No ROI on Your AI? The Solution is Simpler - and More Human - Than You Think
A recent study by SAS and the International Data Corporation (IDC) has shed light on the three roadblocks to successfully implementing Artificial Intelligence (AI) in businesses, revealing that a widespread lack of trust among companies in their deployed AI tools may be hindering Return on Investment (ROI).
According to the study, which analyzed data from over 1,000 enterprises worldwide, the top three reasons for the failure to achieve tangible ROI from AI initiatives are governance, skills, and data infrastructure. "The problem is not with the technology itself, but rather with how it's being implemented," said Dr. Webb Wright, Contributing Writer at ZDNET. "Businesses need to rethink their approach to AI and focus on building trust in these systems."
The study found that 95% of enterprise use cases for AI have been essentially fruitless, with many companies struggling to integrate the technology into their existing infrastructure. This lack of integration is often due to a mismatch between the skills required to implement AI and those available within the organization.
"It's not just about throwing more money at the problem or hiring more experts," said Dr. Wright. "Businesses need to take a step back and assess their current data infrastructure, governance policies, and employee skills before investing in AI."
The study also highlighted the importance of human oversight in AI implementation. "AI is only as good as the data it's trained on," said Dr. Wright. "If that data is biased or incomplete, the results will be too. Businesses need to prioritize data quality and ensure that their AI systems are transparent and explainable."
The lack of trust in AI tools among businesses may have significant implications for society as a whole. As more companies turn to AI to drive innovation and efficiency, it's essential that they do so responsibly.
"AI has the potential to revolutionize industries and improve lives," said Dr. Wright. "But if we don't get it right, we risk exacerbating existing social and economic inequalities."
The study's findings come at a critical time for businesses looking to leverage AI to drive growth and competitiveness. As more companies invest in AI, they must prioritize building trust in these systems.
"The solution is simpler - and more human - than you think," said Dr. Wright. "It's about taking the time to understand your data, your employees, and your customers before investing in AI."
Background:
The study was conducted by SAS and the International Data Corporation (IDC) and analyzed data from over 1,000 enterprises worldwide.
Additional Perspectives:
Dr. Webb Wright, Contributing Writer at ZDNET, emphasized the importance of human oversight in AI implementation, saying "AI is only as good as the data it's trained on."
Current Status and Next Developments:
As more companies turn to AI to drive innovation and efficiency, they must prioritize building trust in these systems. The study's findings highlight the need for businesses to rethink their approach to AI and focus on building trust through transparent and explainable systems.
Sources:
SAS and International Data Corporation (IDC) Study
Dr. Webb Wright, Contributing Writer at ZDNET
*Reporting by Zdnet.*
