As we step into an era that hinges on digital transformation, AI solutions for business are becoming increasingly crucial. Businesses across the globe are scrambling to adapt to the new norm and integrate AI into their operational framework. However, the transition to automation, particularly in the realm of AI, is not as rapid as one might expect.
The Gradual Shift to AI in Business
Contrary to popular belief, the adoption of AI in business operations is not an immediate, all-encompassing leap. It is, in fact, a gradual shift that takes into account multiple factors such as technical feasibility, cost-effectiveness, and economic attractiveness.
The decision to automate a task using AI is not solely according to the technological possibility of automation. It also considers whether automating the task will yield substantial economic benefits and return on investment for the business. Thus, businesses are faced with a careful balancing act: to automate or not to automate?
The Economic Attractiveness of AI Automation
In the course of their research, a team of experts from MIT Sloan School of Management, The Productivity Institute, and IBM developed an innovative model to predict the pace of AI automation. By examining the field of computer vision, they discovered that technical and cost barriers could potentially leave a significant portion of jobs untouched by automation in the near future.
Their research demonstrated that currently, only approximately 23% of labor expenses linked to visual tasks would justify automation based on current costs. This implies that businesses might choose to refrain from automating the majority of vision tasks, which could technically be performed by AI.
The Cost-Benefit Analysis of AI Automation
To further illustrate their point, the researchers presented the hypothetical scenario of a bakery. In this bakery, the task of visually checking ingredients could be automated using computer vision system. However, the expenses involved in developing, deploying, and upkeeping such a system would far exceed the potential labor savings.
Under these circumstances, the bakery would likely opt against automation, as the cost of implementing AI would not justify the ROI. This example paints a vivid picture of the economic considerations that businesses must grapple with when deciding to automate tasks using AI.
The Adoption Curve of AI Automation
The study suggests that big organizations are more likely to adopt AI compared to smaller businesses due to their greater resources. However, this doesn’t mean that smaller businesses will be left behind. The slow adoption curve of AI offers a significant opportunity for these businesses to gradually integrate AI into their operations.
The rate of adoption could quicken if the expenses for AI systems decrease or if businesses opt to utilize AI-as-a-service platforms for deployment. These platforms offer AI capabilities at a larger scale, making it more affordable and accessible for businesses of all sizes.
The Impact of AI Automation on Jobs
Interestingly, the study also found that AI automation is unlikely to increase the rate of job displacement significantly. The influence of automation has already been felt across numerous job sectors.
In fact, following an initial surge, the job displacement resulting from computer vision-based AI automation is expected to be lower than the existing turnover rate in the job market. This gradual adoption enables adequate time for policy changes and retraining programs, thus mitigating the potential negative effect of automation.
A World Full of Possibilities
In conclusion, the path to AI automation is not as direct and swift as it might seem. It is a path that requires careful consideration of the technical feasibility and economic attractiveness of automating each task.
AI solutions for businesses offer a world of possibilities, but it is essential for businesses to assess the economic viability of these solutions before diving in. The gradual adoption curve of AI automation presents an opportunity for businesses to adapt and evolve at their own pace, ensuring a smoother transition into the digital era.
