The Future of HR software: How to Manage Your Employees in an AI-Powered World

• By Aftab Vasiwala
• 15-12-2021
• Artificial Intelligence

Artificial Intelligence (AI) for HR is in its beginning stages however, it could bring new efficiency and better efficiency in the basic human task of engaging with, training and keeping the most important of all resources, people.

For those who are an HR manager who is interested in the ways AI can help your business It is not necessary to know all the details of the HR software, technology and software that make up AI. Instead, look at AI in a commercial standpoint by asking yourself the following questions:

What is the commercial value of this initiative? What processes are you trying to help support?
What requirements must be put in place to be successful?

It is important to note that I did not mention "AI" in any of these questions. These questions require answers in relation to any technology you're trying to bring to your company. AI is not magical and needs to be understood as a tool to be used by humans, just like every other technology must be.

How AI Can Help HR
One approach to consider the ways in which AI can aid in the process is to think from the perspective of the employee's lifecycle. This is similar to how sales sees the lifecycle of a customer, since employees and potential employees are actually the clients of HR. The lifecycle of a customer can differ from industry to industry, and even between companies within the same industry. Consider the below lifecycle as a single instance. A map of the employee's life cycle will aid in answering the two first questions. In the next article, I'll explain the elements that must be in place to allow it to work.

In general, the majority of HR functions must do at least one of the following to satisfy the requirements of the company:

Sourcing:
Candidates need to know about the openings and the company you work for. That means reaching out to the right people and getting job descriptions and open positions in front of the correct people. AI helps make this process more efficient by providing job openings to most qualified candidates, resulting in better-suited applications for candidates. AI can programmatically purchase ads that are targeted to certain segments of the population, industries and interests. AI tools also can adjust the phrasing and tone of advertisements to increase the engagement.

Screening for candidates is labour-intensive and time-consuming. Text analytics tools that are basic (a type of AI) employ pattern-matching to find the necessary qualifications and skills, and also to filter out candidates who don't satisfy the minimum criteria. An alternative method is to utilize previous successful hires to determine applicants by comparing resumes against deeper patterns. This method relies on having a lot of resumes that show the qualities of candidates who are ideal as well as historical information on the work of those who have those qualifications.

Matching:
Determining the suitability of job candidates is a matter of assessing them in a variety of ways. Different types of assessments may be used to evaluate different factors like behaviour communications, risk-taking propensity, ability to learn and learning style as well as cognitive and technical capabilities. The importance of these kinds of assessments lies in knowing how the candidates interact with managers, supervisors as well as co-workers, and if their soft and hard abilities will be in sync with the requirements and expectations of the position, and team.

AI analyses the assessment of the candidate with the outcomes of previous or current employees who have the same job. For instance, one would not choose to put an introvert into the sales field or put a problem-solver who shuns formalities and rules in a job which requires discipline and adhering to the rules (for instance an accountant or auditor).

There are numerous suppliers that can help with this kind of matching and some even are industry-specific or have the ability to specialize in a particular role (such for assessing the capabilities and the style of an engineer) and others offer more general.

Management:
Just like an organization for sales manages sales pipelines of potential and prospects, the recruitment company manages the pipeline of talent. It's crucial to preserve the outcomes of assessments and interviews and to keep up-to-date with communications. An ideal candidate might be interested in the company (and the other way around) however the timing of the interview may not be the right one. Candidates evaluate opportunities by how they are handled during the process. An experience that is negative will affect not only the decision to take the job but also how they present their experiences to colleagues, peers, and to the wider market.

To make the process easier for candidates to improve the candidate experience, to improve the experience for candidates, HR staff should accept the receipt and swiftly send updates on the status of the application. This includes responding to routine questions and scheduling and managing assessment and interview processes. However, the large number of job applicants or the number of interactions created by difficult-to-fill jobs often make the task too expensive to complete manually. AI tools can assist in automating the process of completing these tasks. Chatbots can give routine answers to your questions, but they must be thoroughly tested and incorporate features that allow the escalation of the conversation to a human.

