AI Levels Playing Field For Workforce

Artificial Intelligence (AI) is quickly becoming a cornerstone technology across various sectors. As other new technologies, AI cost is rapidly decreasing, allowing for broader adoption. Surprisingly, the reduction in cost is happening faster than many previous groundbreaking technologies. One such general-purpose technology is solar photovoltaic with exponential decays in cost per watt in a 10-year period creating a profound effect on its adoption around the world.  

The rapid decline in AI cost, combined with its increasing capabilities and prowess is forcing organisations to reconsider how they allocate tasks and redefine job roles. As businesses reorganise workflows, (more) tasks will be delegated to AI agents.  This kind of shift will redefine roles for professionals across industries, from office secretaries to data scientists, in a way that eclipses the changes seen over the last few decades.

Fundamental shift

The workforce is gradually experiencing a fundamental shift over the next decade. Economists have long debated the effects of automation on labour markets, and AI has brought this conversation to a centre stage again. While new technologies typically make economies more productive, allowing workers to move into new fields, AI brings unique challenges. Particularly with automation, there is growing concern that certain types of jobs — especially middle-wage jobs such as clerical work and data analysts — may not survive the wave of the AI technological disruption.

AI can greatly augment the work of customer service agents by using language models to assist with complex queries. Organisations have been using these internally as knowledge base to automate mundane troubleshooting. When Large Language Models (LLMs) augment these knowledge bases, they can bring surprising productivity gains. A customer service unit can measure the changes in the number of issues resolved per unit time when supported with AI vs without AI. There are many examples that show AI not only provides lift but also can level the playing field by empowering less experienced workforce without having to build the years of experience.

However, not all workers will benefit equally from AI’s deployment. The increasing productivity gains in highly skilled sector often come at the expense of jobs that require low skill repetitive tasks. This shift is already creating greater inequality in labour markets, and economists such as MIT’s Daron Acemoglu have warned that AI may widen this gap further if not managed properly.

The adoption of AI is not only reshaping the workforce but also providing higher ROIs than other alternatives. AI systems, which can perform many cognitive tasks, offer a cheaper and more efficient alternative to human workers.  A recent study has shown that the direct cost of using AI decreased 79 per cent in a span of 17 months - from $36 per million tokens to $4 per millions tokens today. According to Andrew Ng, a global authority in AI, the cost of using AI as a virtual assistant — despite its limitations —can be distilled to just $1.41 per hour. This is a significantly lower wage than the U.S. federal minimum of $7.25 per hour, and even more so when compared to the minimum wages in higher-paying regions such as California ($16) and Washington D.C. ($17). 

AI’s ability to streamline complex processes means that companies can handle more tasks in less time. In the case of the aforementioned customer service example, AI enabled agents to handle more cases per hour and reduced customer frustration by providing quicker and more accurate responses. As AI systems become more integrated into business processes, there will be even more opportunities for cost savings. In industries where customer interactions, data processing, and repetitive tasks are prevalent, AI will be a game-changer.

AI's impact on jobs as mentioned above is a double-edged sword. On one hand, lies prospects of more efficient work and productivity gains but on the other, it risks displacing jobs that depend on repetitive or low-skill tasks. However, the key to a successful transition lies in this technology wave creating new jobs in sectors that we have not fully comprehended. The futurists who argue that AI will open new avenues for employment, much like how the internet did in the past. We need to keep investing in upskilling and reskilling so we can have the AI do our chores while we enjoy arts and crafts. 

Ethical concern

Concerns over privacy, ethics, and safety have risen once again with this wave of technology. One of the most significant ethical challenges with AI is the risk of bias and privacy violations. AI systems, particularly those trained on large datasets, can inadvertently perpetuate biases present in the data. For example, generative AI systems can sometimes fabricate information or exhibit biases in their outputs, especially if the underlying data contains historical prejudices. To combat such unintended consequences companies need to take steps to develop ethical guidelines and align their AI with human rights principles. It is imperative that this technology push and pull policies have dual mandate of progress and fairness.

While the productivity gains are undeniable, the challenges posed by AI also abound. Historically, technology development and adoption has focused primarily on speed and efficiency leaving behind social, environmental and moral concerns. Organisations that wish to harness the full potential of AI must strike a balance between innovation and responsibility. By embedding human values into AI systems and ensuring that ethical standards are upheld, companies can pave the way for a future where AI is a force for good. 

(The author is working in building social and financially just algorithms for the insurance and financial services.)