What do leaders worry about the most today? Is it technology? No—not technology itself, but flawed and ineffective technology. And what causes tech to fail? Dirty data centers—outdated, inefficient, and poorly managed infrastructure that drains resources, slows innovation, and increases security risks. To stay ahead, organisations must futureproof their data centers with AI, security, and sustainability goals. 

But this isn’t just a leadership and IT concern—it impacts HR too. In a digital-first workplace, agile and secure data is the backbone of People Analytics and HR tech platforms. HR relies heavily on HR Management Systems (HRMS) for payroll, performance tracking, and employee experience—handling sensitive personal and organisational data. 

A secure, well-managed data center ensures compliance with key regulations, preventing breaches and data loss. Moreover, AI-driven HR analytics depends on the efficient processing of vast workforce data, providing insights into employee engagement, attrition trends, and talent acquisition. This is even more critical in remote and hybrid workplaces, where cloud-based data centers empower HR to manage a distributed workforce through virtual onboarding, collaboration tools, and real-time engagement tracking. 

In the long run, HR’s role in driving ESG efforts also ties into data center sustainability, aiming to reduce their carbon footprint and attract eco-conscious talent must ensure that their data infrastructure aligns with sustainable business practices.  

The future of work isn’t just about technology—it’s about secure, efficient, and sustainable technology. And that starts with the right data center strategy. Recently, Niki Armstrong discussed about building a IT, Legal & HR synergy saying, “There are definitely tools with synergies that both HR and legal teams can use like an applicant tracking system, where the legal team needs to ensure privacy and data protection compliance. Some other tools like compliance training or learning and development platforms—present opportunities to integrate technology, and need to be careful with. There should also be careful reliance on AI-backed tools.”

Niki also underlined key concerns, “One major issue today is that AI generates massive amounts of data, and that data needs to be stored. Where does all that data go? Where are the data centers? There’s only a finite amount of space, so how do we ensure long-term sustainability? We can actually help governments meet their net-zero commitments—many of which are set for 2030 or 2035—by reducing space requirements. With our technology, there’s no disruptive upgrading, no downtime, and lower costs for cooling and energy emissions…One of the biggest challenges with traditional data centers is the sheer amount of e-waste they generate. And honestly, there aren’t a lot of places to put that waste. Space is limited, so the focus should be on doing more with less. By creating an all-flash data center, we can help governments and businesses meet sustainability goals while reducing their environmental footprint.”

While HR may not play a direct technical role in maintaining data centers, their guidance is crucial in identifying risks, ensuring data accuracy, and advocating for secure data practices. Here’s how: 

#1 Data governance & compliance

HR teams handle highly sensitive employee data (payroll, benefits, performance reviews, personal records). Their involvement in data protection policies ensures that data handling aligns with regulations like Saudi Arabia’s Personal Data Protection Law (PDPL), UAE’s Federal Decree by Law No. (45) of 2021 for Protection of Personal Data (PDP) or local labour laws to prevent breaches or misuse of employee data. These regulations permit the collection, storage, and processing of employee data while ensuring transparency, limited use, minimal data collection, and accuracy.

#2 Identifying risks in employee data management

HR can identify weaknesses in HRMS or payroll systems, such as unauthorized access, duplicate data, or outdated records. Through manual checks, they can detect inconsistencies and clean up redundant or incorrect employee information.

#3 Training employees on data safety

HR’s play a key role in educating employees about cybersecurity risks, phishing attacks, and best practices to prevent data leaks that could compromise the data center. They also enforce strict access controls, ensuring sensitive HR and employee data is only available to authorised personnel only.

#4 Advocating for secure HR tech integration 

When implementing new HRMS, AI-driven analytics, or cloud-based tools, HR must ensure these platforms are secure, compliant, and smoothly integrated with the organisation's data infrastructure. They work with IT teams to set up role-based access control, and multi-factor authentication for added security.

#5 Driving a culture of data integrity & ethical usage

HR sets policies and procedures to ensure employee data is used ethically, preventing bias in AI-driven decisions for hiring, promotions, and appraisals. They can also conduct regular audits to maintain data accuracy and remove outdated or incorrect records that could affect analytics and reporting.

Brian Sommer also emphasised establishing strong policies for AI-backed HR saying, "AI holds immense promise, but understanding its nuances and potential risks is essential. Implementing policies and measures to deter the use of generative AI tools can help safeguard against unethical practices and ensure fair competition in the job market,"

#6 Supporting business continuity & disaster recovery

HR ensures employee data is backed up securely in case of system failures or cyberattacks. They contribute to business continuity planning by ensuring that employee access to payroll and HR services remains uninterrupted even during data center disruptions.  

Ankit Abrol, Founder of Talenode identified the hidden costs of flawed data saying, "AI-driven decision-making promises to revolutionise HR, but it is only as good as the data powering it. In people dashboards, I have seen how poor data quality skews predictions, wastes resources, and erodes trust. Headcounts mismatch across departments, performance trends seem inconsistent, and engagement insights appear twisted. Instead of discussing strategy, the meeting devolves into a troubleshooting session. These aren’t limitations of the team and their quality of work, rather symptoms of poor data quality."

He emphasied data cleaning, "Let’s admit it—no one wakes up excited to deal with duplicates, blanks, and inconsistent dropdowns. It’s the grunt work of HR, repetitive and frustrating. Yet, it’s also the invisible backbone of everything HR Teams rely on, from compliance to analytics and decision-making. Without clean data, even the flashiest dashboards fail to deliver value."

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In conclusion, HR can play a key role in data security by ensuring accurate, compliant, and secure handling of employee information. Their collaboration with IT and legal teams can reduce risks, improve governance, compliances, and enhance overall data resilience.