Artificial
Intelligence is a technology that is defining new-age paradigms of
operating business.it is a tool that automates and accomplishes most
of the low-value HR functions so that the larger focus can be driven
to the strategic scope of work. From recruitment to talent
management, AI has the power to transform employee experience
manifolds through speedy and accurate processing of large volumes of
data. In the era today, AI capabilities are scaling new heights and
driving the way we function.
The success of
any organization is dependent on how efficiently and effectively
people, process and technology combine and delivers value at optimum
cost. Artificial Intelligence helps to automate most of the back
office transactional work thereby enabling quick service delivery.
Table of Contents
Definition of Artificial Intelligence
Artificial
Intelligence is primarily a technological tool that aims to help us
solve cognitive issues and enabling machines to “think like
humans”.Its core components are-High speed computation through
complex machine algorithms in handling and processing huge data
volumes Today, Artificial Intelligence is driven by two fundamental
technologies – machine learning and deep learning.
Machine
Learning
This is a branch
of Artificial Intelligence that enables to create and make
predictions based on certain data pattern and hence help in decision
making accordingly. It is a concept that algorithms can learn through
recorded data without being programmed to do so. Key areas of use for
Machine learning in the HR context includes:
Study Employee Attrition: Find employees at high risk of attrition thereby enabling HR with predictions to engage in conversations and retain them
Personalized Feeds: Provide a personalized user experience through predictive analysis in recommending career paths and training programs.
Detecting anomaly in data: Identify events and observations that do not conform to a certain pattern in the database.
Deep Learning
It is an advanced
form of Machine Learning that comprehends a large volume of data
through neural network architecture. Deep learning defines and sets
up basic parameters around data and leaves the computer to learn on
its own through patterns. It is capable of handling much larger and
complex data. Key areas of use for deep learning in the HR context
includes:
Speech Identification: while it is difficult to comprehend varied human dialects and tonality, deep learning algorithms can recognize and respond to human voice inputs thereby ensuring problem resolutions.
Chatbots: NLP (Natural Language Processing) trains chatbots to understand human language, tone, and context and is emerging as a huge capability to automate HR service delivery.
Why choose
Artificial Intelligence for the HR function
Enhanced Employee Experience: With a high level of automation and a major focus on customer experience around the environment, employees also expect a useful and constructive experience when they come on board with personalized engagement. Consumer technologies are shaping employee experiences these days and they are looking for options on how they wished to be engaged and supported.
AI can be effectively embedded into the entire employee lifecycle, right from recruitment and onboarding, to HR service delivery and career pathing thereby providing a bespoke employee experience
Data-Driven decision making: While HR technology has been path-breaking and supported real-time data available to businesses, however many organizations still rely on manual methods to draw insights and decisions from data. This task is often aligned to data analysts and hence creates delays in drawing insights. Decisions also continue to be made with outdated or obsolete information.
AI enables HR teams to extract insights from data and give recommendations in real-time. AI also removes many of the common human biases and inconsistencies in a function that is as sensitive and crucial as Human Capital Management. Thus, decisions powered by Artificial Intelligence is potentially faster at scale and more data-informed and consistent, and unbiased.
Automation with Intelligence: Intelligent automation is a combination of AI with automation to enable machines to sense, understand, learn and act on its own or with little human assistance. Intelligent automation can not only perform manual tasks but also make intelligent insights and decisions as any human would do. Its capabilities can enable machines to understand processes and their deviations. Not only this but AI can be involved across all repetitive processes to boost efficiency, productivity, and drive innovation.
AI in Human Resources opens doors to limitless opportunities and is a huge intervention in creating path-breaking value for the Human Resources Professional.
Artificial
Intelligence includes cognitive engines that help employees arrive at
the day to day decisions at the workplace. Various such decisions and
tasks include:
Updating Employee Information: An employee can access his/her personal information including address, emergency contact number, organization details, and approval status of leaves, etc. Conversational AI can also help with analytical and KPI driven information e.g headcount, top performers, etc.
