University of MIA Report: 1 % of productive artificial intelligence projects lead to failure

The new report “Genai Gap: The Status of Artificial Intelligence in Business 2” by the University of MIT shows that only 2 % of the productive artificial intelligence tests have achieved rapid growth in revenue; While most projects have stopped or have no significant economic impact.

This research is based on 1 Interview with Managers, Survey of 5 Employees and Investigating 2 General Artificial Intelligence The carried out a big gap between limited success stories and broad organizational failures.

Why do most projects fail?

According to the saying Aditia ChalapaliThe main author of the MIT report is not the main problem of the quality of the models, but the organizational learning gap and the incomplete integration of tools with internal processes. He explains that tools like ChatGPT are excellent for individual use, but in the organizational environment they stop because of the lack of compatibility with the workflows.

In contrast, smaller startups have been able to make tens of millions of dollars by focusing on a specific issue and fast implementation.

The allocation of wrong resources

More than 1 % of productive artificial intelligence budget Is spent on sales and marketing in companies; While the findings of MIT indicate the highest return on capital in Office automation And removal is processes outsourcing.

Buy or build?

According to data, buying specialized tools and collaborating with vendors, in 1 % Has been successful; But domestic development has only been concluded in one -third. This gap is particularly more common in setting industries such as financial services; Where companies have experienced a high failure rate despite heavy costs for domestic construction.

Consequences of labor force

The effect of artificial intelligence on the labor market is also evident. Many companies do not fill vacancies instead of widespread expulsion. Most changes have taken place in roles that were previously outsourced, such as customer support and office jobs.

Look at the future

The MIT research also points to the growth of “shadow artificial intelligence” in organizations and the difficulty of measuring productivity. At the same time, the most advanced companies toward Factor artificial intelligence Move; Systems that can learn, remember and act independently. These technologies show a picture of the next stage of organizational artificial intelligence.