**Generative AI Projects Failing Due to High Costs, Risks**
The increasing costs and risks associated with Artificial Intelligence (AI) projects are causing many of them to falter. Despite the promise of AI transforming industries, several recent reports have highlighted the struggles that companies are facing in their AI endeavors.
According to a new Gartner report, at least 30% of generative AI projects will be abandoned after the proof-of-concept stage by the end of 2025. The main reason for this high failure rate is the inability of companies to prove and realize value from their investments, which can range from $5 million to $20 million in upfront costs.
The Gartner report is not the only one to sound the alarm. A separate report from Deloitte found that 70% of companies have only moved 30% or fewer of their generative AI experiments into the production stage, citing lack of preparation and data-related issues as the main reasons.
These findings are consistent with a RAND study, which found that over 80% of AI projects fail, twice the rate of failure in corporate IT projects that don’t involve AI.
One of the main challenges in scaling up AI projects is a lack of preparation. Fewer than half of the respondents to the Deloitte survey felt that their organizations were highly prepared across the areas of technology infrastructure and data management.
The quality of data is another major hurdle. The Deloitte study found that 55% of businesses have avoided certain generative AI use cases because of data-related issues, such as data being sensitive or concerns about its privacy and security.
Despite the challenges, many companies are persevering with their generative AI initiatives, driven by tangible impacts on revenue savings and productivity. However, the ABBYY research found that 63% of global IT leaders are worried that their company will be left behind if they don’t use it.
Despite the buzz surrounding artificial intelligence, many AI projects are faltering due to rising costs and mounting risks. A recent Gartner report revealed that at least 30% of generative AI projects will be abandoned after the proof-of-concept stage by the end of 2025. Companies are struggling to prove and realize value in their endeavors, which can cost anywhere from $5 million to $20 million in upfront investments.
According to Deloitte, a lack of preparation is a primary reason for the failure of enterprise GenAI projects. Fewer than half of the respondents to the Deloitte survey felt their organizations were highly prepared across the areas of technology infrastructure and data management. The quality of data also represents an additional hurdle in seeing GenAI projects to completion.
The lack of clarity on the problem that AI promises to solve is also a significant contributor to project failure. Industry stakeholders often misunderstand or miscommunicate this problem, or choose one that is too complicated to solve with the technology.