Lab to launch: The Hindu’s AI integration strategy
Speaking at our recent Bangalore AI Forum, Suresh Vijayaraghavan, Chief Technology Officer at The Hindu, detailed the publication’s AI journey – highlighting the challenges of moving from standalone experiments to full-scale integration within editorial and production workflows.
“AI in isolation is innovation, but AI in production is transformation,” Vijayaraghavan said, underscoring the need for seamless AI integration rather than relying on fragmented tools.
From siloed systems to an integrated platform
For over a decade, The Hindu has adopted various digital tools, including e-paper platforms, paywalls, SEO systems, social media automation, and recommendation engines. However, these systems operated independently, creating inefficiencies in editorial workflows.
By 2020, the company launched a three-year digital transformation to unify its CMS, analytics, and AI-powered tools into a single integrated platform. The system, completed in 2023, enables journalists to track article performance, analyse audience engagement, and access AI-driven features – all within the CMS.
“We must avoid repeating past mistakes – building AI tools in isolation, only to spend years integrating them later,” Vijayaraghavan warned.
The Hindu is deploying AI across multiple editorial and production areas, including headline and summary generation, SEO optimisation, content translation, video and audio generation, and archival system integration.
These AI-driven tools assist journalists rather than replace them.
“Journalism is the final product. AI can help streamline processes, but the essence of journalism remains human-driven,” he said.
Key technical challenges in AI integration
Vijayaraghavan highlighted several key challenges in scaling AI from experimentation to production. These include aligning AI with existing business processes, handling real-time data inconsistencies, ensuring model accuracy, and addressing security risks.
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Business process alignment
Integrating AI into The Hindu’s content creation, publishing, and archival workflows requires a structured approach. AI tools must:
- Seamlessly interact with the CMS, paywalls, and digital archives.
- Be optimised for different content formats – text, images, video, and audio.
- Have intuitive UI/UX within the newsroom workflow so that journalists can access AI assistance without disrupting their process.
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Real-time data integration and inconsistencies
AI models require live data stream access, but real-world newsroom environments present challenges such as:
- Inconsistent metadata across different publishing systems.
- Delayed updates between CMS, analytics, and archival platforms.
- Managing real-time performance to ensure AI-generated insights are instantly available rather than requiring manual data processing.
The Hindu is also experimenting with retrieval-augmented generation (RAG) to enhance its archival search.
“We are working on a RAG-based experiment where our archival system, 147 years of our archive, is going to be tagged by a model. As I create an article, the model understands the context and suggests related archival articles in real time,” Vijayaraghavan said.
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Performance and scalability
For AI to be production-ready, it must deliver results quickly and efficiently. Key challenges include:
- Inference speed: Ensuring AI models return outputs instantly, without slowing down newsroom workflows.
- Optimising AI deployment: Deciding between cloud, on-premise, or edge computing to balance cost and performance.
- Scalability: Ensuring AI can handle high workloads, especially during breaking news coverage.
While AI has streamlined workflows, its direct financial impact is still uncertain.
“My developers are good. Now they get a code coming to them very fast, but it has not improved the bottom line. That means there is no measurable impact to the bottom line because of what you’re doing,” Vijayaraghavan said.
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Model drift and continuous learning
As AI models evolve, they can produce inconsistent or biased outputs over time. To maintain reliability, The Hindu is implementing:
- Automated retraining pipelines to keep AI models up to date.
- Feedback loops to fine-tune AI-generated summaries, headlines, and recommendations.
- Editorial oversight mechanisms to ensure AI aligns with The Hindu’s journalistic standards.
One of the participants during the Q&A round.
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Security, compliance, and governance
As AI governance continues to evolve, The Hindu is addressing risks related to security, compliance, and ethical AI usage. Key concerns include:
- Cybersecurity risks such as AI model poisoning, where bad actors manipulate AI-generated outputs.
- AI audit trails: Tracking how AI modifies content to ensure transparency.
- Regulatory compliance: Adhering to GDPR and India’s DPDPA to maintain data privacy and ethical AI practices.
- Bias detection analytics: Ensuring AI does not reinforce systemic biases in news coverage.
“These challenges must be addressed at every stage of AI implementation to ensure that AI enhances, rather than disrupts, newsroom operations,” Vijayaraghavan said
AI integration strategy: A unified approach
To ensure sustainable AI adoption, The Hindu follows a three-pronged strategy.
A unified AI architecture ensures AI tools are seamlessly embedded within the CMS, supporting content creation, publishing, and analytics while avoiding workflow disruptions.
AI governance and compliance ensures AI-generated content aligns with editorial policies and regulatory standards such as GDPR and India’s DPDPA. This includes implementing bias detection analytics to prevent systemic biases in reporting.
Industry collaboration and AI research is a key focus, as The Hindu’s CMS is provided by a Danish vendor used by multiple publishers. The company has joined a publisher-led AI advisory consortium to guide CMS development.
“This collaboration ensures that AI integration benefits all publishers using the platform,” Vijayaraghavan noted.
This consortium helps shape CMS-level AI developments, ensuring that newsroom-friendly AI features – such as audit trails and seamless CMS integration – are developed collaboratively.
While AI-driven analytics can optimise news production, Vijayaraghavan cautioned against over-reliance on AI-generated trends.
“If we rely only on AI trends, we become followers, not leaders. Journalism should surprise readers with what they didn’t know they wanted to read,” he explained.
He also addressed the ongoing challenge of audience engagement in the digital era.
“Direct traffic from loyal readers – those who have bookmarked our site – is crucial. At the same time, we must navigate the reality that a significant portion of traffic still comes via search,” Vijayaraghavan said.
