AI-Powered Transformation Will Lead the Shift to a More Productive Future

A pivotal transformation is taking place across the world of work as artificial intelligence is integrated into HR systems. Business leaders consider AI implementation an imperative for success, but it is still unclear what the impact will be on jobs, work, and skills. HR will play an important role in navigating the disruption to the workplace as organizations move from experimentation to full adoption of AI tools.

Tech companies like ServiceNow, which operates a leading workflow automation platform, will also be critical in the seismic shift to AI. ServiceNow is focused on incorporating the newest AI innovations into enterprise workflows. The company’s latest platform release, named Xanadu, adds a batch of new features, including AI agents that work autonomously in the background handling HR tasks, managing processes, and collaborating with employees, rather than just serving them.

SHRM recently met with two ServiceNow executives at the HR Technology Conference in Las Vegas. Heather Jerrehian, vice president of product management for employee workflows, and Allan Sabol, senior director of product management, sat down with SHRM to share their insights on the challenges of AI implementation, HR use cases for the evolving technology, and the latest buzz around AI agents.

SHRM: What are the biggest challenges HR leaders face today when it comes to implementing AI in the workplace?

Jerrehian:  Many organizations are integrating their people and business strategies, with HR playing a key role in driving this transformation. A major challenge, however, is that organizations often overlook the importance of change management. Engaging employees so that they understand what is in it for them is crucial. AI can help create customized experiences, but gaining employee buy-in is essential to successfully leveraging this technology.

Additionally, as AI-driven systems increasingly handle sensitive employee data, HR leaders must navigate complex privacy and ethical concerns. Ensuring transparency, fairness, and accountability in AI implementations is critical to maintaining trust while leveraging AI’s potential.  

Sabol: It’s been a big problem for years—there are too many disparate HR systems, employees can’t find what they are looking for, they get frustrated and give up. Some employers say that to have great employee experience, you can’t promote HR self-service. But those two things go hand in hand. If an employee can ask AI for what they need and actually get it quickly, without logging in to another system and making a service request, they’re happy and it will drive down costs.

Another challenge that HR has is that adopting bold new tech is perceived as risky. But HR leaders are the ones driving the change in a lot of organizations. They want to improve employee experience, but they still have questions about AI bias, hallucinations, the legal risks. They are struggling with that balance, but the majority are excited about GenAI [generative AI] and the impact it will have on achieving business goals.

SHRM: What are some of the key HR use cases for GenAI?

Sabol: We know that HR leaders are looking for a unified conversational experience, along with seamless data integration, support for employees across departments, and a solution that knows when not to engage—such as for sensitive issues like employee relations.

One of the most common early use cases we’re seeing HR leaders adopt is using GenAI for employee self-service—giving employees the ability to ask a question in natural language and get an answer back that is clear, personalized, and actionable. For example, if an employee asks, “How many days of PTO do I have?” the GenAI-powered chatbot should be able to respond with the correct answer and then ask if the employee would like to request PTO and, if yes, make the request. And this should work on all devices.

In a similar sense, generative AI can also be used to improve employee search. Many organizations have intranets or employee portals containing tons of information that can be difficult and time-consuming to sift through. GenAI-powered search can surface actionable, direct answers to employee questions in the form of steps, guidelines, or summaries.

We’re also seeing GenAI support talent acquisition and development. For example, in recruiting, GenAI can be used to draft interview questions tailored to a job or review and extract skills from job descriptions, resumes, learning content, and other data sources. All of this frees HR’s time to focus on interviews, evaluations, and the human aspects of recruiting, such as relationship-building.

SHRM: We’re hearing a lot more about agentic AI lately. What is that and what is its potential for disruption at work?

Sabol: Agentic AI is the logical extension of generative AI. GenAI, powered by large language models [LLMs], is able to understand human language and intent, compose a response, and write it back to the prompter in a way that they can understand. Agentic AI goes beyond conversational ability. AI agents will be able to complete tasks and achieve goals. They will become virtual members of a team to help the rest of the team be more productive and focus on higher value items. It’s what’s next in the AI evolution.

A possible example of where this could be used is interview scheduling. Every employer I know has a frustration with interview scheduling. Organizations have attempted to automate the interview scheduling process, but it’s been difficult to do because there are so many human tasks that traditional automation can’t solve—a person has to reach out to the executive’s assistant, for example, to unblock a time on the calendar for an interview, or get a hiring manager to switch a meeting to accommodate a candidate’s availability. Agentic AI solves this. An AI agent will be able to reach out to anyone and have conversations in real time to set up interviews.

Jerrehian: Employee surveys are another great use case for agentic AI. With a human in the loop, imagine autonomous agents helping to come up with the questions, deploying the survey, sending reminders to complete the survey, and summarizing and analyzing the vast amounts of data that comes back. This is game-changing as it allows people to spend more time understanding and taking action on the data than compiling the data itself.

Sabol: Practical examples really help HR understand the use cases. Think about managers. Managers want to be better people leaders, but they get busy and sometimes forget to do key things for their employees. You can have an AI agent that is essentially an assistant to the manager to help the manager be a better people leader. It can remind them when it’s time to recognize employees, schedule performance management check-ins, and come away with action items from those meetings. There are so many applications for agentic AI.              

SHRM: What can leaders do today to prepare their workforce for the future of AI?

Jerrehian: We know that the impact of AI on the economy and on the workforce will be tremendous. Some tasks will be augmented, and some will be automated. Hours of work will be saved each week. Because of that, organizations are starting to think about their upskilling, reskilling, and redeployment strategies. How do you repurpose that saved time? Are you helping workers learn with traditional learning, or mentorship, or by offering a project or gig through an internal marketplace?

We know this is not easy for employers, that it is a step-by-step process, but the important thing is to get started. Employers will need to begin building a tech-enabled skills architecture.

By moving away from traditional job titles and roles to a more dynamic, skills-based approach, leaders can create more agility in their workforce. This enables employees to transition between projects and roles more fluidly, optimizing the deployment of talent as AI reshapes job functions.

Leaders must also create a culture of continuous learning, offering personalized, self-directed learning journeys that empower employees to upskill and reskill for the evolving demands of an AI-driven workplace. This includes prioritizing digital literacy and AI-related skills across the organization.

Most importantly, leaders should emphasize that AI is a tool to augment human capabilities, not replace them. As we allow the machines to do what they do best—the mundane repetitive tasks—it frees us up to focus on work that is innately human, like creativity, problem-solving, and collaboration. Taking a human-centered approach can alleviate fears around AI.

SHRM: What else is top of mind at ServiceNow?

Sabol: We’ve really doubled down on GenAI and agentic AI, because this is what customers have told us they want. They want GenAI to drive business transformation; it’s a C-suite priority. Our most recent Xanadu platform launch included 350 innovations, including LLM-based proactive prompts that engage employees and managers with timely reminders to complete tasks.

Jerrehian: We’re also focusing on the end-to-end employee experience. Our goal is to support employees at every stage of their career journey: from hire to retire. For example, at HR Tech, we introduced new capabilities within the talent development and employee journey management modules. Leader Hub, a new feature within talent development, gives leaders comprehensive and consolidated workforce insights that can be used to inform talent strategies. With new updates to the employee journey management’s analytics center, leaders gain access to data to help them understand where employees are on unique career journeys—whether it’s preparing for a promotion, coming back from parental leave, or onboarding—to provide timely guidance in the flow of work.