CIOInsider India Magazine

Sameer is a highly regarded business leader with more than 25 years of experience in monetization, forging strategic partnerships, and launching high-growth solutions in sectors including Healthcare, Energy, and Oil & Gas.

Customer experience (CX) has emerged as a significant application for AI-driven technologies as consumer expectations continue to rise. Today, integrating AI is a crucial element of any contemporary digital transformation initiative. AI technologies powering CX include machine learning, natural language processing (NLP), Robotic Process Automation, and predictive analytics, among others. These technologies improve customer interactions by examining and processing large volumes of customer data and drawing insights from and acting on it. This enables highly tailored customer experiences that meet customer needs at every touchpoint and boost operational efficiency. In an exclusive interview with CIO Insider India, Sameer Koul, Co-Founder & Customer Specialist - Dashamlav AI Labs, shares his insights on the impact of AI on sales and marketing, along with human empathy.

How do you perceive the evolution of marketing in the age of AI?
Marketing has evolved in this AI-driven age, and we are still determining whether these shifts are drastic or part of the natural progression of marketing. However, changes are indeed present. From my experience in marketing and sales over the last 25 years, I've had hands-on experience with this transformation. Previously, marketing efforts were geared towards broader audiences. We would identify a particular segment and initiate numerous marketing campaigns targeting that segment at a macro level. Nowadays, the focus has shifted to micro-targeted marketing, which, even if not highly personalized, is more specific.

In the past, we conducted manual analysis, scrutinizing organizations' balance sheets, P&L statements, and their objectives. This process was quite labor-intensive. For instance, to acquire customers, I would review their annual reports. While I still consult annual reports today, the process has become much more efficient; I can simply upload the report and pose a few questions, and AI will generate insights for me. This advancement has made it real-time. Additionally, messaging used to be one-directional, and now it functions as a two-way communication channel. Implementing chatbots allows us to interact with customers, marking a significant shift from general marketing to a more personalized approach.

What part does AI play in the growing demand for customer experience?
I would say that with the rise of AI, customer expectations have increased. Customers continuously seek greater customization of their needs, which has led to higher expectations for support. Service Level Agreements (SLAs) have also evolved; in the past, customers might have agreed to a certain percentage, but now, SLAs have become more stringent with AI. Services are expected to be available around the clock. Given the various predictive analysis tools that can be created with AI, customers now anticipate that the service or product provider should be able to anticipate their needs, predicting what they may ask for after utilizing the service or product. This trend has escalated and continues to develop.

What does AI mean for organizational expectations, resources and results of marketing campaigns?
We previously utilized various tools like CRMs and Excel sheets to analyze results and identify areas for improvement. AI has completely altered this paradigm with a strong focus on process orientation. Even when outcomes are lacking, AI can predict the necessary activities for achieving results, making communication highly targeted. Instead of sending generic messages to all employees regarding sales or finance, communication is now customized based on specific processes. This has led organizations to streamline resource allocation better.
With AI, CRMs have evolved to be more intelligent, and processes have become interactive. Real-time reporting is now achievable, fostering increased transparency. For instance, if you were assigned a task in the past, there may have been numerous excuses for its completion. Today, it's much harder to fabricate excuses, as AI can predict these scenarios. Consequently, while excuses may arise, definitive actions are identified. Besides, transparency has improved, and real-time assessments have enhanced execution and monitoring.