Bridging the AI talent gap: Will this be a new opportunity for employees? Infosys's HR head Shaji Mathew answers

Almost 72 per cent of the organizations surveyed by the Infosys Generative AI Radar (North America) said they were planning to increase Generative AI investments, expecting benefits ranging from enhanced user experience and personalization to higher operational efficiency, streamlined product development, and easier content creation. However, 18 percent were concerned that, more than any other challenge, the lack of talent and skills would hinder implementation. All the organizations who participated in the survey were contemplating various measures to address this issue. For employees, this is a signal to acquire AI skills and embrace an AI culture without hesitation. Doing so would not only help them stay relevant, but actually prosper, in the workplace of the future.  

Upskill-first, AI-first

When looking to bridge the AI talent gap, employers should prioritize upskilling and reskilling existing employees over recruiting new workers or leveraging the skills of partner firms. It is only fitting that they take an AI-first approach to deliver the best possible learning experience to employees. Such an experience offers certain advantages, which I shall now outline. 

Highly adaptive and personalized to individual learners: Enterprise Learning Management Systems have made remarkable progress; but previously, these platforms were designed for scale, and therefore, to provide standardized content and a defined learning path to all employees, irrespective of their individual needs, learning abilities, or motivations. There was no way to personalize a training program to individual requirements, since using manual means was infeasible in terms of both cost and time. Now, however, by rearchitecting learning management systems with an AI-first approach, it is possible to assess the AI (and other) skilling needs of every learner and curate relevant content in real-time, at low cost. AI allows each employee to choose their own path, pace, and method of learning, and also adapts the program based on how they are progressing.  

Real-time and integrated: “Scheduled” training programs, requiring employees to take time out from work, are quickly becoming a thing of the past. With employees able to spare only about 1 percent of their time for learning, employers need to find a way to deliver knowledge without interrupting work, ideally, exactly when it is required. Once again, AI offers a solution – micro learning modules that can be integrated within work processes, ready to be delivered at the right time. Think of an AI application developer who needs help with a piece of code; AI tracking tools can “sense” this and automatically launch a bot to assist the employee. 

Gamified and engaging:  Learning management systems, although they provide rich, accessible knowledge, often deliver lower than expected outcomes. It appears that a major reason for this is lack of learner motivation. An AI-first platform addresses this by leveraging gamification principles to transform the learning process from a tedious chore to an exciting, engaging, and enjoyable experience. Learners can absorb the content better and are motivated to finish their assignments on time. For example, the platform could, based on an analysis of sales data, offer a gamified sales training program that introduces progressively advancing challenges and rewards, personalized to each salesperson. Interestingly, using an AI-based learning platform to train non-IT workers is a great way to make them comfortable with using AI at work. 

Multimodal AI-augmented: Apart from the software writing helper bot mentioned earlier, organizations can leverage AI-based coaches – an approach that is delivering good results. These tools mimic student-teacher interactions, reply to questions, and offer proactive assistance to learners. Multimodal AI-based tutoring is poised to become much more sophisticated with the introduction of Augmented/Virtual Reality, humanoid robots, and holographic teachers. At the same time, AI will enable multimodal pedagogy in formats such as text-to-text, text-to-video, and video-to-video.

Curated and customized: As mentioned earlier, customizing training programs to meet individual needs was not possible for learning management platforms in the past. Also, despite the standardization, learning & development teams spent significant time and energy in developing the content despite its standardized nature. AI is coming to the rescue by scanning, finding, and piecing together the right content to make it easily consumable. Not only that, but Generative AI can also create and curate training materials to suit every user’s context and preferences. And it can do this repeatedly, so content remains fresh, and training programs stay relevant.

To sum up, enterprises’ path to AI adoption is being impeded by a serious talent-and-skills gap. This is an opportunity for employees to upskill their way to better career prospects. It is a win-win scenario because, from an employer standpoint, reskilling existing employees is a much better option than hiring new workers or leveraging third-party capabilities. As employers design their AI skilling programs, an AI-first learning approach would enable them to amplify outcomes.