Home News Generative AI: Creating More Work Than It Saves?

Generative AI: Creating More Work Than It Saves?

Generative AI

Generative AI has been hailed as a groundbreaking technology with the potential to revolutionize various industries by automating tasks and enhancing productivity. However, recent findings suggest that the integration of generative AI might be creating more work than it saves, posing challenges for businesses and employees alike.

The Promise of Generative AI

Generative AI, which includes technologies like ChatGPT and DALL-E, is designed to generate content such as text, images, and code. Companies have adopted these tools to automate routine tasks, improve customer service, and generate creative content. The expectation was that these technologies would significantly reduce workload and enhance efficiency.

Training and Implementation Challenges

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One of the primary issues with generative AI is the extensive training required for employees to effectively utilize these tools. Training data scientists and engineers to proficiently work with large language models (LLMs) can take months. For instance, a financial services company reported it took three months to train its top data scientists to a competent level in generative AI, involving rigorous apprenticeship and ongoing learning sessions​​.

Furthermore, deploying generative AI at scale involves substantial infrastructural adjustments. Companies need to establish centralized teams to develop protocols, standards, and approved tool libraries. This process, while necessary for minimizing risks and controlling costs, adds to the workload rather than reducing it​.

Increased Workload for Employees

Despite the automation potential, generative AI often results in a paradoxical increase in workload. Employees must spend additional time overseeing AI-generated outputs, correcting errors, and ensuring the quality of the content. This is particularly evident in customer service, where AI tools are used to assist agents. While there is a reported 14% increase in productivity for new or less-skilled workers, experienced agents see minimal benefits, necessitating a continuous oversight role for seasoned employees​.

Moreover, a significant portion of workers are using generative AI tools without formal approval from their employers, indicating a gap in training and governance. This unregulated usage can lead to inconsistencies and increased corrective tasks, adding to the overall workload​​.

Changing Nature of Work

Generative AI is also reshaping job roles, requiring workers to develop new skills rapidly. A Microsoft report highlights that employees feel compelled to acquire AI skills to stay competitive, with 76% indicating the need for these skills to remain relevant in the job market. This shift places additional pressure on workers to continuously learn and adapt, further contributing to an increased workload​​.

The impact on job roles is significant, with some roles evolving to focus more on strategic and oversight functions rather than routine tasks. This transformation demands higher cognitive skills, problem-solving abilities, and expertise in AI tools, thereby increasing the complexity and intensity of work​.

While generative AI holds promise for enhancing productivity and automating tasks, the current reality indicates a more complex scenario. The need for extensive training, the necessity of continuous oversight, and the evolving nature of job roles contribute to an overall increase in workload. Businesses must carefully manage the integration of generative AI to balance its benefits with the additional demands it places on employees.

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