The emergence of generative AI and foundation models has revolutionized the way businesses, across industries, operate at this current inflection point. This is especially true in the HR function, which has been pushed to the forefront of the new AI era. In a recent IBM Institute for Business Value (IBV) study, “CEO decision-making in the age of AI” , 36% of CEOs surveyed identified workforce and skills as the most important factor impacting their enterprise. Expanding the use of AI capabilities to augment human work across core HR processes in recruiting, retaining and developing skills and talent promises to deliver enterprise transformation and allow organizations to compete in a global market.

Download the “Enterprise generative AI: State of the market” report to learn how organizations can harness the power of generative AI

The future of HR and talent with generative AI

Traditionally, many HR processes, applications and technologies – from resume parsing, sourcing and screening, and candidate-skills matching – have benefited from and been closely aligned with automation and AI capabilities. In this new era, however, generative AI can deliver more using targeted advisors and the use cases that benefit from it will continue to expand. Human employees’ work on processes such as job description creation and intelligent search can now be augmented using data-driven insights and generative AI. This not only can transform HR processes and enhances business operations, but also empowers HR professionals to innovate and focus on higher value work.

For example, IBM’s HR function has worked to build the capabilities of its internal AI-driven digital assistant, AskHR, over the past six years to automate more than one-hundred processes and handle over one and a half million employee conversations per year. AskHR provides users with relevant information and has recently started pushing nudges to employees preparing for travel, sending weather alerts, and assisting with other routine processes. As AskHR continues to learn and expand its capabilities, human employees can look to save time on repetitive tasks and focus on more complex work.

Read the case study to learn how IBM HR is using AI assistants to transform its human resources business

The evolution of AI capabilities in use cases such as recruiting and acquisition has become increasingly sophisticated, managing the cost and time associated with hiring new employees. With the ability to segment requisitions based on role requirements, talent availability and other mandatory criteria, recruiters can potentially improve candidate skills matching, attract more diverse talent and increase their productivity.

Critical considerations for responsible AI adoption

While the possibilities are endless, the explosion of use cases that employ generative AI in HR also poses questions around misuse and the potential for bias. Widespread adoption and use of AI in HR applications can raise concerns about ethical implications and the impact on employee data and privacy. Before adopting AI into their processes, organizations should develop clear intentions for what responsible AI means to them, individually, and identify not only what they are willing to do, but also what they are unwilling to do. Failure to adopt an organizational strategy that supports the responsible use of AI may lead to heightened reputational, regulatory, legal, and even financial impact.

Therefore, responsible AI use is essential to success across the entire employee lifecycle and must be accounted for in the generative AI strategy. As such, HR leaders cannot simply rely AI to make decisions on its own. You should involve employees throughout the responsible use of AI to help gain trust and organizational buy-in.

To help integrate the responsible AI use in organizational culture, IBM recommends organizations follow these five pillars of AI ethics.

1. Explainability. Earning and maintaining trust by making it clear what went into recommendations, explaining how and why specific decisions are made, and being transparent on when employees are interacting with AI
2. Fairness. AI, with proper calibration, can assist humans in making choices to help counter human biases and promote inclusivity.  
3. Robustness. Guarding AI systems against adversarial threats and potential incursions.
4. Transparency promotes andreinforces trust by sharing information related to AI use with stakeholders of varying roles.
5. Privacy. AI systems should prioritize and safeguard employee privacy and data rights throughout the employee lifecycle, from training to production and governance.

Although we don’t know where the next level of generative AI will evolve, we encourage organizations to make these ethical pillars a foundational part of the culture. HR leaders set the tone. They must challenge the rest of the enterprise on the ethical implications of AI and data privacy. They must also be able to explain to their organization how they plan to attain AI use in an ethical and trustworthy manner.

Revisit the basics to reduce challenges

Listen to the podcast to dive into the daring frontier of artificial intelligence in HR and what HR leaders should be doing as companies integrate AI into their systems

There are many considerations in introducing AI into HR processes, leaving business leaders faced with decision overload on how, when, and where to use it to benefit their workforce. From questions about where to start, confirming you have the necessary skills and technologies, and using quality data, the decision-making process can be complex, overwhelming and confusing. Additionally, there is a lot of pressure to integrate AI into more and more use cases, improve productivity levels and create new business models. 

To simplify and determine the best course of action; however, you should go back to the basics, focusing on your strategy, operating model and people to help assess your organization’s AI readiness.

1. Establish a clear and actionable plan that combines both the business and AI strategies. Create specific objectives and goals with defined measurements for success. Understand your existing workforce and identify any skills gaps. Plan for gaps by reskilling current talent, restructuring job roles to incorporate AI into human workflows, automating routine tasks, and leveraging ecosystem partners.

• Evolve your operating model by reimagining the experience of your workforce as well as your customers to inform new ways of working. Visualize end-to-end processes and identify opportunities to apply AI and gain new efficiencies. Determine if legacy systems will integrate and use AIOps to address any IT issues.

• Invest in the talent and skills of your people. Create a culture of continuous learning. Success in the new AI era requires you put people, instead of technology, at the center of your strategy. Your human workforce is integral to the success of this digital transformation. Their expertise gives them unique insights into where automation and AI could augment performance. Foster an open communication forum for them to provide direct input and insights.

• Be prepared to ask and answer the hard questions. Generative AI is transforming the way we work globally and there are many hard questions HR leaders need to be able to answer to make sure people, processes and technology work together to create business value, deliver on business strategy and improve operational efficiency.

Learn the 3 things CEOs need to know and the 3 things they need to do now for success using generative AI

Challenges can become less of an issue by first aligning your organization’s overall business strategy with the generative AI strategy, defining end-to-end processes and workflows, and educating people and technologies on how everything will work together. No matter where you are in this process, IBM Consulting  can help you answer the hard questions, implement AI applications into your existing HR systems, accelerate digital transformation, and unlock workforce potential.