JOHAN STEYN: AI’s productivity paradox
Monitoring the impact of automation and AI investments requires well-defined goals and objectives, sound technical knowledge, and high-quality data
Investments in machine-intelligent automation and artificial intelligence (AI) have the potential to transform businesses and unlock new levels of productivity and efficiency. However, many organisations find that these investments often do not deliver the anticipated value.
According to a study by McKinsey Global Institute, only 25% of the work done by humans can be automated using present technology. Another study by Gartner suggests that 85% of AI projects will deliver erroneous outcomes due to bias in data, algorithms, or the teams responsible for managing them. And a survey by Deloitte reported that only 38% of respondents reported that their organisation had achieved moderate to substantial benefits from their automation initiatives...
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