Nvidia expanded its partnership with Accenture to help companies scale artificial intelligence adoption.
The news comes as generative AI demand helped drive $3 billion in Accenture bookings in its latest fiscal year, according to a Wednesday (Oct. 2) press release.
The expanded partnership includes the formation of the Nvidia Business Group, designed to “help clients lay the foundation for agentic AI functionality” with Accenture’s AI Refinery, which is powered by Nvidia’s AI stack.
“We are breaking significant new ground with our partnership with Nvidia and enabling our clients to be at the forefront of using generative AI as a catalyst for reinvention,” Accenture Chair and CEO Julie Sweet said in the release. “Accenture AI Refinery will create opportunities for companies to reimagine their processes and operations, discover new ways of working, and scale AI solutions across the enterprise to help drive continuous change and create value.”
Accenture AI Refinery will be available on all public and private cloud platforms and integrate with other Accenture business groups to accelerate AI throughout the Software-as-a-Service (SaaS) and cloud AI ecosystem, per the release.
The partnership follows a May collaboration between Accenture and Oracle designed to help clients accelerate their adoption of generative AI in their finance organizations.
In other AI news, the technology’s increasing role in software development is helping reshape commerce, making product launches faster and creating more personalized customer experiences.
Coding tools, such as the GitHub Copilot and OpenAI’s Codex, are transforming how companies develop and deploy software. These advanced machine-learning models can suggest code snippets, perform functions, or construct entire code files using prompts or existing code.
“AI coding tools enhance the productivity of developers greatly through the automation of some repetitive tasks and code suggestions,” Dhaval Gajjar, chief technology officer of SaaS company Textdrip, told PYMNTS Tuesday (Oct. 1). “This can bring about faster development cycles and, consequently, reduce the time-to-market.”
He said these tools “maintain the quality of code based on best practices and catch potential errors right at the development stage. It reduces an extended testing and debugging process, thereby saving a lot of time and resources.”
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