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Why are manufacturers slow to embrace Generative AI?
A recent Lucidworks poll has stated that manufacturers are deploying generative AI initiatives more slowly than expected due to concerns regarding accuracy.
FILE PHOTO: AI (Artificial Intelligence) letters are placed on computer motherboard in this illustration taken, June 23, 2023. REUTERS/Dado Ruvic/Illustration/File Photo
A recent Lucidworks poll has stated that manufacturers are deploying generative AI initiatives more slowly than expected due to concerns regarding accuracy.
The survey polled over 2,500 leaders from around the world who make choices about AI technology. According to the survey, just 58% of manufacturing executives plan to increase their AI investment by 2024, which is lower than the global and US consensus rates of 63% and 69%, respectively.
Why accuracy matters
93% of executives, including those from the industrial sector, planned to expand AI spending in 2023. Despite this, AI deployment is delayed by concerns about cost and accuracy. ” The initial wave of enthusiasm for generative AI is being met with a more strategic approach. Businesses are recognizing the potential, but also the risks and costs. This study provides the insights you need to make informed decisions and chart a successful path forward with AI,” said Mike Sinoway, CEO of Lucidworks in the report.
The Importance of AI Investment
Investors are optimistic about AI’s potential for substantial returns. AssetLink in a writeup titled ‘The Role of AI in Modern Investment Strategies’, AI is critical in modern investment strategies for changing decision-making, portfolio management, and risk mitigation. In today’s fast-paced financial market, artificial intelligence (AI) plays an important role in improving efficiency, accuracy, and agility, providing a competitive advantage to those that use its capabilities.
According to Lucidworks’ study, nearly 50% of manufacturers reported cost savings after adopting AI initiatives this year.
Understanding Generative AI
Generative AI generates new information based on previous data, but it can occasionally produce incorrect or nonsensical results, known as hallucinations. While 36% of all respondents are concerned about response accuracy due to hallucinations, manufacturers are even more concerned (44%).
Current AI adoption
Despite only 20% of planned AI projects being implemented by manufacturers in the past year, 55% of them feel they are on par with their peers in AI adoption.
The cost concerns
Over the past year, 70% of industrial companies opted for more expensive commercial AI models. According to Lucidworks, manufacturers may transition to more economical open-source models if they show efficient and resourceful. While manufacturers are hopeful about AI’s cost benefits, they intend to maximise its value with reduced spending this year.
