Data Quality and Deployment of AI Applications Are Main Factors Affecting the Success of AI Application Development
AUSTIN, TX / ACCESSWIRE / June 7, 2022 / CognitiveScale, the company leading AI Engineering and Hyper-personalization, shared the results of its 2022 AI Engineering Survey. The survey asked more than 600 executives who are responsible for key AI initiatives and application development decisions, and who play a pivotal decision-making role in digital transformation, about how AI will solve key business challenges in the next 12-18 months. Nearly 95% of decision makers expect AI will play a key role in solving key business challenges. Yet, they say the path toward implementation is unclear.
More than 76% of executives say they are having challenges with scaling the implementation of AI applications across multiple use cases, or functional areas/lines of business, with most executives saying that both data quality and deployment of AI applications affect the success of AI applications. Thirty-two percent of executives say that it has taken longer than expected to get an AI system into production; whereas, just 19% said it took shorter than expected.
Notably, 75% of AI executives say trust and transparency are important to overall AI application development because they're in a regulated industry, and 63% say repeatability is a key factor in AI development processes.
"The potential of AI is immense and while AI adoption is beginning to take place at an accelerated pace, understanding AI implementation is still something organizations are making sense of," said Bob Picciano, CEO of CognitiveScale. "Our AI Engineering Survey shows that data quality is the biggest factor affecting the success of AI adoption within an organization. Mission-critical information, the need for reuse and repeatability, and trust and governance are extremely critical to the success of AI."
According to a recently released report, Forrester's Now Tech: AI/ML Platforms, Q1 2022 report, "the business case for AI is clear, yet businesses struggle when it comes to operationalizing and proving outcomes. For AI to have a transformative impact, it needs to be industrialized. That means putting aside the one-off solutions and establishing proven AI Engineering practices - standardized building blocks, tools, and processes that make it easier to drive value faster, and in a way that scales."
When it comes to the maturity of their AI initiatives, only 20% of executives say they have just implemented an AI solution. Fewer than 40% of respondents say they are experienced, with multiple AI solutions in production, while 40% say they are considering AI.
To learn more and access the full 2022 AI Engineering Results survey from CognitiveScale, please visit https://www.cognitivescale.com/survey-results-ai-engineering/.
About CognitiveScale
CognitiveScale pioneered the concept of 'AI Engineering', paving the way to industrialize scalable Enterprise AI development and deployment. Backed by over 100 granted AI patents, the award-winning Cortex platform empowers businesses to infuse trusted decision intelligence into business processes and applications maximizing total customer experience and operational efficiency. Our focus is on regulated industries such as Healthcare and Financial Services where our platform currently delivers hyper-personalized insights to more than 100 million customers.
Headquartered in Austin, Texas, CognitiveScale is recognized by the World Economic Forum for positively impacting business and society through responsible AI. We are backed by investment from Norwest Venture Partners, Intel Capital, IBM, Westly Group, M12 (Microsoft Ventures), Anthem and USAA. To learn more, visit www.cognitivescale.com and follow us on Linkedin and Twitter at @CognitiveScale.
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SOURCE: CognitiveScale
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