How Leaders Can Navigate the Future of AI in HR
Find out why AI will not replace HR professionals but streamline HR operations and protect employee data.
Artificial intelligence (AI) is changing HR by improving employee experiences and organization operations. Geoffrey Peterson, VP of data and analytics at Alight Solutions, discusses critical areas where AI can enhance HR practices and offers guidance to HR leaders on effectively leveraging its potential.
Artificial intelligence (AI) permeates many facets of the modern enterprise, transforming how businesses function and interact with their employees and customers. The Human Resources (HR) organization has not escaped this trend, where leaders are being pushed to demonstrate how AI is reshaping processes and enhancing employee experiences –all while coming up to speed on how to be AI intrapreneurs and how to ensure AI is being introduced responsibly.
For example, Gartner reports that “By 2025, 60% of enterprise organizations will adopt a responsible AI framework for their HR technology, and in turn, achieve a greater employee experience and trust in the organization.”
However, amidst the promise of AI-driven efficiencies and innovations, there lies a complex interplay of both potential and peril that demands careful consideration and management. Though AI brings new and exciting capabilities to HR, it also inherits the risks and governance needs inherent to all software, as well as a few additional ones.
For example, while AI might be alluring for HR functions like recruitment and performance management to automate resume or performance reviews, errors or bad outputs in these domains can have unacceptable real-world consequences.
As HR executives navigate this landscape, it’s crucial to separate fact from fiction and understand how to leverage AI effectively to enhance the employee experience.
Dispelling 5 Myths About AI in HR
Before diving into the practical applications of AI in HR, it’s essential to debunk some common myths surrounding its implementation:
1. AI will replace HR professionals
Contrary to popular concerns, AI is not poised to replace HR professionals. Current AI technology isn’t autonomous intelligence, it is scaled intelligence. This means every process that is automated or augmented with AI still needs to have some number of humans who are in the loop to monitor its actions and insights for correctness and quality.
Additionally, many HR tasks cannot be “AI-ed away,” including strategic planning, relationship management, and ensuring ethical HR practices. An HR professional’s ability to understand psychological factors, foster workplace diversity, maintain data security, provide clear communication, relate to employees on a human level, and monitor AI systems! cannot be fully replicated by AI.
2. AI decision-making is a Black Box
Some AI algorithms are opaque, but there are many (e.g., linear regressions, decision trees) whose decision-making can be more easily understood. By considering the surrounding business context of a proposed use case – including how explainable good/ bad decisions will need to be – the right AI algorithms can be chosen for an application that offers the right level of understandability.
3. Employee data security is at risk with AI
AI is, ultimately, just software. Companies with robust cybersecurity and third-party management programs already have the mechanisms needed to manage the risks related to employee data security.
A specific scenario that seems to be causing recent concern is that of SaaS vendors training AI models using aggregated, anonymized employee data from across their client base. However, this is not a new risk – SaaS vendors have used aggregated employee data for a long time to understand the performance of their products and make improvements – and the recent focus on this happening with AI models is misplaced.
4. It is possible for AI to be bias-free
All AI produces bad output occasionally, and when those bad outputs concentrate in certain parts of the user population, that is called bias. All models have the bias of some form—if you think yours doesn’t, you just haven’t found it yet.
It is important to understand what types of bias you are especially worried about and continuously check and monitor for those. You may not care if “bad outputs” concentrate on people whose first names start with “A,” but you may care if “bad outputs” concentrate only on older or younger users of the AI system.
5. HR teams need numerous complex AI use cases to be successful
Success in AI implementation does not hinge on the number of use cases but rather on their quality and alignment with organizational objectives. Any meaningful implementation of an AI system will be a large undertaking requiring significant investment (both to implement and to monitor on an ongoing basis). Achieving impact with two to three new use cases is ambitious and an enormous win for most organizations.
See More: Balancing AI Bias with Ethical Data Collection
Understanding AI in HR
AI encompasses various techniques that enable machines to simulate human intelligence. In HR, AI manifests in different forms, from basic algorithms used in recruiting software to complex machine learning models that personalize the employee experience. It’s sometimes helpful to also include robotic process automation (RPA) under the AI umbrella since the objectives (automating repetitive tasks) are the same, and it’s often a precursor to AI-based automation.
There are several key areas where AI can drive substantial improvements in HR practices; these include:
- Personalization: AI can tailor digital experiences to individual employee needs and preferences, whether through personalized onboarding experiences, benefits recommendations, nudges, or learning paths.
- Assistance: AI-powered virtual assistants and chatbots provide immediate support to employees, answering questions and directing them to resources.
- Recommendations: AI analyzes data to offer guidance in complex circumstances, such as health plan options during enrollment or development courses based on career goals.
- Insights: By analyzing data from various sources, AI provides insights into employee sentiment, experience hotspot areas that need improvement, and the effectiveness of HR initiatives.
- Operations: AI automates repetitive tasks like document processing and scheduling, creating faster turn-around times for employees and allowing HR professionals to focus on more strategic initiatives.
As organizations embark on their AI journey in HR, it’s essential to manage expectations and adopt a measured approach. Success relies on the rigorous measurement of performance, error rates, biases, and business impact designed around humans-in-the-loop that can monitor and improve any AI solutions. This journey requires time, experimentation, robust controls and governance to ensure ethical and effective use of AI in enhancing the employee experience.
How can AI revolutionize HR processes, employee experiences, and the broader corporate environment? Let us know on Facebook, X, and LinkedIn. We’d love to hear from you!
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