It is important to understand the arrangement between humans and machines in the conduct of AI projects. Specifically, it is useful to understand decision-making in organizations that deploy AI, the associated growth in headcount and retraining efforts, and the way competence is acquired due to introduction of AI in firms.
Nearly 70 percent of high-revenue firms rely on consensual AI, monitored AI and decision-support mechanisms for decision-making.
In medium sized firms, we observe that nearly 50 percent of the firms rely entirely on human decision-making as they do not use AI.
More than 40 percent of small and micro revenue firms use AI for decision support.
The advent of AI into commercial applications has brought about a shift in the competence acquisition for projects in firms. Such shifts could either require incorporation of fundamentally new concepts or principles in task execution, new skills which the firm did not possess, develop many new skills, learn from completely new or different knowledge bases, adopt different methods and procedures or carry out a high degree of re-training.
Over 70 percent of the respondents agree with each of these shifts in competence acquisition due to AI.
More than 80 percent of respondents from the survey have indicated that either the organization or more than one department in the organization stood to benefit with AI deployment.