This interview is with Sudheer Devaraju, Staff Solutions Architect at Walmart.

Sudheer Devaraju, Staff Solutions Architect, Walmart

Sudheer, could you please introduce yourself and tell us about your background in AI and Information Systems Research?

I’m Sudheer Devaraju, a seasoned expert in HR information systems, AI-driven HR tech, and enterprise architecture. With over 15 years of experience, I specialize in HRIS implementations, strategy, and large-scale system integrations.

I’ve authored books on HR information systems and contribute to research on AI-driven workforce analytics, automation, and enterprise data architecture. My work bridges HR technology, AI, and business transformation.

What first sparked your interest in this field and led you to where you are today?

My journey into HR information systems and AI-driven HR tech began with a deep curiosity about how technology could optimize workforce management. Early in my career, working with ERP and ATS platforms, I saw the inefficiencies in traditional HR processes.

This led me to specialize in Workday, where I implemented large-scale integrations and automation. Over time, I expanded into AI and data-driven HR analytics, shaping enterprise strategies that enhance workforce intelligence.

Can you share an example of a time you witnessed AI significantly improve a decision-making process within an HR context? What was the impact, and what key takeaways can HR professionals learn from it?

During a global Workday HRIS implementation for a Fortune 500 retailer, AI-driven predictive analytics transformed workforce planning. The company struggled with high attrition and inefficient hiring, leading to rising costs. By integrating AI with Workday, we analyzed turnover trends, engagement scores, and performance data to identify at-risk employees months in advance.

This proactive approach reduced attrition by 18%, saving $12 million annually in recruitment and training. Workforce planning became more efficient, cutting overtime costs and improving productivity. The key takeaway for HR professionals is that AI, when embedded into HRIS, enables data-driven decisions that prevent costly workforce issues before they arise.

In your view, what are some common misconceptions HR professionals might have about implementing AI solutions, and how can they overcome these misconceptions?

Many HR professionals assume that AI will replace human decision-making, but in reality, AI enhances it by providing data-driven insights. Another misconception is that AI implementation is too complex and expensive, when in fact, many HRIS platforms like Workday already offer built-in AI tools that require minimal customization.

To overcome these misconceptions, HR leaders should start with small, targeted AI applications, such as predictive attrition models or resume screening. Investing in AI literacy and cross-functional collaboration ensures that AI is seen as a strategic enabler, not a disruption.

You've emphasized the importance of data quality in AI. How can HR departments ensure their data is 'AI-ready' and what steps can they take to address potential biases in their existing data?

HR departments can ensure their data is AI-ready by focusing on accuracy, consistency, and completeness. Standardizing data inputs, reducing manual-entry errors, and integrating HRIS systems like Workday with real-time validation checks help maintain clean data.

To address bias, HR teams should conduct regular audits to detect patterns of discrimination in hiring, promotions, or pay equity. Using diverse training datasets, applying ethical AI frameworks, and involving cross-functional teams in model validation can minimize bias and promote fair decision-making.

Let's talk about the ethical implications. What advice would you give to HR leaders who are considering using AI for tasks like resume screening or performance evaluations to ensure fairness and mitigate bias?

HR leaders should ensure AI enhances fairness, not reinforces biases. First, they must audit training data to detect and correct historical biases in hiring and performance evaluations. AI models should be continuously monitored, with transparency in how decisions are made.

It’s also crucial to maintain a human oversight layer, ensuring that AI suggestions are reviewed, not blindly followed. Finally, HR teams should implement bias mitigation techniques such as anonymized résumé screening and diverse dataset training to promote equitable and ethical AI-driven decisions.

Looking ahead, what are some emerging trends in AI and Information Systems Research that you believe will have the most significant impact on HR in the next few years?

The future of AI in HR will be shaped by generative AI, personalized employee experiences, and ethical AI governance. Generative AI will streamline HR tasks like policy creation, job descriptions, and automated responses in HR chatbots, reducing administrative burden.

AI-driven personalized career pathing will help employees upskill based on their strengths and company needs. Additionally, explainable AI (XAI) will become critical, ensuring transparency in AI-driven HR decisions, fostering trust, and meeting compliance standards.

For HR professionals who are eager to incorporate AI into their work but may not have a deep technical background, what practical advice would you offer to get started?

HR professionals can start with AI-powered tools already embedded in HRIS platforms like Workday, focusing on automation and analytics. Begin with small, impactful use cases, such as AI-driven résumé screening, attrition prediction, or chatbot-assisted HR support.

Building AI literacy is key—HR leaders should take introductory AI courses and collaborate with data teams to understand AI’s capabilities and limitations. Lastly, engaging with vendors and industry peers helps in selecting AI solutions that align with HR goals without needing deep technical expertise.

What resources or learning opportunities would you recommend to HR professionals who want to stay updated on the latest advancements and best practices in AI for HR?

HR professionals should follow AI-focused HR conferences, like HR Tech and Workday Rising, for real-world applications. Online courses from Coursera, edX, and LinkedIn Learning offer beginner-friendly AI training tailored for HR.

Reading industry reports from Gartner, Deloitte, and SHRM helps track trends, while joining AI and HR communities on platforms like LinkedIn fosters knowledge sharing. Subscribing to newsletters like MIT Sloan’s AI & Work Update keeps professionals informed on best practices.

Thanks for sharing your knowledge and expertise. Is there anything else you'd like to add?

AI is transforming HR, but success depends on data quality, ethical implementation, and human oversight. HR professionals don’t need to be AI experts—they just need to understand its impact and apply it strategically. Staying curious, adaptable, and proactive will ensure HR remains a key driver of business success in the AI era.

—-

Interview Link:

Sudheer Devaraju, Staff Solutions Architect, Walmart, https://tech.walmart.com

Linkedin: https://www.linkedin.com/in/ssdevaraju/