Accenture’s AI Refinery platform supports businesses in integrating AI agents, collaborating with software professionals to rapidly build and deploy AI-driven networks, streamlining operations and driving innovation across organizations
The transition from traditional AI models to autonomous systems is reshaping the workforce, requiring AI practitioners to acquire new competencies. Speaking at the Nasscom Technology & Leadership Forum 2025 in Mumbai, Senthil Ramani, Accenture’s lead for data & AI, shed light on the evolving skills and roles needed to drive the future of AI.
Ramani stressed that AI is unlocking new potential in organizations, driving them to rewire their operations. "AI is breaking the code on action and intelligence. Organizations are going to rewire and reinvent themselves. It is a huge opportunity to act now," he stated. According to Accenture, over 50,000 professionals worldwide have been trained on its Agentic AI platform, with a significant presence in India, highlighting the global demand for AI expertise.
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To help businesses harness AI, Accenture has introduced the AI Refinery platform. This platform facilitates the integration of AI agents into organizations, working alongside software professionals to build and deploy AI-powered networks. Serving 12 industries, the platform aims to accelerate the development of AI solutions and drive efficiency.
Shaping AI roles and collaboration
One of Ramani’s key points was the importance of effective data management. He urged businesses to engage in “dialogue with data,” meaning that organizations need to integrate AI models into their day-to-day operations to ensure widespread usage and adoption. “If businesses can communicate effectively with data, they have already diffused AI into their processes,” he explained.
The evolution of AI roles is another major trend. Data engineers are now using Generative AI (GenAI) to automate processes and improve data quality. AI/ML computational scientists are moving toward using GenAI and retrieval-augmented generation (RAG) for advanced model development. The role of large language model (LLM) architects is also expanding, as professionals will now focus on creating systems for AI agents capable of autonomous decision-making.
Ramani also highlighted the growing need for collaboration across teams. AI specialists, data analysts, business professionals, and governance experts must now work more closely than ever to ensure that AI is successfully integrated across organizations. This shift in mindset will be crucial for businesses to fully capitalize on AI’s potential.
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