LONDON--(BUSINESS WIRE)--A recent study conducted by Mindtech, the leading developer of synthetic training data, revealed that an impressive 90% of automotive industry executives are harnessing the power of synthetic data. The survey, which collected responses from 250 business leaders in the automotive sector across the US and UK, highlights the pressing need for optimised data practices and the growing focus on AI in today's business landscape.
Among the participants, 87% reported being familiar with synthetic data, noting quick problem-solving as a key strength (29%), followed by the quality of data (23%) and privacy compliance (21%). One in three respondents expressed dissatisfaction with their current real-world data practices, citing the difficulty of finding a suitable solution as a major factor. Interestingly, 87% of participants identified AI as a key focus for their business in 2023, with 25% selecting automation as the primary advantage of AI. Solving difficult problems (22.8%) and better decision-making (21.8%) were also recognised as key benefits.
Steve Harris, CEO of Mindtech, commented: "More and more, we are seeing the automotive industry embracing the power of synthetic training data to elevate their AI vision systems and optimise their data practices, marking a remarkable shift in the technological landscape. Industries worldwide are encountering the limitations of relying solely on real-world data.”
Eighty percent of automotive industry leaders pinpointed electric and autonomous vehicles as pivotal advancements by 2028. "The survey findings underscore the urgency for businesses to reassess their data practices and invest in AI-driven solutions. By doing so, companies can unlock a competitive edge and meet the evolving demands of their customers," Harris concluded.
To find out more about Mindtech, visit the website here.
Mindtech Global is the developer of the world's leading end-to-end 'synthetic' data creation platform for the training of AI vision systems. The company's Chameleon platform is a step change in the way AI vision systems are trained, helping computers understand and predict human interactions in applications ranging across retail, smart home, healthcare, and smart city.