The scale and time pressures involved in effectively meeting HR goals today can feel insurmountable, even in moderate sized organizations. However, across industries, emerging technologies like artificial intelligence are helping to relieve this burden, freeing up time for HR professionals to focus on strategic initiatives. Analysts predict that AI augmentation will recover 6.2 billion hours of worker productivity by 2021 and that one in five workers engaged in mostly non-routine tasks will rely on AI to do a job by 2022. But you shouldn’t wait until then to prepare your team for AI in HR – there are steps you can take now.
Breaking down the basics of AI in HR
AI works like most objective and analytical human minds, but at a scale and speed that humans alone cannot match. By leveraging AI to emulate and augment current approaches to completing common manual HR tasks, more time will be available for HR professionals to focus on strategic, business-altering initiatives.
To achieve the necessary speed and scale for impact, most AI applications in HR depend in one way or another on competency frameworks. Competencies are taxonomies of knowledge, skills, abilities, and other attributes (KSAOs) required for the successful performance of jobs in an organization. KSAOs may include expected skills that the worker should have (such as education and experience) as well as personal characteristics of the worker (such as cognitive abilities, traits, and interests).
Starting the AI journey
As an HR leader considering how to leverage advancements in technology to deliver business growth, there are three key steps you must take to prepare your HR team for AI:
1. Create a foundation of standardized candidate scoring rules
In recruiting, the volume of online applications submitted per job can be greater than humans can objectively process, often reaching into the hundreds or thousands. However, there are rules that humans use to make decisions about candidates that leverage specific KSAOs. These rules, once defined and understood, can be coded, automated, and executed in an AI application. With this information, the application can identify desired employee attributes and then rank candidates who meet the selected qualifications for a final human decision.
2. Establish competency assessments that indicate when a worker has skills for a new role
While most organizations know that clear progression opportunities and successful job transitions are integral to effective talent management strategies, the reality is that most employees are left to their own devices. While high performing employees may be singled out for development opportunities, career coaching has historically been an extremely high-touch, human-driven process with a lack of tangible results. AI can now be applied to model employment patterns within organizations to benefit both employees and the business, suggesting new opportunities to workers when competency assessments indicate that the employee has the skills for a new role.
3. Match learning content to skills gaps
Typically, organizational learning is deployed in a one-size-fits-all approach or is determined by individual managers with funding from a discretionary budget. While learning management systems (LMS) allow more effective delivery and evolution of corporate-wide training, AI applications create opportunities for greater personalization. By leveraging AI to curate LMS content to match employee skills gaps or to tailor content selections to individual learning preferences, the perceived value and relevance of the education is increased. This can ultimately increase training adoption and skills growth across the workforce.
Each of these steps requires a strong foundation of competency frameworks. If you are an HR leader who wants to prepare your business to leverage AI, there is one essential activity you need to undertake now: audit the quality of your organization’s competency frameworks.