How to be Agile in the Era of Generative AI: A Perspective by Tech Entrepreneur Working in AI and ML

Dipali Trivedi
- Advertisement -

By Dipali Trivedi

By 2025, 90% of online content is going to be generated by AI and 300 million jobs will be replaced, enabling companies to save resources and use increased productivity for more complex functions that has potential to increase overall GDP by 7%.

According to an academic research study, automation have reduced wages by more than 50% replacing blue collar jobs in last half century, but Generative AI, robotics and machine learning will go beyond blue collar jobs to replace entry level white collar jobs performing surgeries, writing simple software and generating creative art artifacts. This will increase productivity that can increase GDP up to 7%, but it will widen income inequality resulting in much wider income gap or unemployment of unskilled or entry level workforce. That’s it’s important for young workforce to focus on skills that cannot be easily replaced by AI.

Generative AI refers to machine learning algorithms that can generate new content, such as images, music, or text, based on patterns and data that they have learned from. While generative AI has the potential to revolutionize many industries and create new opportunities, it also has the potential to exacerbate income inequality in several ways.

1. Job displacement: As generative AI becomes more advanced, it may replace human workers in certain industries, such as graphic design, music production, or content creation. This could result in job loss for some workers, especially those who lack the skills or education to transition to other industries.

2. Skill-based income distribution: As generative AI becomes more prevalent, the ability to create high-quality content may become less valuable. This is because anyone with access to the technology can generate high-quality content, reducing the demand for human creators. This could lead to a shift in income distribution toward those who have skills in areas that cannot be easily replicated by machines, such as strategic thinking or interpersonal communication.

3. Concentration of power: Generative AI requires large amounts of data to learn from, which can create a feedback loop where companies with more resources can generate higher-quality content, attract more users, and collect even more data. This could lead to a concentration of power in the hands of a few large companies that control the most advanced generative AI technology and have access to the most data.

Generative AI has the potential to create new opportunities and enhance productivity, but it is important to be aware of the potential risks and work to mitigate them to ensure that the benefits are shared more broadly and distributed equally helping young workforce to focus on skills that cannot be replaced by generative AI. There are few types of jobs difficult for generative AI to replace.

Jobs that require creativity and originality: While generative AI can create new content based on patterns in existing data, it may struggle to generate truly original and creative ideas. Therefore, jobs that require creative problem-solving, innovation, and imagination are less likely to be automated by generative AI. This includes jobs in the arts, design, writing, and other creative fields.

Jobs that require emotional intelligence: Generative AI lacks the ability to empathize with human emotions and experiences. Therefore, jobs that require a high degree of emotional intelligence, such as counseling, social work, or teaching, are less likely to be automated by generative AI.

Jobs that require physical dexterity and mobility: While robots and other forms of automation can perform many physical tasks, there are certain jobs that require a high degree of manual dexterity and mobility that are difficult to replicate with machines. This includes jobs in fields like construction, plumbing, and mechanical repair.

Jobs that require complex decision-making: While AI can assist with data analysis and decision-making, it may struggle to make complex decisions that require a deep understanding of multiple factors and nuances. Jobs that require this type of complex decision-making, such as senior management roles, are less likely to be automated by generative AI.

Overall, it is important to recognize that the impact of generative AI on the job market is complex and multifaceted. While some jobs may be automated, others may be created or augmented by the technology. Therefore, it is important for workers to develop skills and knowledge that are complementary to AI and to remain adaptable to changes in the job market, while companies should start exploring AI to increase productivity and shift resources to more complex functions to maximize their profit.

(Dipali Trivedi is an MIT graduate and a serial entrepreneur. She is currently working as co-founder and CTO of Everyday Life, a FinTech startup that serves middle-income families with innovative insurance products and financial planning using AI and ML. Prior to Everyday Life, she founded CloudFountain Inc., a consulting firm focused on big data, AI, ML and Salesforce CRM consulting. Dipali has 10+ years of corporate leadership experience prior to entrepreneurship. She volunteers for various non-profit organizations in USA, India, and Africa, and serve as board advisor. She is an influencer for Women in Tech and Entrepreneurship to break glass ceiling and fight gender bias.)


Please enter your comment!
Please enter your name here