Voice AI adoption in India is moving beyond early experimentation towards multilingual, integrated and outcome-oriented deployments. Nasscom at the BPM Confluence today has released the findings from its report India Voice AI Readiness 2026 in partnership with Krisp, a leading provider of Voice AI models and solutions. With capabilities including accent conversion, live speech-to-speech translation in 65 languages, voice security, agent assist and speech analytics, its technology is deployed on more than 200 million devices and processes over 80 billion voice minutes every month.
The report is based on survey responses from over 140 organizations across pure-play and integrated BPM providers with contact centre operations, GCCs with contact centres in India, organizations evaluating, piloting, or deploying Voice AI.
While adoption maturity varies across organisations, the study indicates a shift towards production deployments, with greater focus on enterprise integration, multilingual performance, governance and measurable business outcomes. As per the study findings, 31% of the surveyed organisations have progressed to limited production and around 13% have scaled Voice AI across multiple customer journeys. Although enterprise-wide scale remains at an early stage.
Organisations at higher levels of maturity are deploying multiple Voice AI capabilities in production, including inbound and outbound voice agents, automated QA, speech analytics and agent assist. BFSI, telecom, e-commerce, retail/CPG, travel and logistics among the major adoption sectors, owing to high interaction volumes, repetitive workflows, measurable returns and digitally accessible customer data. Structured, high-frequency workflows are the first use cases to scale across sectors.
Organisations increasingly view Voice AI as an operational transformation rather than a software purchase.As a result, partnership-led models are becoming central to scale Voice AI deployment in India. The survey finds that 41% of organisations use a hybrid model combining internal teams with external technology or implementation providers, while 29% co-develop Voice AI capabilities with partners.
The key proof point for Voice AI is efficiency as leaders move from measuring activity to business outcome metrics. As per the survey findings, 61% report more than a 20% reduction in cost per eligible interaction, showing that efficiency gains are already visible for many organisations. 30% of scaled organisations also report a positive impact on their revenue.
India’s Voice AI opportunity is closely linked to its multilingual domestic market.
As per the survey findings, over one-third of organisations have moved beyond bilingual Voice AI, supporting at least three Indian languages in production. Multilingual agents capable of handling four or more languages are also emerging as a growing deployment category.
Rajesh Nambiar, President, Nasscom, said, “Voice AI is creating a significant opportunity for India’s BPM sector to move beyond traditional voice operations towards AI-enabled, multilingual customer operations with greater ownership of outcomes. As organisations move from pilots to production, the opportunity will increasingly lie in building capabilities around multilingual performance, workflow integration, governance and continuous optimisation, areas that can strengthen India’s role in serving global customer operations.”
India has an opportunity to translate its growing multilingual Voice AI capabilities into solutions for global customer operations, leveraging the experience of deploying Voice AI across diverse languages, accents and customer environments. Among organisations with broader Indian language capabilities, 39% identify global or multi-region customer operations as a major opportunity. As production language coverage expands to three-to-five languages, organisations identify opportunities in North and Latin America and Europe and the UK, with broader multilingual capabilities also opening opportunities in the Middle East and Africa.
For India’s BPM industry, this creates an opportunity to move beyond traditional voice operations towards AI-enabled, multilingual customer operations. Over the next two years, investment priorities are expected to shift from pilots to the capabilities required for scaled deployment. While 68% of surveyed organisations report realising ROI within 6-24 months, two-thirds expect Voice AI investments to increase by up to 50%. Multilingual and Indian-language accuracy ranks among the top three spending priorities for 63% of organisations, alongside real time agent assist, QA analytics and autonomous voice agents.
Davit Baghdasaryan, Co-Founder and CEO of Krisp said “The future of Voice AI will be defined not by how many languages a system supports, but by how reliably it performs in real-world conversations. India’s multilingual, multi-accent and often noisy contact center environment makes it one of the most demanding markets for Voice AI, and a proving ground for technology built to operate at global scale. With 63% of organisations ranking language accuracy among their top three Voice AI spending priorities, the industry is recognising that performance starts with how clearly people are heard and understood. Organisations that get Voice AI right in India will be well positioned to serve customers anywhere.”
AI-mature organisations are expected to place greater emphasis on workflow orchestration, language-specific performance management, while early-stage organisations are more likely to focus on foundational telephony, cloud and pilot deployment capabilities.
India’s multilingual Voice AI readiness can become a competitive advantage in global customer experience, positioning the country as a hub for AI-enabled voice delivery. Realising this will require sustained investment and progress across operational and language constraints to translate India’s domestic capabilities into reliable, enterprise-scale global delivery.
Voice AI can become an important new chapter in India’s technology and service-delivery story if the industry converts domestic complexity into scalable global capability.