AI in the data center: Transforming operations and careers

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Source is ComputerWeekly.com

The growing role of AI has the potential to transform fundamental aspects of data center operations and staff roles and responsibilities.

As AI continues to expand and intertwine with data center operations, there are various ways the technology can improve efficiency, enhance security, optimize infrastructure and free up staff to focus on more strategic initiatives. Let’s explore how AI enhances data center jobs and how the industry can take advantage of its potential in the future.

Operational efficiency

AI is constantly working in the background to gather and analyze data points related to data center operations. Its analysis provides insights that might inform decision-making, which leads to more impactful operational strategies and execution.

Server management

AI-powered management tools help dynamically balance servers, storage and networking resources. This includes optimizing server utilization, scaling resources automatically and reducing network latency. AI’s ability to adjust workload distribution based on usage patterns and real-time changes in demand drives operational efficiencies across the data center.

Energy consumption

Intelligent energy management can help data centers maintain optimal conditions and reduce energy consumption. Integrating AI into energy management systems enables consistent monitoring of environmental factors, such as temperature and humidity levels. AI also adjusts settings according to equipment specifications.

Data management

AI processes data faster than humans, making it well suited for identifying efficiencies in data storage and workloads. This increases data processing speed, delivering faster response times to users and enabling more efficient access at scale. AI also flags inconsistencies, redundancy and other data quality concerns, protecting against human error.

Better security and data protection

The rapid advancement and adoption of new technologies lead to vulnerabilities. AI helps data centers stay one step ahead of bad actors who are constantly evolving their techniques.

AI excels at anomaly detection as it continuously monitors the environment for unusual activity. This includes looking for suspicious behavior, detecting usage patterns that deviate from the norm and identifying unknown anomalies. AI threat detection systems monitor for known threats and vulnerabilities. When a threat is detected, the system flags the issue and generates actionable next steps to shut the threat down.

Cybersecurity tasks can be automated to protect the security perimeter until human intervention is possible. For example, AI filters out false positives during continuous threat and anomaly monitoring and adjusts specific settings to isolate potentially compromised devices.

Integrating AI into security practices enables staff to focus on more complex issues, such as compliance and governance.

Optimized infrastructure management

Configuring and maintaining the data center infrastructure are resource-intensive, time-consuming and complex. Data center equipment requires consistent maintenance and attention to ensure all components function properly. One malfunction can lead to unexpected downtime.

Traditional data center infrastructure management initiatives often approach maintenance from a reactive standpoint. When complications arise, administrators must troubleshoot to identify and resolve the root cause. Valuable time is lost with a reactive response approach. Integrating AI, however, makes infrastructure management more proactive.

AI monitoring tools that use machine learning autonomously track equipment status and predict when maintenance is necessary. Machine learning algorithms are trained on historical system data and facility logs to establish a performance baseline across hardware and software. Predictive models estimate when maintenance is necessary based on specific events, activities, status data and performance metrics.

Depending on the complication, AI resolves it or generates guidance for humans to address. This method saves time by reducing the need for manual repairs and maintenance. It enables administrators to approach infrastructure management proactively, which helps prevent unexpected downtime. As a result, systems remain fully functional, well maintained and optimized around the clock.

AI technologies are designed to support and augment human capabilities, not replace them.

Freeing up staff to focus on higher-value tasks

AI technologies are designed to support and augment human capabilities, not replace them. By automating intensive, repetitive and tedious tasks, AI empowers data center staff to direct their attention to more strategic jobs.

AI resolves low-level complications and automates routine maintenance tasks, while humans manage more complex situations. The visibility and transparency of AI provide administrators with a better understanding of system functionality and performance on a macro and micro level. This enables administrators to diagnose and solve system issues more accurately.

Data center employees have valid concerns about AI integration and the future of their jobs. AI integration does decrease the need for staff to perform repetitive tasks and maintenance, but it creates new job opportunities for more advanced careers, such as AI engineering and data science.

On a strategic level, AI enables staff to dedicate more time and resources to growth activities, such as scaling up capacity to meet demand and evolving data center capabilities to maintain a competitive edge. This includes researching, developing and investing in more sustainable data center technologies and systems to reduce environmental impact and realize efficiencies that would have otherwise gone undiscovered.

The staff can also allocate time to upskilling. Areas of focus might include the following:

  • Adopting new applications.
  • Improving data privacy policies.
  • Optimizing operations to improve the bottom line.
  • Protecting the security perimeter.
  • Solving integration and interoperability challenges.

Staying ahead of the AI learning curve

As the technology evolves, AI’s role in the data center will continue to grow. When applied thoughtfully and strategically, AI is an asset that transforms the way data centers operate. Admins should explore AI’s benefits for data centers to gain a competitive advantage in the future by doing the following:

  • Acquire experts to manage AI-powered infrastructure. AI data centers need a skilled workforce trained in AI implementation and management. Admins should encourage staff upskilling and provide the proper support to do so.
  • Provide technical support for AI. As AI systems evolve, they will need more specialized components, which might require unique configurations and cooling requirements. Admins should consider how facility design might need to be adapted to support these needs. Building more sustainable systems keeps operational costs low and reduces environmental impacts.
  • Prepare for changes in AI’s regulatory landscape. As organizations grapple with AI ethics, security and privacy concerns, data center infrastructure and admins must be flexible enough to adapt to changing regulations and compliance requirements. Taking precautions around implementing and using AI now, including establishing clearly defined standards and policies, could put data centers in a more stable position.

Jacob Roundy is a freelance writer and editor with more than a decade of experience with specializing in a variety of technology topics, such as data centers, business intelligence, AI/ML, climate change and sustainability. His writing focuses on demystifying tech, tracking trends in the industry, and providing practical guidance to IT leaders and administrators.

Source is ComputerWeekly.com

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