Vala Afshar, Chief Digital Evangelist at Salesforce, has emphasized India's pivotal role in the tech giant's global strategy, stating that the nation's success will have a direct impact on Salesforce's own growth. Afshar highlighted India as a key market for enterprise AI adoption, attributing this to its robust digital infrastructure, dynamic startup activity, and escalating technology spending.
India: A Critical Hub for Salesforce's Global Strategy
Salesforce views India not only as a significant talent and engineering hub but also as one of its fastest-growing enterprise markets. The company's commitment to India, which launched in 2001, has seen its employee count surge from approximately 2,000 to nearly 17,000. Afshar underscored the extraordinary talent pool and rapid digital adoption pace in India, noting that the country already boasts two million Salesforce developers and nearly three million learners on its Trailhead online learning platform.
According to IDC, the Salesforce ecosystem alone is projected to contribute nearly $89 billion in new business revenues in India by 2028. The nation's burgeoning startup ecosystem, now home to 131 unicorns, is also attracting significant investment from Salesforce Ventures, with a substantial number of these startups focused on AI.
Leading Enterprise AI Adoption Use Cases
Afshar identified customer service and support as the primary areas seeing the strongest AI adoption globally. This is largely due to these operations already having structured workflows, governance models, and service-level agreements. Approximately 60% of current enterprise agent adoption occurs in service operations, targeting repetitive, deterministic, and process-driven tasks for automation.
Sales functions represent the second-largest area of adoption, leveraging AI for internal coaching, forecasting, and external customer engagement. Marketing and commerce are also rapidly accelerating their use of AI. In commerce, the scale of change is particularly significant; Salesforce Commerce Cloud processed nearly $1.3 trillion in global commerce transactions in November and December 2025 alone, with about $262 billion involving AI-driven recommendations or automated customer engagement to personalize experiences based on purchase history and preferences.
Measuring Returns and Organizational Transformation
The primary returns companies expect from AI and automation investments are increased speed and operational efficiency. Businesses continue to measure success through traditional KPIs such as marketing conversion, sales productivity, customer service resolution times, and overall operational efficiency. What has changed dramatically, Afshar noted, is the speed at which these outcomes can be achieved.
"Before an important customer meeting, I can ask an agent to instantly generate a customer profile, financial performance insights, competitive positioning, previous meeting history and recommendations on how to position Salesforce products. Earlier, gathering that information could take days or weeks. Now it happens in real time," Afshar explained.
At Salesforce, over 60,000 employees actively use AI agents daily to synthesize information and generate insights instantly, rather than manually sifting through dashboards and reports. However, Afshar warned that many enterprises underestimate the organizational and cultural shifts required for AI transformation. This transition necessitates redesigning workflows, reskilling employees, redeploying talent, and recalibrating performance metrics. Salesforce itself redeployed nearly 3,000 employees into sales functions after automating repetitive tasks with AI systems.
Evolving SaaS Models and Market Positioning
Traditional licensing models are rapidly evolving. Companies are experimenting with hybrid pricing structures that combine subscription-based pricing, consumption models, and impact-based pricing. Customers still desire predictable enterprise licensing but are also exploring how automation and token usage will scale within their organizations. More broadly, businesses are shifting from viewing software platforms merely as productivity tools to seeing intelligent systems as operational contributors, moving towards what Salesforce describes as digital labor platforms.
Regarding competition in enterprise AI, Afshar stated that successful companies remain intensely focused on customers rather than competitors, striving to deliver measurable outcomes. He highlighted that many companies often perceived as competitors, such as Microsoft, Google, and Amazon, are also Salesforce customers and strategic partners, especially in areas like cloud infrastructure and local data residency requirements.
Addressing Barriers to Enterprise AI Adoption
Afshar identified culture as arguably the biggest challenge to enterprise AI adoption. Organizations must foster environments that encourage experimentation, continuous learning, and iteration. Companies that penalize failure are likely to struggle in keeping pace with those that embrace experimentation and rapid deployment. India, however, is uniquely positioned to overcome these challenges due to its significant engineering talent, vibrant startup ecosystem, robust digital infrastructure, and entrepreneurial energy.