Overview:
In this fortnightly, we shift our focus back to the tech industry’s favorite subject – Gen AI. In the IT services world, there are several large companies that have built solutions around Gen AI.
Leading companies such as Accenture, TCS, Infosys, and Wipro are also showcasing their solutions to gain an early foothold in this market. While large scale adoption of such solutions across enterprises is still a few years down the road, we see several use cases emerging across sectors, especially in the automation and customer service verticals.
IT services firms are developing AI-powered solutions and IP around AIOps, Algo Retail, smart manufacturing, digital twins and robotics.
Training of professionals is Gen AI technologies is one of the key hurdles that the industry faces in the development and implementation of such solutions.
What are some of the leading players doing in the Gen AI space?
Accenture was the first IT services company to announce its Gen AI revenues in Q3 of this year. The company clocked $100 million in sales from over 100 projects in Gen AI. Its solutions focus in five key areas – decisions making, content creation, software coding, process automation and security. Over the last few years, Accenture has invested $3 billion in data and AI technologies and plans to double its talent base in these areas to over 80,000 professionals.
TCS has 50 Gen AI projects in the concept stage and another 100 in the pipeline. The company has started advising clients on creating a roadmap for Gen AI adoption and has started training its workforce across multiple Gen AI solutions in partnership with hyperscalers, aimed at creating an AI-trained talent pool of ~100,000 professionals.
Infosys launched Topaz, a Gen AI focused platform and is working on 80 Gen AI projects. Topaz has over 12,000 use cases, more than 150 pre-trained AI models and more than 10 AI platforms that can be deployed across multiple industries. Internally, the company has started implementing AI in various aspects of its software development and coding process, with real-time feedback from AI on coding standards and quality. Infosys has ~40,000 AI-trained professionals.
Cognizant plans to invest $1 billion in Gen AI capabilities over the next three years and currently engaged with 100 clients on the implementing AI based solutions. It also has built Cognizant Neuro AI, a library of reusable Gen AI models and tools.
Wipro launched Wipro ai360 in July 2023, an AI-first innovation ecosystem, and has committed to investing $1 billion in AI capabilities over the next three years. The company also plans to integrate Google Cloud’s full suite of Gen AI products and services with its own intellectual property, business accelerators and pre-built industry solutions.
Challenges ahead:
While Gen AI may be the future of the technology industry, there are several hurdles such as quality of data, the lack of a large talent pool, and large-scale use cases.
Moreover, there are several privacy concerns and regulatory barriers to the successful implementation of Gen AI solutions. In industries such as healthcare and financials services, safeguarding of patient and customer data respectively are paramount.
While applications such as ChatGPT, GITHub Copilot and Stable Diffusion may have captured the attention of the industry, enterprise-level implementations are still a few years down the road. The bottom line is that Gen AI solutions are simply not stable enough to be implemented at scale.
There is also the case of technologists trying to force-fit a Gen AI solution to a problem, rather than independently trying to find a solution for the same problem. Solutions in areas of predictive and prescriptive analytics have been around for years, and such solutions are perfectly capable of solving a majority of the industry’s problems.
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