Kuljesh Puri is Senior Vice President and General Manager of Media & Technology Communications, Media & Technology at Persistent Systems. He brings over 26 years of experience in the software, telecom and semiconductor industries, as well as a wide range of international risks and passion for transformation.
Prior to joining Persistent, Kuljesh led Tech Mahindra’s telecom product engineering portfolio. Prior to that, he worked at Samsung’s Harman International, where he served as Vice President and Global General Manager for Telecom and Industrial Verticals, and forced the growth trajectory of the business. Earlier, Kuljesh held senior business and engineering positions at Aricent in both B2B and B2C businesses.
Persistent Systems is a global digital engineering and enterprise modernization company that works with enterprises to drive innovation and accelerate digital transformation. With deep expertise in software, cloud and data, continuity delivers end-to-end solutions across industries including healthcare, financial services, communications and technology.
What is the most transformative way you see AI-impacted call center operations in telecommunications and media today?
Traditionally, contact centers are cost centers designed to handle customer inquiries. Over the years, from a phone-based call center, customer service has evolved into a multi-channel service center through chat, email and mobile applications. Key innovations such as seamless omnichannel experiences, AI-powered multilingual self-service, sentiment analytics and predictive churn management are no longer optional – they are essential. Meanwhile, proxy AI goes beyond scripted chatbots by fully handling end-to-end tasks such as billing corrections, planned upgrades, or technical troubleshooting without human intervention. Overall, AI enables businesses to anticipate customer needs rather than simply responding to them by switching from reactive support to prediction, personalization, and self-improvement. The result is the ability to improve operational efficiency and improve customer satisfaction and loyalty. By reducing costs and improving services, AI transforms call centers from traditional cost centers to high-value, customer-centric hubs that directly affect revenue.
How do predictive analytics, automation and NLP improve real-time customer interaction?
The integration of predictive analytics, automation, and natural language processing (NLP) is revolutionizing how we interact with customers in real time. Predictive analytics allows organizations to predict customer behavior and provide proactive solutions. Automation speeds up the process, ensuring quick response to customer queries while minimizing human error. NLP, on the other hand, gives chatbots and virtual assistants to have more natural human-like conversations, thereby improving service quality and speed. After the merger, these technologies create an environment that enables customer interactions faster and more personalized, thereby enhancing customer experience and promoting loyalty.
Does AI help create a more seamless omnichannel customer experience?
AI is a key component of a seamless omnichannel client experience. It enables companies to integrate interactions across a variety of channels – whether it’s chatbots on websites, conversations on social media or phone calls to contact centers. By merging data from these touchpoints, AI ensures that messaging is consistent and tailored to each client. The real power of AI lies in its ability to personalize these interactions, ensuring customers receive relevant, context-aware support across channels. This creates a frictionless experience where customers can move from one contact point to another without losing continuity.
With extensive experience working with telecom and media companies, we help organizations leverage AI to simplify customer journeys, improve workflows, and deliver a unified experience. This enables customers to create a more seamless personalized service that increases satisfaction and drives lasting loyalty.
What are the most common pain points when an organization deploys AI to a call center?
One of the biggest challenges organizations face when deploying AI in call centers is integrating it with legacy systems. Many traditional contact centers, especially those relying on local solutions, lack the infrastructure to support advanced AI capabilities. Migrating to the cloud is crucial to unlocking the full potential of AI, but this transition can be complex and expensive. Additionally, AI models require high-quality, well-organized data, which traditional systems are often difficult to provide. Ensuring a smooth transition without disrupting the customer experience is another major obstacle. Privacy and security issues regarding data usage also need to be fully addressed.
Organizations need an experienced partner to address these challenges, which is a deep understanding of AI and industry-specific needs. We have helped many telecom companies and media companies modernize their contact centers, overcome these pain points, and ensure a seamless transition to increase operational efficiency and enhance overall customer experience.
For example, Persistent works with leading U.S. telecom technology providers to enhance the operations of its contact centers. Customers want to analyze customer interactions through their conversational AI platform to understand insights on customer satisfaction and agent performance. We have developed a GCP-powered data analysis layer that processes data from over 30 real-time streaming pipelines that process more than a billion messages per day. The solution provides nearly real-time insights to help customers monitor key metrics such as caller sentiment and service satisfaction, ultimately improving customer experience and operational efficiency.
By working with experts who understand the AI and telecommunications industries, organizations can overcome common deployment challenges, modernize their contact centers, and unlock valuable data-driven insights to enhance customer interaction and drive operational improvements.
