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Time of India
6 hours ago
- Business
- Time of India
Agent economy has arrived: Can India leapfrog the platform era?
Not long ago, transformation meant thick slide decks, long timelines and consultants advising from the sidelines. They brought frameworks, not outcomes. Today, in a world shaped by generative and agentic AI, businesses are no longer looking for advisors. They're looking for co-creators: partners whose contribution is defined not through scale of people, but through scale of intelligence and an ability to rapidly deliver tangible business value. Independence Day 2025 Before Trump, British used tariffs to kill Indian textile Bank of Azad Hind: When Netaji gave India its own currency Swadeshi 2.0: India is no longer just a market, it's a maker Agentic AI makes this shift possible. These systems don't just assist but act, learn and adapt within business workflows. They minimise manual intervention and integrate directly into enterprise environments. From onboarding and compliance to reconciliation and customer support, agents execute autonomously, continuously and intelligently. Importantly, this isn't the end of platforms. It's their evolution. Agentic AI thrives on strong digital infrastructure, data pipelines and system integration. Together, platforms and agents form intelligent environments where actions are automated and outcomes accelerated. This changes the game for India. India led the platform era, powered by deep engineering talent and global delivery scale. Now, that talent base becomes a launchpad. The agent economy rewards not just scale, but speed, accuracy and intelligence and calls for a reinvention of how technology is built, deployed and delivered. India's historic strength is application-level innovation. In an age of agentic AI, this is the crucial level - beyond chipset and large language model innovation - where business acceleration is unlocked and organisations can create the greatest value. It's where agentic AI comes alive: embedded in enterprise workflows, customised for real-world processes and scaled with precision. Live Events With a global high-end engineering backbone rooted in India, Publicis Sapient is deploying agentic AI to transform how businesses operate. Our proprietary Bodhi platform enables rapid agent deployment, while Sapient Slingshot and CoreAI, built on Bodhi, transform enterprise software development and marketing, respectively. Our India-based teams not only write code but orchestrate complex enterprise environments to make agents effective - in use cases from autonomous onboarding solutions for financial services to agents that manage regulatory compliance for pharmaceutical companies and streamline logistics for retailers. We've built agent-driven platforms that cut manual reconciliation by 80%, and helped Fortune 500 firms develop AI-native capabilities that evolve in real time. Our SPEED capabilities-strategy, product, experience, engineering, and data with AI-embeds agents into enterprise architecture where they act, learn and scale. To realise India's potential in the agent economy, three key shifts are needed. First, move from integration to orchestration. Agents can't function in silos. To be autonomous, they must be embedded within business logic and workflows-not layered onto legacy systems. Publicis Sapient's approach to system orchestration, rooted in domain expertise and agile delivery, shows how India-based teams can lead in building intelligent enterprises . Second, rethink how value is measured. In the agent economy, the traditional time-and-materials model gives way to value-based engagements. Success is defined by reducing onboarding time, improving compliance accuracy, and driving faster time to value through autonomous execution. Third, expect speed to match ambition. The era of 18-month timelines is over. AI-native delivery models allow for rapid prototyping, refinement, and deployment - in weeks, not quarters. The rise of agentic AI isn't just technological. It's philosophical. It raises the question 'what can AI agents do on their own and where do humans add the most unique value?' This mindset shift lets us redeploy human talent toward higher-value tasks: strategy, judgment, creativity and orchestration. India is uniquely positioned to lead this future. It has the scale, the talent and the mindset. If India commits to building the agentic layer of the enterprise, it won't just ride the next wave - it will define it. (Nigel Vaz is CEO of Publicis Sapient. He will be speaking at The Economic Times World Leaders Forum in New Delhi)
Economic Times
6 hours ago
- Business
- Economic Times
Agent economy has arrived: Can India leapfrog the platform era?
