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Can Organizations Stay Afloat With Generative AI Dreams Or Drown In Shortage?

By TD NewsDesk

TD NewsDesk

Updated on Fri, Jul 21, 2023

Overall Rating
Whoa!

Are organizations swimming in the AI pool but lacking the floaties to meet Generative AI expectations?
Revelations from a recent study by open-source AI solutions provider ClearML clearly indicate that how much ever organizations may like to join the Generative AI bandwagon, they still have a long way to go in leveraging their true potential.

ClearML conducted a study of the use of generative AI and published its findings in a report titled "Enterprise Generative AI Adoption: C-Level Key Considerations, Challenges and Strategies for Unleashing AI at Scale”. The report sheds light on the economic impact of AI and the considerable obstacles faced by top C-level executives to fully realize AI's potential within their own organizations.

Despite the high expectations of corporate leaders for generative AI innovation, the global study found that 59% of C-suite executives needed more resources to deliver. Successful enterprise-wide adoption of AI has been hampered by budgetary and resource constraints, which have prevented the development of concrete value.

Sixty-six percent of those surveyed admitted they lack the tools necessary to accurately assess the financial benefits of their AI/ML initiatives. This exemplifies the severe difficulty for large-company AI, ML and engineering teams to quantify achievements due to inadequate resources (funding, staffing, and governance).

“While most respondents said they need to scale AI, they also said they lack the budget, resources, talent, time and technology to do so,” Moses Guttman, cofounder and CEO of ClearML, told a technology new platform. “Given AI’s force-multiplier effect on revenue, new product ideas, and functional optimization, we believe critical resource allocation is needed now for companies to invest in AI to transform their organization effectively.”
 
While it's pretty evident that businesses require a cannonball of AI solutions to realize their generative AI visions, the situation could be better.

Let's dive deeper to unlock more information.
 

The state of generative AI adoption


Most of those surveyed in the study agreed that employing instances using artificial intelligence and machine learning to produce business value is crucial. Eighty-one percent of those who took the survey considered it very or somewhat important.

In addition, 78% of businesses expect to deploy xGPT/LLMs/generative AI in FY2023, with an additional 9% expecting to initiate adoption in FY2024 for 87%.

59% of C-level leaders need more resources to meet the expectations of business leadership about gen AI innovation, even though gen AI and ML adoption is a critical revenue and creativity engine within the firm.

“Enterprise decision-makers are poised to increase investment in generative AI and ML this year, but according to our survey results, they’re seeking a centralized end-to-end platform, not scattering spend across multiple point solutions,” ClearML’s Moses Guttmann told VentureBeat. “With growing interest in materializing business value from AI and ML investments, we expect that the demand for increased visibility, seamless integration and low code will drive generative AI adoption.”
 

Key challenges hindering generative AI adoption


The study found that there have been severe economic and financial repercussions due to increased governance issues around AI and generative AI.

Enterprise losses owing to weak governance of AI/ML applications were cited by 63% of respondents and 54% of CDOs, CEOs, CIOs, heads of AI and CTOs. In some instances, these losses were as high as $50 million.

ClearML's Moses Guttmann claims that the poll results highlight a severe barrier to successfully adopting new technology: a need for more transparency, measurable outcomes and predictable outcomes. All of those are essential for achieving one's goals.

“Enterprise customers should strive to get out-of-the-box LLM performance, trained on their internal business data securely on their on-prem installations, resulting in cloud cost reduction and better ROI,” he said.
 
Will companies jump into the AI pool frenzy and make a splash in the field of generative AI? Or will they just be trying to keep their heads above water while technology sweeps over them? Let us know your thoughts in the comments section below!

First published on Fri, Jul 21, 2023

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Tags:

Artificial Intelligence (AI)Generative AI Organizations Resources Expectations Study Swim Sink AI Challenges AI Limitations AI Adoption AI Implementation

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