Training, on boarding and training and development of skills:
AI can help ensure better job satisfaction and retention, even after the hiring tasks have been completed and the candidate is given to the manager who hired them. The tools that measure and predict the skills required for a job, and eventual success also determine gaps in knowledge and abilities. E-learning programs that are customized can make up for those gaps. A variety of AI tools are in use to assist in on-the-job training. (For instance, call centres make use of AI simulations to teach new representatives at call centres.) Helper bots can give immediate answers to new employees. AI-powered tools to enhance the use of knowledge from organizations and experience will improve the satisfaction of employees and increase retention.

Recruiting, Screening and Hiring Training and Skill Development Day-to-Day Knowledge Work
Screening applicants using resume processes along with assessment of capabilities and skills as well as the identification of gaps in knowledge Reskilling opportunities, previous experience applying, intellectual proclivity and alignment of temperament.

The statistical models of emotional, academic and psychological makeup are aligned with job descriptions and models of applicants who have been successful.

Workforce management employs computer-generated learning techniques to anticipate customer service numbers based on variables like the need for skills, vacations, seasonal variations, impacts on demand due to weather conditions and shifts in demand because of promotions.

Personalized eLearning that adjusts to learning and thinking preferences.

Learning and remediation of knowledge via customized, personalised, live-time eLearning, which can quickly train people to take on new positions in their careers.
Training aids that are just-in-time and provide relevant information.
Augmented reality overlays serve as a virtual reference to physical tasks.
Review of performance using data-driven validation to decrease subjective judgement and increase career success as well as personal growth.

Collaboration spaces that facilitate curation workflows as well as automated taggers.

Semantic search is a way to enhance access to information (including search-based apps that combine unstructured and structured information sources and answer-to-question systems that detect employee intentions using machine learning.

Helper bots, configuration and transactions that allow the retrieval of information that is not structured help users navigate through complicated configuration of equipment and product and run routine queries on organized data sources.

What Needs to Be in Place to Make AI Work

As I stated in the previous paragraph, "AI is not magic." It must be understood. It is important to understand the business procedure. If humans cannot understand the process, then AI won't be able to provide value. Start by mapping your employee's lifecycle. How do you identify potential employees? What criteria do you use to screen candidates? What criteria do you use to evaluate the applicants? Find a consensus within your company regarding the current lifecycle in the most detailed way feasible. What are the obstructions? What happens when things get off course? What are the candidates' experiences? What could be improved? Do not think about technology, simply consider the way things are done and their impact on both external and internal people involved.

It is essential to know the issue you're trying to solve with AI. Don't begin with the technology and then look for problems that you can solve. Start by identifying your business's challenges and be as precise as you can when describing them. This is the reason why a map of the employee's lifecycle is essential. You can't automate something you don't fully understand and you shouldn't be able to make a mess. When you start looking at vendors, ask them to show you your scenarios and make use of cases instead of their own.

Another important aspect is the definition of success. What aspect of the process can be improved upon and what are the primary criteria? Take a look at what's being assessed in the present and ensure that people are aware of and trust these measurements, as well as any improvements that are promised. If they don't believe in the data, then they will not believe that the use of AI tools has resulted in any improvement. A high-quality data set is crucial. Find the data sources and ensure you try out vendor solutions using your own data and use instances.

One of the biggest red flags for HR professionals is the potential for bias in the programs. Request vendors to confirm in writing how they came up with their algorithms and validated their data. Be aware of biases that could lead the AI to make incorrect assumptions about the qualifications of candidates or accidentally sort out results based on certain demographics or applications.

AI has a vast array of potential applications in HR, ranging from taking the knowledge and experience of employees with long tenure to making knowledge more easily available to all employees in the company. AI-powered learning and knowledge management is an exciting area. Integrating AI into HR functions could provide a significant competitive advantage for your company. The earlier you begin to explore the potential benefits of AI, the quicker you'll reap the rewards.

Conclusion
AI is getting used in HR to automate repetitive, low-value tasks thus increasing the main target on more strategic work. AI tools automate common HR tasks like benefits management or handling common questions or requests through Chatbots, which are getting increasingly popular.