Training: In the current landscape of skill gaps and enhancement, AI is a game changer.AI is supporting in building personalized learning paths through conversational analytics eventually leading the L&D to new horizons.
Managers can conduct skill gap assessments and accordingly plan digital training opportunities. Conversational AI can help managers and employees track such training.
Recruitment: Cognitive solutions in Artificial Intelligence can help tap multiple data sources thereby enabling screening of candidates efficiently. In addition to this AI is also helping reduce Human Bias in shortlisting candidates. Large organizations are involving in creating AI-augmented Job Descriptions which are more inclusive and objective thereby enabling objective screening of candidates.
Automation of low-value tasks: Many small tasks that eventually consumes a lot of HR time. E.g. Onboarding processes, basic benefits and answering common request questions.AI can standardize and automate such responses and enabling shifting focus on the more strategic scope of work.
Employee Engagement: Artificial Intelligence is a strong catalyst in establishing how employees and businesses interact.AI can strongly conduct employee engagement tasks like intelligent surveys, real-time feedback platforms, rewards and recognitions to name a few.
Artificial intelligence in Human Capital Management: AI is playing a crucial role in integrating major HR functions thereby overhauling the entire pedigree of employee experience. It is contributing to building talent processes to reduce employee turnover and manage key areas like performance management, workforce planning, people analytics, career-pathing and virtual assistance for self-service.
Barriers to adopting AI in HR
Lack of Skilled Talent: It can be very expensive considering the dearth of skilled people on the technology for integrating HR functions.
Privacy Concern: Since HR data is quite confidential and needs to be maintained securely. Data security is a huge concern in amalgamating HR functions through Artificial Intelligence.
Ongoing Maintenance: Similar to other technologies. Constant reviews and up-gradations are a necessary part of Artificial Intelligence making it a tedious maintenance process.
Complex Integrating capabilities: Data availability is limited due to shifting towards SAAS (Software as a Service) hence limiting the scope of integrating the HR functions technologically with full bandwidth.
Points to consider in deploying AI in HR
With technology
evolving at a fast pace, organizations need to be exercising the AI
systems with caution. Following points are key to consider while
managing AI systems effectively:
Finding accurate data sets: Real-time and accurate data is very important for effective AI results. Something free from bias and all-encompassing. So first get the right set of data and then clear the objective of output driven.
Using the right AI implementation: AI environment is a lot different from other IT environments. It requires specific skills and methodologies for implementation. Make sure in being specific about collecting the right data sources and cleaning and curating the same.
Clarity: It is very important to understand and know the insights to be driven. Hence, there ought to be clarity and training on knowing the correct patterns to study and act accordingly.
Eliminate Bias: AI can deliver accurate and unbiased results based on the algorithms and logics fed in the system. Ensure the accuracy of data and always remember, AI will do what you want it to do and will not decide things for you.
Final Thought
AI-based HR interventions can strongly raise employee productivity and help HR professionals boost employee performance and experience. HR applications powered by AI can analyze, predict and support decision making for key stakeholders. Adopt AI solutions that you’re your business needs and fit in with the culture of your organization and develop the required Digital maps. Employees will be eventually impacted by the AI function in multiple ways and can claim to have a fast-paced and accurate user experience. Therefore it is quite crucial to focus on employee needs and know the possible outcomes that you are expecting.
HR data privacy
is also a crucial challenge in AI development. Employee data needs to
be protected and appropriate governance guidelines need to be set up
in administering AI-driven HR interventions. The guidelines should
not just address overall technical and data inputting processes but
also varied legal aspects.
A strong AI system will foster a deeper understanding of people’s behaviour and pattern. By consolidating and comprehensively analyzing employee, mood, and intentions on different digital platforms human behaviour can be simulated and validated for useful employee experience.
Astute Human Resource Professional with 13 years of experience and a strong focus on details.Sound exposure to Talent Management, Performance Appraisal, Employee Engagement, Rewards, and Recognition & Research
Jyoti Kapoor