Upskilling HR: Building Future-Ready Workforces Through Intelligent Support

Working in human resources, you're used to handling day-to-day tasks like managing PTO requests and sending out benefit election forms, while still being expected to drive culture, engagement, and change. 

AI is a force multiplier for enterprise HR teams. As an HR leader, learning to use it to automate routine work can allow you to take on a more strategic, people-centric role. 

Think: more time on change management and workforce planning and less time manually screening hundreds of job candidate referrals, drafting employee verification letters, and sending out training reminders. 

Upskilling on AI can also position enterprise HR leaders to guide their organizations through a broader digital transformation. But it’s only possible when they have support from the entire C-suite. Enterprises need to invest in upskilling by providing access to the right AI tools and the time to learn how to use them effectively. When that support is missing, progress slows, skills gaps widen, and opportunities to improve employee engagement and productivity are left on the table.

But despite AI’s potential, research from the Society for Human Resource Management (SHRM) shows gaps in AI adoption and understanding across HR leadership:

• 43% of HR leaders have limited or no theoretical knowledge of AI.
• 62% have had limited interactions with AI apps both inside and outside their work.

But those gaps represent opportunities. As AI becomes more embedded across the enterprise, HR has the chance to shape how AI is adopted and experienced — and it starts with intentional, organization-wide AI upskilling.

The enterprise upskilling imperative

Compared to HR at many small businesses, enterprise HR faces unique pressures that make upskilling even more important. It's not easy complying with regional regulations, navigating cultural differences, and juggling employee support at enterprise scale.

AI can help ease this workload, but if HR professionals don't have the skills to work effectively with AI, they risk falling behind as new tools and workflows emerge. 

HR leaders also need to help their companies shape how AI tools are used. Instead of just throwing AI into the mix, it needs to be implemented compliantly, ethically, and in ways that make employees feel empowered to do their jobs better. But to lead this transformation and maintain relevancy, HR leaders need to upskill on AI themselves. 

That upskilling then puts you in a better position to add value to the enterprise. Gaining competency in using AI training tools then makes it more practical to design upskilling and reskilling programs for other employees. Or learning how to automate onboarding tasks means you can focus on designing a better onboarding experience. For example, having new hires spend more time shadowing other teams to see how they function.

Upskilling vs. reskilling

Upskilling is the process of improving existing skills, or learning new ones that apply to your current job. Reskilling means learning new skills for a new role or career.

What does that look like for HR?

• Upskilling: HR teams are already pretty familiar with using applicant tracking systems (ATS) and human resources information systems (HRIS). But as AI evolves and changes how HR professionals and employees interact with these tools, HR leadership needs to level up their knowledge to get the most out of these systems. 

Example: An in-house recruiter learning how to work with AI agents that integrate with recruitment software or interpret workforce analytics and performance data. AI agents can streamline candidate tracking and onboarding, which are critical parts of everyday enterprise workflows. By learning how to work with this new technology, the recruiter can keep pace and even excel in their current — but evolving — role.

• Reskilling: HR teams may also need to prepare for entirely new types of roles as AI takes over certain administrative or transactional tasks. In this case, reskilling could mean helping HR professionals transition into more strategic positions that didn’t previously exist in the same way. 

Example: An HR operations specialist might train to become an AI workflow manager or people analytics partner, learning how to oversee AI agents, interpret advanced workforce insights, and advise leadership on talent decisions. This kind of reskilling enables employees to move into new roles that support the organization’s changing needs, rather than simply adapting their existing responsibilities.

Challenges blocking effective HR upskilling in enterprises

Many HR leaders agree that upskilling is important, but the tough part is getting upskilling initiatives off the ground in large, busy enterprises where many HR teams are already stretched thin. A few common culprits often stall HR upskilling efforts:

• Fragmented technology foundations: When HR data, learning tools, and workflows are spread across disconnected systems, it’s difficult to create an upskilling program that’s cohesive, measurable, or tied to real outcomes.
• One-size-fits-all learning approaches: Limited visibility into individual skill gaps often results in generic training that doesn’t reflect how different HR roles actually work day to day.
• Weak signals from leadership: When learning is treated as optional or secondary, adoption drops quickly, even if resources technically exist.
• Poor connection to real work: Training that isn’t anchored to live HR workflows tends to feel theoretical, which makes it easier to ignore when priorities pile up.

