Managing People Through AI (Part II of II)

Abhinav Raj, Writer
@uxconnections

Artificial intelligence (AI) technology has witnessed steadfast adoption in many large corporations. As AI solutions become more commonplace, accessible and scalable, small firms are likely to follow suit.

If data is the new oil, artificial intelligence is the new vessel—and given enough data, AI can take us light years ahead. 

Big Data and Small Businesses: The Challenges and Prospects for AI 

In a 2020 analysis of businesses leveraging big data by the International Data Group (IDG), it was revealed that small and medium-sized enterprises manage about 50 terabytes of data—a figure that was expected to grow by a margin of 50% over the coming year. 

This becomes an intriguing figure as small-medium enterprises accounted for 99.9% of the business population in the UK at the start of 2021. 

One may be led to believe that an estimated 5.5 million SMEs generating large amounts of data would mean that the said data is being actively employed in analytics—however, it may be a faulty presumption. The truth is that infrastructural challenges unique to SMEs oft act as barriers to the effective utilization of data analytics. 

As the infrastructural challenges are addressed, the vast amount of data generated by SMEs can be readily translated into actionable information. 

Artificial Intelligence in Recruitment 

(Image: LinkedIn Sales Solutions on Unsplash)

Recruiting, resourcing and onboarding talent are organizational activities that have witnessed the most extensive deployment of artificial intelligence tools over the past five years. 

The allure of AI-enabled tools in talent acquisition lies in the capability of the said tools to expedite the process of resourcing talent exponentially. 

Large organizations have been steadfastly adopting software solutions that employ predictive analytics to gauge a candidate’s suitability for a role and their probability of succeeding in the organization—of which one example is the AI-powered resourcing tool Pymetrics.

Pymetrics follows a gamified approach to behavioural assessment. Through a number of small mini-games, the artificial intelligence tool evaluates the candidate’s focus, decision-making ability, propensity to learn and retain information, and risk tolerance alongside a myriad of relevant capabilities tailored to match the jobs they are applying for. 

The succeeding phase includes a video interview that provides a ‘comprehensive evaluation’ of candidates in context. The AI-enabled resourcing tool enables resourcing talent for diversified work profiles and industries as the design of methods can be tweaked and customized by hiring managers and recruiters headhunting for a specific occupation. 

Recruitment and onboarding practices are likely to witness greater process automation as AI solutions become more credible, accessible, affordable and inclusive. 

Artificial Intelligence in Learning and Development 

(Image: Eddie Kopp on Unsplash)

The one-size-fits-all approach to organizational learning is outdated and is being readily replaced by personalized coaching and mentoring methods. 

By adopting an individualized approach to learning and development, employers can have a greater sense of the unique learning need of employees. 

Machine learning algorithms, remarked by their remarkable efficiency in analyzing large amounts of data can be utilized to reveal insights into the individual learning requirement of employees. 

A learning approach that integrates AI can not only automate data analysis faster but can also help learners keep track of their performance and learning objectives in practicum—enhancing their user experience by keeping them informed of their developmental trajectory. 

AI has the potential to transform organizational learning, and tech startups are willing to bet on it. 

The financial prospects are tantalizing. Organizations that create opportunities for mutual learning between employees and artificial intelligence are twice as likely to obtain financial benefits. 

By enabling AI tools to facilitate the growth of organizational knowledge, firms are empowering employees to make better decisions in their everyday work life. In this way, organizational learning becomes an agent of continual enhancement of workforce knowledge—catalyzed by technology. 

Digitization was an antecedent to the artificial intelligence revolution. With new technological tools hitting the market every day, innovation in the arena of AI is unlikely to stagnate. 

Is it too early to manage our people through AI? Let us know in the comments.