AI’s Broken Promise: Why Companies Are Struggling to Unlock Value

It’s been over 18 months since the release of ChatGPT, and the hype surrounding Generative AI (Gen AI) continues to grow. However, a recent study by SoftServe reveals a stark reality: only 22% of organizations are effectively using Gen AI across all business functions. Despite this, companies are still investing heavily in the technology, with 80% of decision-makers claiming their employees are struggling with use case awareness and general understanding of Gen AI complexity.

Companies are struggling to unlock the value of Gen AI

According to the study, organizations are experiencing less value from Gen AI than expected, with only 42% having the capabilities to train Gen AI models and a staggering 89% facing difficulties preparing business data for Gen AI use. The gap between expectations and reality is significant, with 79% of decision-makers concerned about their organization’s ability to execute their business goals with current levels of internal or external expertise.

The gap between expected and actual value of Gen AI

One of the main reasons for this gap is the lack of data readiness, governance, and skill development. Companies are struggling to prepare their business data for Gen AI use, with only 24% having governance plans in place. Moreover, there is a significant gap in technical skills, with 88% saying deeper technical expertise is becoming increasingly important for data integration, model optimization, use case development, and further application development.

Lack of technical expertise is a significant challenge for companies implementing Gen AI

Another challenge companies are facing is the over-abundance of use cases. With so many potential applications of Gen AI, companies are struggling to determine which ones will deliver the biggest impact. As a result, many are investing in multiple use cases, with plans to pilot at least one more in the next 12-18 months. However, this approach is not sustainable, and companies need to focus on prioritizing their use cases and developing a clear strategy for implementation.

Companies are struggling to prioritize their Gen AI use cases

In conclusion, while the hype surrounding Gen AI continues to grow, the reality is that companies are struggling to unlock its value. The gap between expectations and reality is significant, and companies need to focus on developing their data readiness, governance, and skill development in order to succeed. By prioritizing their use cases and developing a clear strategy for implementation, companies can overcome the challenges associated with Gen AI and realize its full potential.

“Despite a swift start to the Gen AI race, many initiatives get stuck in the piloting stages as more organizations realize their data infrastructure isn’t ready to adequately deploy Gen AI technologies beyond the proof-of-concept,” said Alex Chubay, SoftServe’s CTO.

“The dangers of prompt injection are still not widely well known, but they are easy to execute. Companies should not rely on pre-prompting as an infallible defense mechanism and should employ more robust mechanisms when interfacing LLMs with critical resources such as databases or dynamic code generation,” said Shachar Menashe, senior director of security research at JFrog.