Redefining the Training Landscape: The Impact of Gen AI

Redefining the Training Landscape The Impact of Gen AI
Gen AI can aid create new content, analyze data to convert into meaningful information, learn from data interactions and suggest ideas and executions that can impact workforce positively and efficiently.

In today’s time and day technology is evolving without a warning and making the world more agile and appreciative of possibilities. Generative Artificial Intelligence (Gen AI) is making reality come closer and faster.

It is making leaders and managers to review their respective industry landscape in a fresh way, marrying aspirational and practical approaches to even skills training.

Gen AI can aid create new content, analyze data to convert into meaningful information, learn from data interactions and suggest ideas and executions that can impact workforce positively and efficiently. It is critical to adapt ourselves to remain relevant and ahead of the curve from competition.

Gen AI at the workplace attempts to automate operational/BAU tasks that may require human intervention. Examples could vary from data entry to processing, content creation and placement and basic analytics to highly predictive analysis.

However, automation is not limited to routine tasks and can be extended to more complex data driven decision-making, which demands professionals to develop better and higher technology skills. Traditional learning and training approaches may have varied limitations and have constraints to address future of work.

Continuous learning, adaptability and agility are the most vital skills for current and future professionals.

Key Skills to Leverage Gen AI

  • Technology Quotient: Basics of artificial intelligence, machine learning, and data science are becoming increasingly unavoidable and a much-needed basic skill. Undertaking offline or online courses and certifications will aid individuals in attaining fundamental knowledge.
  • Correlation Quotient: While Gen AI will process data faster than humans, it will always lack the nuanced understanding of context and real situations on the floor. Hence, the ability to critically analyze and generate valuable insights or inferences from such data, which will be business-related information for decision-makers will be a key differentiator and core advantage.
  • Creativity Quotient: Gen AI will generate content and ideas from data. Creativity and lateral thinking of the human mind should keep professionals in business. Encouraging diversity of thought will remain a critical component of skills training.
  • Emotional Quotient: Empathy, understanding and mental ability to sense belonging would be very tough for machines to replicate. Training people in emotional intelligence is not just crucial but necessary as we all will always work in teams, with people and stakeholders.
  • Data Quotient: Gen AI will keep generating huge amounts of data. The ability to grasp, collate, interpret, and convert into actionable information for impactful decision-making will become invaluable. For this to happen, professionals need to possess data literacy, data accuracy, data sanity, and play with data for better understanding, quicker analysis, and higher utilization of available data.

We may know where we need to reach. And then we figure out how we get there.

Outlining some known and some probables that may help create a roadmap for effective skills training and learning programs in the AI era here:

  • Investing in Lifelong Learning: There has to be a concerted and consistent focus on continuous education programs by way of upskilling/reskilling and refresher courses. Long-term and continuous learning has to become part of the culture of organizations.
    • Blending Learning Approaches: Synergizing and utilizing traditional classroom modules with virtual learning platforms and merging structured learning courses with real-world/on-the-job experiences need to become the new/innovative learning mode. It provides not just a new training experience but a holistic and highly flexible learning landscape.
  • Personalized Development Paths: Just as there are horses for courses, there need to be courses for horses! Tailored learning interventions for individuals leveraging their individual learning styles as well as their professional goals/objectives and personal aspirations will have a multiplier effect on growth as well as productivity of individuals.
    • Soft Skills are to be hard-coded: While AI works through technology, people-centered competencies whether it is teamwork, personal or business communication, and professional and technical agility, process adherence and psychological adaptability etc are critical professional skills to be attained and improved on.

A critical factor to remember while implementing any form of AI as AI continues to evolve, is the purview of ethics. Issues around privacy, bias in algorithms and job displacement eventualities needs a debate to create business-friendly and customer impacting guidelines around ethical boundaries. Training should encourage healthy discussions on use of AI and its responsibilities.

Gen AI is a gold coin that has two sides- challenges and opportunities. To develop a responsive model, organizations need to co-create flexible training ecosystems while embracing AI and superimposing the unique and unavoidable human angle in the AI framework.

A committed and transparent approach by corporate and learning institutes, as well as professionals and relevant individuals to become adept and being adaptable and learn, un-learn and reskill oneself is demanding and yet need of the hour.


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