In the last few years, we have seen that the managers of Silicon Valley companies promise that artificial ielligence will increase productivity and profitability and will transform the world; But reality shows something else. A new report from KPMG shows that the vast majority of companies that have turned to artificial ielligence have yet to monetize it.
According to the findings of a KPMG survey of 753 differe businesses, only 2% of companies reported that their investmes in productive artificial ielligence have paid off. This statistic becomes even more ieresting when you know that most of these successful 2% are also gia companies with annual revenue of more than 1 billion dollars.
The main reason for this lack of profitability is the excessive procrastination of companies in the trial and error phase. Many organizations have yet to fully iegrate AI io their work and are just experimeing with the tools.
Lack of profitability of artificial ielligence in most companies
There is a strange coradiction in the statistics; 93% of the surveyed organizations use artificial ielligence, but most of them do not benefit financially. Of these, 31 perce have only iegrated this technology io core operations. For this reason, experts say that just buying a ChatGPT subscription or using image generation tools will not increase revenue or reduce operating costs.
Of course, business leaders believe it’s a long-term game. Most managers (about 61%) expect to see tangible financial results between 1 and 5 years from now. “Stephanie Terrill” (Stephanie Terrill), one of the senior managers of KPMG Canada, warns that it is dangerous to stop investing despite the lack of immediate profits. “It’s not realistic to expect to see immediate value,” he says. “Companies must accelerate the implemeation of artificial ielligence in their core operations in order to maiain economic competitiveness.”
Also, one of the main problems is that companies do not know how to measure the efficiency of artificial ielligence. Should we only look at cash? Experts suggest that in order to properly understand ROI, strategic and qualitative criteria should be considered:
- How much has artificial ielligence made managers’ decisions more accurate?
- Are things done faster and easier?
- Has better service led to greater satisfaction?
Therefore, focusing solely on reducing costs or increasing direct sales does not provide a complete picture of the value of AI.