Not long ago, transformation meant thick slide decks, long timelines and consultants advising from the sidelines. They brought frameworks, not outcomes. Today, in a world shaped by generative and agentic AI, businesses are no longer looking for advisors. They're looking for co-creators: partners whose contribution is defined not through scale of people, but through scale of intelligence and an ability to rapidly deliver tangible business AI makes this shift possible. These systems don't just assist but act, learn and adapt within business workflows. They minimise manual intervention and integrate directly into enterprise environments. From onboarding and compliance to reconciliation and customer support, agents execute autonomously, continuously and intelligently. Importantly, this isn't the end of platforms. It's their evolution. Agentic AI thrives on strong digital infrastructure, data pipelines and system integration. Together, platforms and agents form intelligent environments where actions are automated and outcomes accelerated. This changes the game for India. India led the platform era, powered by deep engineering talent and global delivery scale. Now, that talent base becomes a launchpad. The agent economy rewards not just scale, but speed, accuracy and intelligence and calls for a reinvention of how technology is built, deployed and delivered. India's historic strength is application-level innovation. In an age of agentic AI, this is the crucial level - beyond chipset and large language model innovation - where business acceleration is unlocked and organisations can create the greatest value. It's where agentic AI comes alive: embedded in enterprise workflows, customised for real-world processes and scaled with precision. With a global high-end engineering backbone rooted in India, Publicis Sapient is deploying agentic AI to transform how businesses operate. Our proprietary Bodhi platform enables rapid agent deployment, while Sapient Slingshot and CoreAI, built on Bodhi, transform enterprise software development and marketing, respectively. Our India-based teams not only write code but orchestrate complex enterprise environments to make agents effective - in use cases from autonomous onboarding solutions for financial services to agents that manage regulatory compliance for pharmaceutical companies and streamline logistics for built agent-driven platforms that cut manual reconciliation by 80%, and helped Fortune 500 firms develop AI-native capabilities that evolve in real time. Our SPEED capabilities-strategy, product, experience, engineering, and data with AI-embeds agents into enterprise architecture where they act, learn and realise India's potential in the agent economy, three key shifts are move from integration to orchestration. Agents can't function in silos. To be autonomous, they must be embedded within business logic and workflows-not layered onto legacy systems. Publicis Sapient's approach to system orchestration, rooted in domain expertise and agile delivery, shows how India-based teams can lead in building intelligent rethink how value is measured. In the agent economy, the traditional time-and-materials model gives way to value-based engagements. Success is defined by reducing onboarding time, improving compliance accuracy, and driving faster time to value through autonomous execution. Third, expect speed to match ambition. The era of 18-month timelines is over. AI-native delivery models allow for rapid prototyping, refinement, and deployment - in weeks, not quarters. The rise of agentic AI isn't just technological. It's philosophical. It raises the question 'what can AI agents do on their own and where do humans add the most unique value?' This mindset shift lets us redeploy human talent toward higher-value tasks: strategy, judgment, creativity and is uniquely positioned to lead this future. It has the scale, the talent and the mindset. If India commits to building the agentic layer of the enterprise, it won't just ride the next wave - it will define it. (Nigel Vaz is CEO of Publicis Sapient. He will be speaking at The Economic Times World Leaders Forum in New Delhi)
Yahoo
13-05-2025
- Business
- Yahoo
Enterprises eye AI assistants to modernize systems
This story was originally published on CIO Dive. To receive daily news and insights, subscribe to our free daily CIO Dive newsletter. Enterprises are turning to generative AI tools to drive modernization and cut through technical debt, according to Publicis Sapient. The digital consulting firm commissioned HFS Research to survey more than 600 IT and business leaders for a report published Thursday. Four in 5 respondents expect generative AI coding assistants to help them break free from managing outdated systems by documenting legacy applications, rewriting old code and automating software testing, the report found. Technical debt is an expensive headache, accounting for $1.5 trillion to $2 trillion in spending among Global 2000 companies, according to HFS Research. 'Tech debt isn't just a weight — it's a ticking time bomb that's threatening the future of global enterprises,' the firm's Chief Analyst and CEO Phil Fersht said in the report. As coding assistants rose to the top of a heap of generative AI use cases with ROI potential, vendors mobilized to deploy tools trained to decipher and refactor decades-old applications. IBM taught watsonx more than 100 programming languages and trained its open model to translate COBOL applications into Java. AWS trained its AI assistant, Amazon Q Developer, to build applications and set the tool loose on mainframe modernization last year. As cloud and enterprise software vendors rolled out similar capabilities, banking became a proving ground for the technology, according to Accenture. Goldman Sachs saw its army of 12,000 developers achieve efficiency gains of roughly 20% with GitHub Copilot, the company's CIO Marco Argenti told CIO Dive last month. Bank of America and Citigroup saw similar returns on AI investments. Enterprises across industries can cut years off of modernization initiatives by harnessing the technology, according to Sheldon Monteiro, Publicis Sapient EVP and chief product officer. 'AI really is a jackhammer,' Monteiro said in an interview. 'CIOs need to be thinking about this in terms of some pretty major concrete breaking.' Publicis Sapient inked a five-year partnership with AWS to build AI-powered modernization tools in March. In addition to leveraging the hyperscaler's cloud-based services, the alliance aims to expand the reach of the Sapient Slingshot software development platform. The modernization opportunities are vast, according to HFS Research. A $1.5 trillion IT industry has grown up around servicing rather than eliminating technical debt, the firm estimates. Enterprises spend an average of nearly 30% of IT budgets maintaining legacy technologies, the report found. Yet, fewer than one-third of respondents said their organization has modernized core applications. 'Something's broken in the way clients are buying IT services and the way the service industry has been incentivized,' Monteiro said, pointing to a tendency to see staff augmentation as a means of containing technical debt. Monteiro added, 'If modernization is going to take 10 years to complete, what CIO is going to look at that with any sense that it can get done within their tenure?' Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