To move from intention to impact, enterprise HR teams have to work through a few specific blockers that show up repeatedly:

Competing priorities and limited learning time

HR professionals are juggling a wide range of day-to-day responsibilities:

• Answering benefit policy questions
• Processing time-off requests 
• Managing onboarding workflows

While AI can ease these constraints, HR leaders currently have little bandwidth to develop their own skills to work more effectively with AI tools. This can make it hard to get the ball rolling: Upskilling is necessary to make AI useful, but the pressure of daily work makes it hard to get started.

HR's role centers on supporting other employees' growth, but that often comes at the expense of HR staff's own development. Instead, they need protected time and organizational prioritization for their own upskilling.

Gaps in access domain-relevant learning resources

Most enterprise learning AI programs cater to executives or those in technical roles, not HR. That leaves HR employees with limited opportunities for specialized skill development in areas like data analytics or using AI for more strategic workforce development. 

Even when learning content is available for HR, the material is often too broad or disconnected from real HR challenges, which leads to less practical upskilling. Instead, HR teams need AI training for the specific tools and workflows they use.

Cultural and structural barriers to growth

Although HR's role is changing, many enterprises still view HR as a support function. If enterprises don’t prioritize HR as a forward-looking, value-added role, professional development and experimentation are easier to deprioritize.

These cultural barriers also tend to coincide with structural barriers, like enterprises having fragmented or outdated HR systems that aren't equipped for digital transformation.

Essential skills HR leaders need to drive AI transformation

To overcome these hurdles, HR leaders need to take the reins. They play a central role in how AI is introduced, adopted, and trusted across the enterprise. That means they’re often the ones expected to translate strategy into day-to-day reality for employees. 

That starts with building a set of core capabilities that help HR teams move from operational support to strategic leaders in an AI-enabled organization:

• Data literacy and workforce analytics
• Change management and communication
• Strategic business acumen
• AI ethics and governance
• Digital fluency and tool integration
• Conflict resolution
• Learning and development design

To be clear, these skills are foundational. While they may not be “AI skills,” they’re what you’ll need as an HR leader to be able to drive meaningful, impactful digital transformation in your organization.

How AI transforms HR upskilling

While HR leaders need to get more comfortable using AI tools, AI is also what provides the catalyst for more continuous, contextual learning. So there can be a positive feedback loop that helps HR professionals improve in real time. Here’s how:

Personalized learning pathways for HR professionals

AI tools can tailor employee upskilling plans to each HR role by analyzing performance data, career goals, and current skill gaps.

That could look like AI recommending workforce analytics training to HR personnel, but instead of suggesting the same training to each team member, the specific modules could be tailored to each person’s current skills and goals. AI might also recommend an AI ethics course for a chief human resources officer, recognizing their unique role in policy development.

Learning and career development aren't one-size-fits-all, and AI can help provide more relevant recommendations.

Proactive resource delivery for just-in-time learning

AI can also proactively identify and deliver learning moments. For teams in a region that passes new labor laws, AI could surface microlearning resources about these new laws. Or, if a company deploys new HR tech, an AI platform could surface training modules so all HR employees get up to speed.

This contrasts with the old approach where HR professionals review learning portals on their own and manually search for relevant resources. With AI, the process is faster and more engaging because the recommendations are personalized and relevant.

Data-driven insights for continuous HR development

AI dashboards can reveal team-level learning trends, adoption rates, and emerging skill gaps within the HR function itself. This means that HR leaders can more easily assess progress and step in as needed on a more strategic level.

Suppose the analytics suggest emerging skills gaps in areas like data literacy or change management. That could prompt HR leaders to coordinate with finance and other C-suite members to gain buy-in for investing in these skills. 

