According to a study by MIT, the cost of deploying artificial intelligence (AI) technology currently makes it more economical for employers to keep human workers. The study focused on tasks that rely on computer vision and found that only 23% of workers’ wages for such jobs could be cost-effectively replaced by AI. The researchers predict that even with a 20% drop in cost per year, computer vision tasks would still take decades to become economically efficient. While AI excels at recognizing patterns and analyzing images, it comes with hefty installation and maintenance costs and needs help with tasks that require intuition and implicit knowledge. Industries like banking, marketing, retail, legal services, transportation, and healthcare are prime candidates for increased automation, but the narrative of machines stealing jobs seems exaggerated for now.
A study conducted by Cognizant predicts that AI could contribute about $1 trillion to the US economy in the next decade. However, this growth comes at the cost of job losses, with an estimated 9% of employees related to the US economy expected to lose their jobs in the next ten years. The adoption of AI in US companies is projected to increase from 13% to 50% over the next 20 years, impacting various job sectors such as credit analysis, computer programming, data administration, and graphic design.
CeADAR, the Irish research centre for applied AI, is developing an early warning system for severe flooding in Ireland. Using data from the European Space Agency’s Sentinel-1 satellite, researchers have created an AI model to predict future floods and provide early detection to at-risk communities. The project aims to limit damage by allowing local authorities to implement emergency measures. The data collected from Storm Babet in Co Cork will help refine the model and improve its accuracy. The project has significant implications for flood-prone areas and is funded by the Irish Department of Enterprise, Trade and Employment.
Why do we care?
For now, AI is not a universal replacement for human labor but rather a complementary tool. IT service firms can leverage this insight by focusing on hybrid models that effectively combine AI with human expertise, particularly in industries where AI cannot match humans’ intuition and implicit knowledge. This is where the value is.
Consider the example. Using AI to provide better insights for human analysts is the kind of use case to explore AI applications in other critical areas like climate change mitigation, environmental monitoring, and emergency response systems or beyond.