In the global economy, organizations compete with each other, mainly on the basis of talent in the organization. Talent management, therefore, becomes the top priority for the leaders of any organization. Leading human resource institutes defines talent management as the company’s ability to acquire, develop and retain high performing individuals to accomplish current and future business goals and implement strategic initiatives to improve the practices of talent management.
In most organizations, Talent Management is broadly divided into three main stages of an employees’ lifecycle in an organization. The first stage is called talent acquisition, wherein organizations attract, identify, and recruit high potential individuals for open positions in the company, this stage also includes effective onboarding, which reduces time to be effective. The second stage is known as talent development, wherein organizations nurture and grow their employee skills for the current and future needs such as improving productivity, revenue, margins, markets share, and achieving a higher growth rate or, importantly, leadership succession. The final stage is talent retention, wherein organizations motivate high performers to stay engaged with the organization and, in turn, reduces talent attrition, thereby reducing the impact on organization performance.
While these are broad stages in any organization, there are no one-size-fits-all guidelines for talent management, and different organizations deploy various practices, strategies for effective talent management. Technology-enabled talent management is one such strategy that, over the past decade, almost all human resource functions of the organizations are experimenting with. Many tools use Social networks, Mobility, Analytics, and Cloud technologies (also referred to as SMAC technologies), and Artificial Intelligence (AI) to advance and be effective.
Technology-enabled Talent management is the key driver of change in current and future human resource management. Given Talent management is the heart of HR, now lies at the intersection of human and technology or digital journey in any organization. HR that is not digitized is not adding full value to the business, the current and future of HR lie in the power of digitalization to improve speed, quality, reduce costs, and biased. Business, and HR leaders understand and assimilate the latest emerging technologies for organizational advantage.
That said, many technologies look promising from an efficiency and effectiveness perspective but need to be evaluated given organizational landscape, need, and broader integration set up. One such technology that is finding wide applications in numerous areas of HR is AI or Machine Learning. AI offers the opportunity to reduce mundane, repeatable work and tasks to machines, giving more time to do value-adding work for humans. This is the biggest advantage of AI applications for talent management it helps to streamline HR processes.
Learning and development is time-consuming and is not scalable, how can it be not straining. With AI, organizations are able to break free from traditional eLearning systems and outdated Learning Management Systems and move toward more immers
Age of experience: why does Employee Experience matter?
Employee experience has emerged as a key strategic word in the HR space lately, but let’s not be confused for it to be just a new word or concept for an old term. Many organizations have explored the critical link between better employee experience with high engagement and have seen revenue, overall growth, retention and greater ownership. Now HR functions are designing strategies and exploring digital tools to compete in the market to attract and retain talents and provide better employee experiences.
AI in Talent Acquisition can create engaged candidates and satisfied hiring managers
The adoption of AI can be beneficial and can make recruitment easier, more accurate and efficient. Some noticeable areas are saving recruiters time by automating high volume tasks through AI and improving quality of hire through standardized job matching with Machine learning tools. With AI tools taking care of preliminary sourcing, screening, skill-matching tasks, human recruiters can channelize their energy into converting the right candidates into hires. The emotional connect that is built with a candidate predominates how they feel about the organization and their roles. Ironically, some non-human intervention in the form of AI can improve this emotional predisposition and alignment.
Making Learning more engaging, fun as well as just in time.
Given experience is the centre of everything for employees, learning plays an important aspect in providing lifelong learning a candidate for change in traditional learning mechanism. Learning and development is time-consuming and is not scalable, how can it be not straining.
With AI, organizations are able to break free from traditional eLearning systems and outdated Learning Management Systems and move toward more immersive, just in time, curated learning pathways to utilize Learning Experience Platforms.
Gamified, immersive, learner-oriented experiential Augmented Reality and Virtual Reality enabled content is changing how we look at organizational learning. It molds as per the learning requirement and is no longer set for all in one way. It takes charge of what they learn, when and how they learn by adopting the modules, learner’s pace, and format of learning while still adhering to business strategies– all this while creating a superior learner experience.
Change management in implementing AI and other digital tools.
As Organizations increasingly adopt AI technology, managing the transformation and transition should also be on top of their mind. To make sure investments in AI are realized well, it’s important to pay attention to these four people issues:
Employees as your stakeholders, prepare them for change: For any transformation including AI and digital, to be successful, organizational cultural support is very important. Organizations that focus on how people will think, feel, and behave in light of the change find their transformations successful, and adoption rates are higher.
Continuous Education: Starting education early with a tailored approach creates a better organizational experience. It can provide employees (stakeholders here) with the value that AI will offer, this sets clear expectations when it comes to human: technology interface. It’s important that people throughout the organization understand the benefits of adopting AI.
Change management and feedback on AI: Gathering feedback from people involved in testing initiatives gives leaders visibility into how the rest of the employees might react. Gradual adaptation turns an AI rollout into a learning process rather than a radical and immediate change.
Bottoms-up approach better than top-down: AI adoption is as effective as the people who create it. Organization should engage employees with the knowledge and skills to help identify the opportunities for AI. The ownership of defining the need and deployment will be easier and cost-effective. Organization should train employees on identifying opportunity boxes for digitization. Initiatives such as AI for Hackathon or other simplification exercises can be powerful tools for bottoms up approach to change management. Too often, organizations take a top-down approach, relying on people with technical expertise to take the lead on AI while leaving out the subject matter experts who can actually identify the opportunities for the business.