How tech-based gig companies are harnessing AI for success

A crucial aspect where AI is involved is the integration of AI-powered chatbots to streamline communication between freelancers and clients.

How tech-based gig companies are harnessing AI for success

Sunday January 07, 2024,

3 min Read

The gig economy is quite a dynamic landscape, and tech-based companies in the industry are embracing the transformative potential of artificial intelligence (AI) to redefine success.

One of the key areas where AI’s effect on the gig economy can be seen is in the domain of intelligent matching. There is a massive shift from using traditional algorithms to using sophisticated AI-based models. These models take a lot of factors into consideration before matching.

Factors such as user preferences and historical data to real-time demand are considered, ensuring optimal matches between freelancers and opportunities. This not only enhances user experience but also maximises efficiency, leading to increased overall productivity.

Data-driven decision-making

Data is one of the most important things in the gig economy. There has been a shift from intuition-based decision-making to a data-centric approach.

AI algorithms process vast amounts of data generated by freelancers and users, offering valuable insights into trends, preferences, and performance metrics.

This data-driven decision-making essentially helps gig companies to adapt swiftly to market changes, optimise their operations, and provide a personalised experience for both workers and clients.

Enhanced user experience through chatbots

A crucial aspect where AI is involved is the integration of AI-powered chatbots to streamline communication between freelancers and clients. These bots are equipped with natural language processing capabilities, which help them efficiently handle all queries and provide real-time updates.

This not only enhances the user experience but also frees up human resources for more complex tasks, helping build a seamless and efficient gig economy ecosystem.

Reducing bias in gig platforms

Addressing bias on gig platforms has been a critical challenge. AI is being used to reduce bias in various aspects, including task allotment and performance evaluations. By deploying AI algorithms that are impartial, companies are working towards creating a fairer and more inclusive environment, fostering diversity among their gig workforce.

The road ahead: navigating challenges

AI is currently a transformative force in the gig economy; it is revolutionising the way freelancers connect with clients and enhancing overall efficiency. Its impact on the gig economy brings some promising advancements.

The intricate matching algorithms consider skills, background, aspirations, cultural bent, and availability rather than just skill sets. AI can easily reduce the entire screening process of going through thousands of profiles to seconds. However, a vigilant approach is required to prevent biases and ensure fairness in algorithm-made decisions.

AI's role in designing skill tests helps ensure the overall quality of freelancers, and the feedback mechanism fosters continuous improvement in project productivity. With AI’s help, tracking project progress and milestones can contribute significantly to streamlined project management. AI can also help freelancers be up-to- date with the recent developments within this dynamic industry and encourage them to upskill.

However, we need to be mindful of certain ethical issues concerning potential biases in algorithms. There needs to be a well-made, mature and researched framework that's based on millions of data sets and consumer research. This involves prioritising the development of ethical guidelines, comprehensive AI training, and collaborative efforts among stakeholders to ensure a balanced and responsible evolution of the gig economy.


The author is Founder and CEO of Begig, a platform that helps tech freelancers find work.


Edited by Affirunisa Kankudti

(Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views of YourStory.)