Numerous IT service providers and consulting businesses have ramped up their artificial intelligence (AI) practices in recent weeks in a bid to drive demand for enterprise AI.
The latest announcement is Accenture’s expansion of its partnership with Nvidia, resulting in the formation of the Accenture Nvidia Business Group, through which it plans to help enterprises rapidly scale their AI adoption. According to Accenture, generative AI (GenAI) orders grew to $3bn in this financial year.
Using Nvidia’s AI stack, AI Foundry, AI Enterprise and Nvidia Omniverse tools and platforms within its own AI Refinery, Accenture said the group’s goal is to provide a foundation for “agentic AI functionality” in application areas such as process reinvention, AI-powered simulation and sovereign AI. The AI functionality is used to replace manual human keystrokes with AI systems that Accenture says can act on the intent of the user, create new workflows and take appropriate actions based on their environment.
Accenture’s AI Refinery will be made available on all public and private cloud platforms and will integrate with other Accenture business groups to accelerate AI across the software-as-a-service and cloud AI ecosystem. “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,” said Julie Sweet, chair and CEO of Accenture.
The IT services company said it has 30,000 professionals receiving training globally to help clients reinvent processes and scale enterprise AI adoption.
As part of its Center for Advanced AI, Accenture said it is also expanding its engineering network of hubs to provide technical capacity for using agentic AI systems. The new hubs will be based in Singapore, Tokyo, Malaga and London, adding to existing capabilities in the Mountain View hub in California and the Bangalore hub.
AI additions
In September, Tata Consultancy Services (TCS) expanded its AI-powered cyber security portfolio with TCS Managed Detection and Response (MDR) powered by Google Security Operations. According to TCS, the new service uses AI, machine learning and automation to enable security teams to reduce the time required to detect and respond to threats. Working with Google, TCS MDR continuously monitors risks, identifies deviations and recommends remedial actions.
Meanwhile, Kyndryl has expanded its portfolio of services around Copilot for Microsoft 365 to speed up AI adoption in the workplace. The services are being positioned as a way to help Kyndryl customers build effective use cases for Copilot for Microsoft 365. Kyndryl said the new services drive high-impact use cases by aligning data services (which includes capabilities around Microsoft Purview), data extensibility, user interface design and continuous improvement reporting. The services are designed to empower customers by enhancing decision-making, streamlining operations and driving digital transformation while accelerating the deployment and adoption of Copilot for Microsoft 365 services.
In August, Infosys expanded its collaboration with Nvidia to drive innovation and operational excellence for telecoms companies. Based on Infosys Topaz services and platforms, the company said it will be offering telcos the ability to deploy generative AI technologies to enhance customer experiences, streamline network operations and accelerate service delivery.
IT services provider Wipro, meanwhile, is now using Google’s Vertex AI and Gemini models for project execution to clients and is equipping its workforce with generative AI-powered tools to enhance developer productivity, accelerate cloud migrations and deliver innovative GenAI applications. The company is building new industry offerings based on the Gemini models and integrating Gemini Code Assist into its internal tooling to accelerate application development for customers. It is also using Gemini for rapid prototyping of its internal applications.
Another internal use of AI is occurring at EY, which earlier this year announced it was deploying Microsoft Dynamics 365 Sales and Copilot for Sales to 100,000 staff by 2025. While an internal project for streamlining sales processes and improving collaboration, Hanne Jesca Bax, EY’s global vice-chair for markets, said the project is being used to demonstrate to EY clients how such AI deployments can be achieved in highly regulated industries.
Making AI accessible
There has also been a raft of new product developments and services from the traditional server manufacturers to support growing customer demand for AI.
HPE is working with Nvidia on HPE Private Cloud AI, which it describes as a turnkey, cloud-based experience co-developed with Nvidia to help businesses of every size build and deploy GenAI applications. According to HPE, the offering enables software developers to build and deploy GenAI-powered virtual assistants with just one mouse click.
Dell, meanwhile, is collaborating with Red Hat to deliver its PowerEdge servers with Red Hat Enterprise Linux AI. Dell described the new product as a foundation model platform built on an AI-optimised operating system, which it claims enables users to develop, test and deploy AI and GenAI models to Dell PowerEdge servers.
It is a similar story at Lenovo, which recently announced a suite of services designed to fast-track AI transformation by making “private AI accessible to every business”. Lenovo aims to provide on-demand AI to its customers, helping businesses use their on-premise proprietary data to build, scale and evolve GenAI workloads.
AI skills in demand
A Gartner survey of 300 US and UK organisations in the fourth quarter of 2023 found that 56% of software engineering leaders rated AI and machine learning (ML) engineers as the most in-demand role of 2024. The survey respondents said the biggest skills gap was in applying AI and ML to applications.
The fact that major IT services firms are ramping up their AI practices illustrates the role the IT industry sees for AI in plugging this skills gap. Recent product offerings from the major PC server manufacturers and IT consulting firms also show that the industry recognises the need for businesses to train their own GenAI models and host AI applications on-premise or in private clouds.
