Digital Event Horizon
Moving Beyond Hype: Overcoming the Challenges of Deploying Generative AI
The adoption of generative artificial intelligence (AI) has been on the rise, with 65% of businesses now using it in at least one business function. However, despite its potential benefits, successful deployment remains a major challenge for many companies. This article explores the challenges associated with implementing generative AI and offers insights into how businesses can overcome these hurdles to unlock the full potential of this powerful technology.
The share of businesses using generative AI in at least one function doubled to 65% in 2023. 91% of organizations expect generative AI applications to increase their productivity. Two-thirds of business leaders are dissatisfied with progress on their AI deployments. The cost and complexity of implementing generative AI systems is not straightforward. Generative AI has the potential to impact GDP by $1 trillion to $4.4 trillion annually. Companies need to develop new tools and technologies to support the successful integration of generative AI into business operations.
The promise of generative artificial intelligence (AI) has been a siren's call to businesses for some time now. Since the introduction of ChatGPT in November 2022, companies have flocked to large language models (LLMs) and generative AI models seeking solutions to their most complex and labor-intensive problems. The promise that customer service could be turned over to highly trained chat platforms capable of recognizing a customer's issue and presenting user-friendly technical feedback, for example, or that companies could break down and analyze their troves of unstructured data from videos to PDFs has fueled massive enterprise interest in the technology.
This hype is now moving into production. According to McKinsey, the share of businesses that use generative AI in at least one business function nearly doubled this year to 65%. The vast majority of organizations (91%) expect generative AI applications to increase their productivity, with IT, cybersecurity, marketing, customer service, and product development among the most impacted areas, according to Deloitte.
Despite these encouraging statistics, difficulty successfully deploying generative AI continues to hamper progress. Companies know that generative AI could transform their businesses—and that failing to adopt will leave them behind—but they are faced with hurdles during implementation. This leaves two-thirds of business leaders dissatisfied with progress on their AI deployments. And while in Q3 2023, 79% of companies said they planned to deploy generative AI projects in the next year, only 5% reported having use cases in production in May 2024.
"We're just at the beginning of figuring out how to productize AI deployment and make it cost effective," says Rowan Trollope, CEO of Redis, a maker of real-time data platforms and AI accelerators. "The cost and complexity of implementing these systems is not straightforward." Estimates of the eventual GDP impact of generative AI range from just under $1 trillion to a staggering $4.4 trillion annually, with projected productivity impacts comparable to those of the Internet, robotic automation, and the steam engine.
Yet, while the promise of accelerated revenue growth and cost reductions remains, the path to get to these goals is complex and often costly. Companies need to find ways to efficiently build and deploy AI projects with well-understood components at scale, says Trollope. This requires a deeper understanding of the challenges and limitations of generative AI deployment, as well as the development of new tools and technologies that can support its successful integration into business operations.
As the technology continues to evolve and improve, it is likely that we will see significant progress in this area. The recent success stories surrounding generative AI, such as the creation of a replica of Minecraft using only AI-generated video clips and keyboard inputs, offer promising glimpses into the potential for this technology to be used in innovative and creative ways.
In order to unlock the full potential of generative AI, it is essential that businesses develop a deeper understanding of its capabilities and limitations. This requires ongoing investment in research and development, as well as a commitment to exploring new and innovative applications for this technology.
Ultimately, the successful deployment of generative AI will depend on our ability to overcome the challenges and complexities associated with implementing these systems. By working together to develop new tools and technologies that support its integration into business operations, we can unlock the full potential of this powerful technology and realize its promise of accelerated revenue growth, cost reductions, and increased productivity.
Related Information:
https://www.technologyreview.com/2024/12/02/1106689/moving-generative-ai-into-production/
Published: Mon Dec 2 11:01:44 2024 by llama3.2 3B Q4_K_M
