Leverage GenAI for reskilling

The infusion of technology in this quest made things easier and today, when artificial intelligence is at its most advanced, it is time to unlock the next chapter in effective reskilling of employees. In clearer terms, it is time to leverage GenAI, our portal into the future for this aim.

By Viiveck Verma 

Re-skilling, or the process of empowering your employees with skills and competencies they need to stay in tune with the times, used to be an unwieldy proposition in the past. Even as employers acknowledged the necessity of reskilled employees, the endeavour required a tremendous pooling of resources, planning, implementation as well as time and space to be carried out and the efficacy of results was not easy to glean. The infusion of technology in this quest made things easier and today, when artificial intelligence is at its most advanced, it is time to unlock the next chapter in effective reskilling of employees. In clearer terms, it is time to leverage GenAI, our portal into the future for this aim. Let us look at the possibilities and the implications of putting GenAI to use for revolutionising reskilling.

Tailored Training

To begin with the basics, Generative AI or GenAI is the kind of artificial intelligence which can seamlessly and quickly generate media including text and images, using generative models. This enables the automation of several processes, reducing the degree of human involvement. For example, where one would need to read data, create a table, type in the records, analyse, interpret and present one’s findings earlier, with the help of GenAI, which takes care of the basic and intermediate steps, all one is left with is the interpretation and presentation of the information. Similarly, when it comes to re-skilling employees, GenAI can take care of a lot of intermediate work, reducing the human cost inherent in the process. For instance, GenAl can easily analyse the skills of individual employees, their styles of learning as well as their preferences to create personalised learning paths. Where experts were supposed to preach to a crowd earlier with little to no personal involvement, by understanding each employee’s strengths, weaknesses and interests based on available information, GenAl can create and recommend tailored training modules, optimising the learning process. In addition to this, such Al can adapt training materials and pacing based on an individual’s progress. Significantly, such an adaptive approach to learning ensures that employees receive content at an appropriate level, maximising their comprehension and retention of newly acquired skills. In fact, there is no limit to pushing the envelope when it comes to training employees using AI. For example, GenAl can create realistic simulations and scenarios relevant to various job roles, fostering an immersive training experience which allows employees to practise skills in a risk-free environment, enhancing and sharpening their competencies before applying them in real-world situations. Al-powered chatbots and virtual assistants can provide immediate support and clarification on topics or challenges encountered during training and what is incredible is that employees can access this information and guidance at any time convenient to them, a process that facilitates continuous learning. As an example, think of DuoLingo’s effective language learning AI solution which provides instant feedback and simulates interactions between the source of knowledge and the learner. Beyond this, GenAl can analyse learning data to provide insights to employers and this includes identifying skill gaps across the organisation, assessing the effectiveness of training programmes and predicting future skill demands, enabling proactive reskilling strategies. Importantly, Al-driven reskilling programmes can be more cost-effective and time-efficient compared to traditional methods as automated assessment of skills, instant feedback and adaptive learning reduce the time required for employees to acquire new competencies.

Tread Cautiously

However, we must not be heedlessly in awe of GenAI since its use in reskilling employees presents various ethical implications that need careful consideration. First of all, GenAl algorithms are prone to inheriting the biases present in the data they are trained on, which is fed by humans, and this can perpetuate existing societal biases, leading to unfair advantages or disadvantages in the reskilling process. To exemplify, datasets based on performance indicators in a country with a particular work culture and only one dominant language of operation, when imported to another location, can unfairly judge employees in a multilingual setting. Ensuring fairness in access to training opportunities and mitigating biases within the Al systems is extremely crucial. Since reskilling often involves the collection and analysis of vast amounts.

GenAl algorithms are prone to inheriting biases present in data they are trained on, which is fed by humans, and this can perpetuate existing societal biases

of personal data, protecting this data from breaches and unauthorised access is paramount. Employees must have control over their data and be informed about how it is being used in reskilling ventures. Furthermore, GenAl-powered reskilling initiatives should be accessible to all employees, regardless of socioeconomic background, education level, or technological proficiency. Ensuring equal access and opportunity for upskilling is crucial to prevent exacerbating extant inequalities. Ultimately, while Al can assist in suggesting learning pathways, human oversight is necessary. The final decisions regarding reskilling, the validation of skills acquired and the assessment of readiness for new roles should or rather, must involve human judgment to maintain ethical standards. It is important to note that reskilling is not a one-time event; it is an ongoing process due to the rapid evolution of technology and the new demands the world of work continuously places on its inhabitants. Consequently, companies using GenAl for reskilling must commit to continually updating and improving training programmes to keep pace with changing skill requirements.

Ethical Implications

GenAl’s ability to personalise learning experiences, provide adaptive and immersive training, analyse data for insights and offer cost-effective, scalable solutions makes it a powerful tool in reskilling the workforce to meet the demands of an evolving job landscape. However, there are many ethical implications in its usage which require a multidimensional approach, encompassing policy development, regulatory frameworks, ethical guidelines and ongoing monitoring. For a vigilant, resourceful and beneficial in the long run, it is incumbent upon companies to ensure that their use of GenAl for reskilling aligns with ethical principles, respects individuals’ rights, and fosters an inclusive and supportive environment for all workers. In other words, GenAI changes the nature of engagement of human resources in the reskilling process, rather than replacing them. It is a tool which has to be used under expert human supervision to the benefit of everyone concerned. On the whole, collaboration between AI and human intelligence remains a key to optimal efficacy of the former in the process of reskilling. When employed with enlightened and alert considerations, GenAI not only galvanises the way we train employees but also radically opens new windows for productivity. Let us turn this opportunity into stellar success and let GenAI be our catapult to summits of excellence!