What is the biggest difference between how telecom companies and media companies adopt AI for their customers?
The telecommunications department has long been a pioneer in establishing large-scale contact centers, driven by basic services such as management of basic services such as billing queries, new connections and solving connection problems. These features remain at the heart of the industry, and AI is increasingly leveraging these features to optimize operations in these areas as they represent a large portion of customer support tickets. Given the competitive landscape, many telecom operators also use predictive analytics to predict customer churn, achieving their targeted marketing campaigns and retention strategies.
By contrast, media companies focus on AI for different purposes, such as detecting account sharing, managing subscriptions, analyzing viewing patterns, curating content, and enhancing customer engagement with automatically provided self-service options.
At Persistent, we have partnered with telecom companies and media companies to tailor AI solutions that meet their unique challenges. For Telecom, we focus on improving operational efficiency and leveraging predictive analytics to drive proactive customer service. For media companies, we aim to enhance customer engagement through AI-driven advice, content personalization, and self-service automation.
In your experience, fully embracing AI in these departments is a necessary cultural or organizational transformation?
To fully embrace AI, telecommunications and media companies must go through a cultural shift in becoming data-driven organizations. This requires cultivating a mindset of continuous learning and innovation in various departments. AI adoption is not only an IT initiative, but also requires cross-departmental collaboration, especially between IT, customer service and operations. Companies must invest in AI talent and focus on re-applying their existing workforce to ensure they have the skills to manage and work with AI systems. Furthermore, adopting an agile methodology is critical to allow organizations to iterate rapidly and optimize their AI solutions. Strong leadership drives these changes and ensures that AI plans align with overall business goals, especially to improve customer experience while driving business outcomes.
How does the Starfish Association acquisition enhance Persistent’s AI-driven contact center and unified communication capabilities?
The acquisition of Starfish Association greatly improves the position of durability in AI-driven contact centers and unified communication spaces. This strategic acquisition builds on our existing engineering capabilities in the contact center and unified communications sectors, expands our AI-driven business transformation expertise and strengthens our focus on operational excellence. Starfish Associates is known for its cutting-edge enterprise communications automation platform, which serves some of the world’s largest businesses, including many Fortune 500 companies. When combined with the persistence advantages in AI-driven automation, this acquisition enables us to deliver stronger, integrated solutions to simplify workflows, enhance customer engagement and increase operational efficiency.
Data security and privacy are major issues in telecommunications organizations – how to continuously address these issues in AI-aa-Spair customer service solutions?
Data security and privacy are key issues, especially in the telecom industry where customer data is sensitive and highly regulated. At Persistent, we help telecom companies address these challenges by implementing AI solutions to ensure every step of data protection. We support our customers in compliance with global regulations such as GDPR, CCPA and other data protection laws, embed privacy protection measures into their AI-driven customer service operations.
We assist customers in integrating reliable security features including encryption, anonymity and access controls to ensure data throughout their lifecycle. Furthermore, we have a clear understanding of its use and management by helping our customers maintain full control of their data, thus ensuring transparency is visible. By providing ongoing AI model reviews and risk assessments, we ensure that our solutions remain safe, compliant and adaptable as regulations evolve, giving our customers confidence to responsibly leverage AI technologies while maintaining customer trust.
Finally, how successful have you performed over the next five years for the AI-powered customer experience of telecom players?
Over the next five years, AI will redefine the role of contact centers in the telecommunications industry. Success will be measured by the ability of telecom companies to transform traditional call centers into active customer engagement centers. Agesic AI will transform the telecom customer experience by proactively solving problems, providing personalized support and implementing autonomous service actions across channels. Learning from interaction to adapt in real time ensures faster, smarter and more human-like engagement is key to the transformation of customer experience.
By offloading 50%-60% of regular customer service tasks into proxy AI, telecom operators can improve efficiency while allowing human agents to focus on more complex problems. Predictive analytics will play a key role in predicting customer needs, while omnichannel integration will ensure a seamless experience across all touchpoints.
In persistence, we help telecom and media companies implement proxy AI solutions to drive innovation and improve customer interaction. Our expertise in AI and telecommunications enables the creation of smarter, more agile contact centers that leverage data to align with business goals. Going forward, our goal is to help these organizations safely inject AI into their operations, deepen their connections with their customers, and position them as success in a rapidly growing digital landscape.
Thanks for your excellent interview, and hopefully learn more about the readers who should access the persistent system.
