providing flexibility and efficiency in deployment.
Talent Development and AI-Friendly Culture
The rapid evolution of AI will challenge businesses to prioritize continuous learning and foster an AI-friendly culture to stay competitive. Nicole Helmer, VP of Skills and AI at Degreed, emphasizes that companies have extensive skill requirements for AI engineers. However, the technology landscape evolves so quickly that even top talent must commit to continuous learning to remain relevant. AI-savvy businesses will need to ensure that their workforce is equipped with the necessary skills and knowledge to handle new technologies, making continuous education and training a priority. Building an AI-centric culture involves democratizing data access and educating employees. Matheus Dellagnelo, co-founder and CEO at Indicium, underscores the importance of aligning data accessibility with business needs. Simplifying data access for non-technical stakeholders and utilizing generative AI alongside no-code analytics tools will be vital. Strong data management processes are essential to ensure everyone within the organization can benefit from AI advancements.
Moreover, treating learning and data accessibility as ongoing priorities will enable businesses to maximize the potential of their AI investments while empowering employees to make informed, data-driven decisions. By creating an environment that encourages innovation and continuous learning, organizations can maintain a competitive edge. As the AI and DevOps landscape evolves, fostering a culture that embraces AI and supports talent development will be crucial for businesses aiming to lead in this rapidly changing digital era. This approach ensures that organizations remain adaptable and can leverage emerging technologies effectively to drive growth and innovation.
Looking Ahead
The rise of AI entails increased risks, such as covert malware within AI models and compliance difficulties, especially in HR applications. By 2025, AI security and data governance will be paramount, emphasizing meticulous oversight. Knowledge graphs will emerge as a vital tool, bridging the gap between generative AI and users by offering a semantic layer for clearer data ecosystems. Christian Buckner explains that knowledge graphs will link previously isolated data, enabling AI and business users to derive meaningful insights. This will be crucial for organizations aiming to fully leverage their data while ensuring security and compliance.
Michael Lieberman, CTO and co-founder of Kusari, highlights the rising challenge of detecting AI-related threats. With advancing AI, he foresees an increase in covert attacks via free models containing malware, which could introduce backdoors. Addressing these risks requires robust data governance and security protocols. Additionally, Krishna Subramanian, Co-founder and COO of Komprise, predicts that maturing processes for unstructured data governance will be essential to prevent data leaks and ensure correct AI results. Automated workflows for data classification and management will be vital for efficient large-scale data handling. As AI and governance practices progress, tackling security issues and utilizing innovations like knowledge graphs will be crucial to safely and effectively harness AI’s power.