The Future of Work with Generative AI and ML

The Future of Work with Generative AI and ML
Data is becoming the driving force behind most business decisions, especially when AI will be able to consume data that should therefore be harvested and harnessed in the appropriate way.

Artificial Intelligence is “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.” “AI” describes advancements in computing, systems, and technology in which computer programs can perform tasks that require ‘human intelligence’ including learning from past processes.”

Machine Learning is a subset of AI that enables machines to learn from data without being explicitly programmed.  AI and ML are expected to transform the job market by automating repetitive tasks and augmenting human capabilities. 

Like many discussions around the impact of technology on the future of work, a short-sighted conclusion could be that AI and ML are ‘going to make human workers redundant!’ However, a realistic view indicates that certain ‘lower order jobs’ that are repetitive in nature might become redundant. However, jobs that require higher-order skills cannot be replaced or made obsolete in the short term.

As the days pass, we see a longer list of jobs that AI can take over – medical diagnosis, composing music, automotive design, etc. Yet there are still very complex jobs that need a lot more intelligence than has so far been learned by the bots. The sheer volume of data sets that need to be crunched – implies far superior computing technology that typically implies exorbitant costs for superior processing which might be higher than the cost of hiring a human being to do the task!

While the trend towards automation will continue and impact innovation in diverse industries –this would also increase the requirement for skilled technologists who know how to apply advanced tools to diverse use cases. This will create new job opportunities in diverse fields related to AI and data science.

While there was a lot of excitement with the launch of Chat Gpt which even passed a medical exam in the US, there was also an observation that it ‘did not display empathy’. So, while it can make an accurate diagnosis, it cannot replace a doctor!

The Future Workplace Will be Impacted by

Ø  The sheer range of applications of AI & ML to a diverse set of tasks: Each industry and sector are going to be affected in a completely different way. Most employees working in industries where the potential for automating tasks is higher will need to acquire new competencies to help them check the myriad ways in which to apply the new technology to their area of work.

Ø  The need for upskilling team members to prevent obsoletion: Employees will become much less specialized and much more flexible as the old “specialized skill set” gradually becomes obsolete. Most employees will have a higher average education, but more importantly, everyone will be required to possess some degree of data literacy.

Ø  A need for greater creativity to keep pace with the advancement in technology: Automation will free up much more space by freeing up creativity and critical thinking in the workplace as the more mundane tasks are automated by machines. AI-based bots or assistants will handle a lot of the repetitive tasks, allowing workers to enjoy more free time to concentrate on more creative functions. 

Ø  Robotic Process Automation (RPA) is simplifying data retrieval, processing, and many other mundane, repetitive tasks. AI is significantly improving RPA by making it “intelligent” through the addition of ML-powered features such as deep learning, natural language processing (NLP), and optical character recognition (OCR). However, human critical thinking is a critical component of many jobs that cannot be replaced

Data is becoming the driving force behind most business decisions, especially when AI will be able to consume data that should therefore be harvested and harnessed in the appropriate way. AI will collect immense amounts of data from connected devices on its own, but humans need to decipher and interpret this data, and, more importantly, establish a safe and inclusive environment that safeguards everyone’s privacy and cultural differences.

Ø  A need to humanize interactions in the face of increased automation that might tend to make all interactions ‘mechanical’- Machines might make workplaces more hectic. People could adopt a mechanical approach – not having the patience to wait when the pace of work is quick as attention spans are short and people expect quicker response time. AI will make all response and reaction times shorter. This has the potential to make workplaces more hectic unless we exercise a degree of moderation.

In fact, most intelligent AI is still in its development phase, and will require a lot of human help to become “mature.” A lot of new jobs will be created for AI trainers who will have to assist machines while they perform their duties. “Intelligent automation” requires cooperative environments where employees and AI work together to achieve a given goal much more efficiently. Whilst artificial intelligence will be more productive than human workers for repetitive tasks, humans will always outperform machines in jobs requiring relationship-building and imagination.

Impact on the HR Function

It is exciting to see the immense possibilities to utilize AI and ML in the HR function itself.

Vast amounts of information on all aspects of employee activity will be analyzed and processed by MI to present usable reports, which will identify important trends, threats, and opportunities.

Glassdoor and LinkedIn have effectively used machine learning to narrow searches and seek out suitable candidates based on advanced intelligent algorithms. This could help transform recruitment efforts.

FedEx used machine learning products developed by Google to analyze the characteristics of potential applicants to show them positions that are a good match to their skills, experience, and personality.

Properly applied machine learning technologies can save time through the use of predictive analytics to reduce time wasted in recruiting and make the process more reliable and accurate.

Machine learning will streamline the process, reduce errors and improve results.

While the human element is still required to get a feel for the candidate, machine learning will provide accurate and usable analytics to improve the effectiveness of recruitment. It will also help to eliminate human bias and other human elements that could be hindering the process.

Spotify and Netflix utilize machine learning to present content based on your previous activity, providing curated suggestions such as “Made for You” playlists on Spotify and “Recommended for You” movies and TV shows on Netflix. Similarly, machine learning can surface content and curate recommendations, such as news, search results, and documents, based on previous user activity which can help save employee time and enhance overall workplace productivity.

As machine learning gains a deeper understanding of an organization and has absorbed all relevant information, it will be able to Identify knowledge gaps; fine-tune and personalize training; become a resource for information and questions related to company policies, benefits, and company procedures. It might even be able to help performance reviews and guide and enhance employee growth and development!


Please enter your comment!
Please enter your name here