The result? Your HR team is better prepared to handle privacy, bias, and adoption challenges as automation scales. 

That also helps achieve broader organizational performance goals. If employees are hesitant to adopt tools due to privacy concerns, for example, that can hamper digital transformation efforts. So, HR needs to be able to address these concerns with employees and make them feel more comfortable working with new tools.

Best practices for building a future-ready HR function

Turning AI upskilling into lasting impact requires more than encouragement. It takes visible leadership, learning embedded into real work, and clear signals that capability building matters. 

Here are a few best practices to help you operationalize AI upskilling within your HR department in a way that sets up digital transformation enterprise-wide.

Demonstrate leadership with HR upskilling

HR leaders should chart the way as learners, running hands-on upskilling pilots with real HR tools — not theoretical training examples. When leaders experiment with AI in areas like workforce analytics, recruiting workflows, or employee support, they can point to concrete wins and practical use cases.

That visibility matters. HR leaders often need executive advocacy to secure time, budget, and tools for capability building. Demonstrating personal progress and tangible outcomes makes those conversations easier and more credible.

Upskilling efforts are also more likely to gain traction when they align with broader enterprise priorities. If leadership is focused on becoming more data-driven or improving operational efficiency, positioning HR upskilling around data literacy or AI adoption directly supports those goals.

Integrate learning into HR’s daily workflow

Learning sticks when it happens in the flow of work. Rather than relying solely on formal training sessions, HR teams can build skills by using AI directly within everyday workflows.

AI assistants can surface process guidance, insights, or policy updates in real time as HR employees work. In recruiting, that might mean using an AI assistant to track candidate progress and hiring metrics, helping HR teams practice data analysis as part of their daily tasks. In onboarding, AI can guide new hires to the right forms or benefits information while HR teams build digital fluency and reclaim time for higher-value work.

The same approach applies to case management. Automating routine tasks like time-off requests reduces friction for employees and gives HR teams space to focus on more strategic decisions, such as evaluating policy changes or retention trends. When learning is embedded this way, adoption increases because it feels useful, immediate, and relevant.

Measure what matters in HR capability building

To treat upskilling as a strategic investment, HR leaders need to measure their own progress with the same rigor they apply elsewhere. AI makes that possible by providing clear signals about how skills are developing over time.

Keep track of useful KPIs like:

• Time-to-skill for emerging tools
• HR technology adoption rates
• Percentage of HR staff meeting data literacy goals

As HR team members build confidence interpreting AI-driven insights and outputs, they become better equipped to advise managers on how to refine their own learning programs. That also helps HR leaders tie professional development directly to business goals and creates real-time feedback loops: If adoption stalls or skill development lags, leaders can adjust training approaches quickly and see whether those changes improve outcomes.

Over time, this closes the gap between learning effort and business impact, helping HR tie capability building directly to enterprise performance.

Enable upskilling with Moveworks

AI upskilling is now foundational to HR’s ability to lead transformation, not just support it.  Moveworks helps upskill HR teams by taking repetitive support work off their plate and making them AI- and data‑savvy.

It automates FAQs, routing, and common HR workflows so HR can focus on strategy, while dashboards and EX insights build HR’s fluency in AI, analytics, and change management—turning HR into a proactive, metrics‑driven partner rather than a ticket desk.

Moveworks brings this approach to HR with an agentic AI Assistant platform that integrates with your existing HR technology stack to:

• Provide employees with instant answers to HR policy and process questions, freeing up HR professionals to focus on strategic growth and development.
• Give HR leaders get rich analytics on HR demand and friction points, not just ticket counts to help HR understand skill gaps, burnout risks, and EX pain points across the workforce
• Deliver learning nudges, AI training resources, and policy changes at scale, reinforcing your HR teams AI leadership

By reducing administrative drag and making development more practical, Moveworks helps HR leaders focus on what matters most: building a future-ready workforce that can navigate ongoing transformation with confidence.

Learn how Moveworks helps enterprise HR teams lead AI-driven workforce transformation.