The build vs buy crossroads of AI for CX

In India’s dynamic market, customer experience (CX) is becoming a top priority–not as a buzzword, but because a single bad interaction is often all it takes for customers to walk away.  As demand grows for faster, more personalised support, organisations face an important crossroads: should they build artificial intelligence (AI) for CX in-house, or partner with experienced providers who offer ready-to-use solutions? 

It’s tempting to see AI for customer service as just another enterprise automation tool. In reality, effective AI for service must operate at the intersection of human empathy, real-time context, and brand identity–often in high-stakes, emotionally charged, and complex situations that directly impact customer trust and loyalty.

Unpacking the complexity of AI for CX 

Delivering great customer experiences in India is as nuanced as the market itself. Businesses serve customers across diverse languages, regions, and cultural contexts, all influencing how customers articulate their needs. With the rise of quick commerce and digital adoption, expectations for always-on, omnichannel support–delivered in their preferred languages and formats–continue to accelerate.

This diversity makes AI for service fundamentally different from other use cases. These systems must understand local languages, interpret emotional tone, and operate fluidly across platforms and channels. While building in-house AI can offer deep customisation, achieving the breadth, agility, and intelligence that today’s consumers expect is a significant challenge.

Crucially, implementing AI for service isn’t a one-off project. With AI technology rapidly evolving, businesses need dedicated teams, sustained engineering focus, and strong compliance discipline to keep pace with constant technological and regulatory change. Building effective AI for CX requires not just rich, domain-specific training data, but also careful workflow orchestration and a deep understanding of the logic that governs how AI agents interact and resolve issues–work that can tax even specialised teams. 

Then, there’s the question of speed. Developing tools from scratch drastically delays time-to-value. With AI entering the mainstream, expectations for personalised service are rising: 76% of Indian consumers say they expect more tailored service from brands using AI. For brands, this means that waiting months or even years to deliver impact simply isn’t an option. AI for CX needs to make an immediate difference, delivering faster resolutions and building personal connections from day one.

Partnering for better outcomes

Building in-house has its advantages. It promises control, customisation, and integration with existing systems. Yet, starting from scratch isn’t the only path to these advantages. 
 
Not all AI is created equal. There’s a fundamental difference between retrofitting generic AI models for customer service and using platforms specifically engineered for CX. Purpose-built AI for CX are designed for the realities of high-stakes, emotionally charged interactions. These solutions deliver accurate, contextually relevant responses and ensure complex situations receive timely human escalation across channels–capabilities that can otherwise demand extensive development and constant tuning when using general-purpose AI tools.  

Established CX platforms also dramatically accelerate time to value. Instead of spending months or years designing, building, and debugging custom tools, companies can deploy proven solutions in weeks, or even days. Solutions that offer low-code or no-code customisation also allow for rapid adaptation to changing needs without heavy IT reliance. 
This not only minimises the resource drain on engineering teams, but also enables them to focus on core business differentiators. 

Crucially, experienced providers manage ongoing compliance, security and platform updates. Their solutions evolve to meet new regulatory and business demands, without placing the burden of constant maintenance and vigilance on internal teams. 

Choosing an established partner also provides access to a dedicated CX support ecosystem, transparent costs, and the reliability of technology proven across a broad, demanding customer base. For Indian businesses in a rapidly changing market, these advantages make a compelling case for buying over building, enabling brands to deliver the kind of responsive, personal service their customers now expect.

Simplicity and security at scale  

Strong AI governance and ease of management are not simply checkboxes–they’re essentials as customer service becomes more complex. Leading AI platforms unify orchestration, workflow management, and performance monitoring so teams gain clear oversight of every customer journey in one place. 

Equally, robust security and compliance frameworks are critical. Not all providers guarantee the same standards, so organisations should prioritise those with features like transparent agent behavior, audit trails, and intuitive tools for ongoing refinement. Enterprise-grade certifications–such as HIPAA, SOC 2, GDPR, ISO 27001 and ISO 42001–reduce operational risk and offload the burden of keeping up with evolving requirements. 

Focus where it counts

The build-versus-buy debate often centres on control and ownership. For many businesses, the urge to build feels like a natural extension of innovation–a way to create something truly their own. However, in a rapidly evolving market like India, success lies not just in building the technology, but in how effectively it’s applied to deliver seamless, human-centred experiences.

While building from scratch may suit a select few with unique needs and deep resources, for most organisations, purpose-built AI solutions offer a more practical and scalable way to deliver standout customer experiences.

Purpose-built, agentic AI solutions give businesses that advantage, by taking on the heavy lifting of orchestration, maintenance, and governance. It allows companies to focus on where it truly counts–enhancing products, empowering people, and strengthening customer trust. In the end, the smartest investments are those that keep innovation focused on a business’s core strengths. 

Siddarth Shah

---

Siddarth Shah, Director, India, Zendesk