The publishing industry is undergoing a profound transformation as digital-first strategies and artificial intelligence redefine the way content is created, managed, and delivered. To explore this shift, Rajeev Ranjan, Editor of Digital Terminal, spoke exclusively with Sameer Kanodia, Managing Director and CEO of Lumina Datamatics & Vice Chairman and CEO of TNQTech. In this conversation, Kanodia shares insights on how AI is no longer just a supporting tool but a core enabler in publishing workflows, revolutionizing editorial processes, enhancing accessibility, and driving measurable business outcomes.
Rajeev: How is the shift towards digital-first publishing changing the expectations for publishers in terms of speed, quality, and accessibility?
Sameer: The digital-first approach has set a much higher benchmark for publishers. Today readers expect instant access to content, seamless digital experiences, and formats that work across multiple devices. This has compelled publishers to compress production timelines while maintaining uncompromised editorial quality.
At the same time, accessibility is no longer optional, it is an essential mandate. Meeting global standards like web content accessibility guidelines ensures that content is inclusive and available to diverse audiences regardless of their abilities. Hence, publishers must balance speed, quality, and accessibility in every stage of their production workflows.
Rajeev: What factors are driving AI’s transition from a support tool to a core enabler in publishing workflows?
Sameer: Artificial intelligence has moved from being a support system to a core enabler in publishing because of three crucial factors, namely, scalability, accuracy, and adaptability. Content volumes are multiplying with time, and manual processes cannot keep up with the scale required to meet the customer’s expectations.
AI offers precision in several areas like metadata tagging, rights management, and accessibility compliance, tasks that demand both speed and accuracy. Furthermore, AI tools are highly adaptable, learning from past data to continuously improve. Overall, these capabilities make AI essential in today’s publishing ecosystem.
Rajeev: In what specific ways is AI transforming editorial functions such as proofreading, tagging, and assessment creation?
Sameer: AI is bringing efficiency and consistency to editorial tasks that were once cumbersome and labor-intensive. For proofreading, AI can identify not just grammatical errors but also style deviations and help maintain brand-specific editorial guidelines.
For tagging, AI ensures content is enriched with accurate metadata which improves discoverability and compliance. In assessment creation, AI can generate practice questions, quizzes, or comprehension checks from existing content, particularly supporting the education sector. These enhancements enable human editors to concentrate on high priority tasks like content research, development and curation.
Rajeev: How are AI-powered tools helping publishers meet rising accessibility standards and deliver inclusive content at scale?
Sameer: AI-powered accessibility tools help publishers to scale inclusivity in multiple ways that were previously impossible. Automated tools can generate alternative text for images, provide audio descriptions, and validate content against accessibility benchmarks like web content accessibility guidelines.
Moreover, they ensure consistent application of these standards across large volumes of content. This not only supports publishers comply with regulations but also establishes a genuine commitment to reaching all readers, including those with visual, auditory, or cognitive disorders.
Rajeev: What measurable business benefits have publishers achieved by adopting AI platforms in their production cycles?
Sameer: The business impact of AI adoption is quite evident. Publishers are reporting significant reductions in turnaround times, sometimes minimizing production cycles by up to 40%. Costs are reduced through automation of repetitive processes, while accuracy levels improve, curtailing the risk of rework.
In addition, improved metadata tagging and content enrichment drive discoverability, which automatically leads to stronger engagement and higher revenues. Perhaps most importantly, AI adoption enables publishers to scale rapidly without compromising on quality or compliance.
Rajeev: How do Lumina Datamatics’ modular, API-first AI platforms differentiate themselves in enabling publishers to scale with confidence?
Sameer: At Lumina Datamatics, our AI-based platforms are designed to be modular and API-first, ensuring seamless integration into existing publishing ecosystems. Publishers can adopt specific modules, such as AI-powered editorial enrichment, accessibility compliance, or workflow automation, without disrupting their existing infrastructure.
This flexibility permits them to scale at their own pace. In addition, our advanced platforms are built with resolvability and transparency in mind, which gives publishers confidence in the accuracy and accountability of AI-driven outputs. Eventually, we support publishers to transform their workflows with solutions that are agile, scalable, and future-ready.
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