Few innovations in history have advanced as rapidly as generative artificial intelligence (AI).
And in news on Tuesday (April 16), Intel is collaborating with several other industry partners to launch Open for Enterprise AI, which aims to accelerate secure and cost-effective GenAI adoption for enterprises. We are collaborating on a sandbox project called Platform (OPEA). Leveraging AI is becoming an increasingly important concern for businesses.
In a release announcing OPEA, Intel said AI is “currently in a state of dynamic innovation, with a byproduct of technology and tool fragmentation.” This fragmentation hinders enterprise adoption of GenAI and the immense value it brings to the business. Developers tasked with realizing this value will be faced with a dizzying array of choices when incorporating GenAI. ”
“OPEA has the ability to take GenAI to the next level by providing a standardized platform for evaluation, development, and deployment,” Intel added.
in the end, IInnovations with defined use cases are more likely to be accepted by the market. When companies can see and measure how new products and technologies like GenAI solve problems or improve existing workflows, they are more likely to adopt them.
Without defined use cases, it is difficult to determine whether an innovation is achieving its intended goals and delivering value.
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Establishing enterprise use cases for GenAI systems
The inability of organizations to define their own use cases for GenAI is part of the reason OpenAI CEO Sam Altman is holding conferences this month in San Francisco, New York, and London, each with more than 100 people the AI company aims to company executives attended. We position our AI systems as enterprise-grade solutions and sell them to businesses.
ChatGPT Enterprise, OpenAI's enterprise-grade chatbot, is positioned as a value-add to enterprise capabilities such as call center management, translation, and other applications. And OpenAI isn't the only company seeking lucrative corporate deals for its AI systems.
As we covered here, Amazon launched its own enterprise-focused AI platform, Amazon Q. The platform includes corporate partners such as Accenture, BMW Group, Gilead, Mission Cloud, Orbit Irrigation, and Wunderkind. Last month, Microsoft announced the launch of two new AI-optimized devices designed specifically for business users: Surface Pro 10 for Business and Surface Laptop 6 for Business.
Google is also pioneering the field of B2B GenAI, introducing several new enterprise AI capabilities to the Google Workplace suite this month (April 9), helping businesses make traditional tasks more intelligent and automated. I'm trying to help you convert to a process that is
“The ChatGPT light bulb went on in everyone's heads, bringing artificial intelligence and cutting-edge deep learning into the public sphere,” Andy Hock, senior vice president of product and strategy at Cerebras, told PYMNTS. .
“From a corporate perspective, a light bulb went off in the heads of many Fortune 1000 CIOs and CTOs,” Hock added. “These generative models do things like simulate time-series data. For example, they can classify languages and documents for applications like finance and legal.”
According to data from PYMNTS Intelligence, 7 in 10 consumers already believe that AI can replace at least some of their professional skill sets. Younger consumers, those making more than $100,000, and those working in an office environment are most likely to recognize this skill overlap.
And it's not just big tech companies pushing GenAI systems for enterprises. An emerging group of AI startups and small and medium-sized enterprises are also targeting the corporate market with innovative solutions.
Also read: The future of AI is becoming indistinguishable from the future of work
Overcoming obstacles to implementing enterprise AI
Still, there remains uncertainty across the market as to whether GenAI models are “worth it” for business applications due to cost, unpredictability, and resources required to effectively deploy them. Masu.
As Adrian Aoun, CEO of Forward, told PYMNTS, “For AI to work and scale, we need to build things for the AI world.”
Developing and implementing innovations requires resources such as time, money, and human resources. Defined use cases can help allocate these resources more efficiently and ensure that they are invested in projects with clear objectives and potential impact.
Pecan CEO and co-founder Zohar Bronfman explained to PYMNTS that access to skilled data scientists who can effectively implement AI solutions is both valuable and scarce.
Eddie Zhou, head of AI at Glean, told PYMNTS that he highlighted the challenges posed by market-wide silos in fragmented data environments, making it easier to clarify use cases before deployment and to invest in enterprise AI. emphasized the importance of understanding the value proposition of
“If companies aren't clear about what they want to solve, integration can be delayed,” Chou said. “Yes, AI is helpful, but what do you want it to do? It's a moving target…We're just beginning to discover where the real value is added.”
To learn more, PYMNTS Intelligence's Generative AI Tracker®, in collaboration with AI-ID, breaks down the myths and realities of AI and explains how companies can use the technology wisely.
