As enterprises accelerate their adoption of hybrid cloud and AI, the focus is shifting from isolated deployments to ecosystem-driven innovation. Scaling AI from pilot projects to enterprise-wide impact now demands deep collaboration across technology providers, system integrators, startups, and clients – anchored by open, trusted platforms. In an interaction, Yukti Punjabi, Director – Ecosystem, IBM India & South Asia, shares why collaboration has become foundational to designing and scaling hybrid cloud and AI initiatives. She discusses how open platforms enable trust and interoperability, how partnerships are localising AI innovation for India’s diverse market needs, and how IBM’s enhanced Partner Plus program is strengthening co-innovation across industries.
As enterprises deepen their digital transformation journeys, hybrid cloud and AI are no longer viewed as standalone technology deployments. Instead, they are reshaping how organisations operate, innovate, and create value. According to Yukti Punjabi, Director – Ecosystem, IBM India & South Asia, this scale of transformation cannot happen in silos.
“Hybrid cloud and AI are inherently complex, multi-layered journeys. Enterprises today are not just adopting a platform or a tool, they are re-architecting how they operate, innovate, and create value,” says Punjabi.
This complexity is precisely why collaboration has become fundamental. No single organisation can bring together all the capabilities required to make hybrid cloud and AI successful at scale, ranging from infrastructure and data strategy to security, AI models, and change management. Ecosystem partners play a critical role in stitching these elements together and helping enterprises design architectures that are open, resilient, and future-ready.
At IBM, Punjabi notes, the strongest outcomes emerge when partners and clients co-create solutions from the very beginning. “This shared approach ensures that AI and hybrid cloud strategies are not only technically sound but also aligned to real business priorities and long-term outcomes,” she adds.
Moving AI from pilots to enterprise impact
While many organisations have experimented with AI, scaling those pilots into enterprise-wide deployments remains a challenge. Punjabi believes this gap is less about technology and more about execution.
“Moving AI from pilots to production is less a technology challenge and more an execution challenge,” states Punjabi.
Scaling AI requires integration with existing systems, robust governance frameworks, domain-specific workflows, and the confidence to deploy responsibly. This is where collaboration across the ecosystem becomes critical.
Technology providers bring platforms and models, system integrators enable enterprise-scale implementation, startups inject agility and innovation, and clients contribute deep domain expertise.
“When these capabilities come together, AI solutions are designed with scale, security, and operational reality in mind from the start,” asserts Punjabi. As a result, AI initiatives move beyond experimentation to deliver measurable business value.
Openness as the cornerstone of trusted AI
Open platforms are increasingly seen as the foundation for scalable and trustworthy AI innovation. Punjabi emphasises that openness is not just a technical choice, but a strategic one.
“Openness is essential to building AI that enterprises can trust and scale,” she says.
Open platforms enable interoperability across diverse environments, help organisations avoid vendor lock-in, and support stronger governance and transparency. In hybrid IT environments, this flexibility allows enterprises to choose the technologies that best fit their needs while maintaining consistency across deployments.
From an ecosystem perspective, openness accelerates co-innovation. “It allows partners to build differentiated solutions on a shared foundation, while ensuring interoperability and consistency across deployments,” Punjabi notes. This shared foundation is critical for scaling AI responsibly and securely.
Localising AI innovation for India’s diverse market
India’s diversity across industries, languages, infrastructure maturity, and regulatory environments demands localised innovation. Ecosystem partnerships are central to addressing this complexity.
IBM’s collaborations in India highlight how global technology can be adapted to local realities. One example is IBM’s partnership with Bharti Airtel, which brings together the telco-grade reliability, security, and data residency of Airtel Cloud with IBM’s AI-ready infrastructure and software. The collaboration enables enterprises in regulated industries to scale AI workloads efficiently while ensuring interoperability across hybrid environments.
IBM has also expanded its partnership with Amazon Web Services (AWS) by making the watsonx portfolio available natively through the AWS Catalog in the India region. This move brings enterprise-grade AI capabilities closer to Indian businesses while ensuring compliance with local data regulations.
In the BFSI sector, IBM worked with NeuroGaint Systems to enhance NeuroLC, an AI platform designed to transform Letter of Credit processing, using IBM watsonx.ai and Cloud Pak for Business Automation. The solution helps banks and financial institutions streamline complex trade finance processes.
Another collaboration with C-Metric led to the development of Aivio, an AI-powered assistant that enables employees to interact with structured and unstructured enterprise data through a single secure interface. The results were tangible – an 80% reduction in time spent resolving queries and locating information, and 60% automation of first-level internal support tasks.
“These collaborations ensure that AI deployed in India is not only globally advanced, but locally relevant, designed to deliver measurable outcomes for businesses,” points out Punjabi.
Strengthening co-innovation through IBM Partner Plus program
IBM’s belief in ecosystem-led growth is also reflected in the latest enhancements to its Partner Plus program. In 2026, the focus is firmly on scaling growth, expanding reach, and strengthening alignment across the ecosystem.
“The latest enhancements to IBM Partner Plus are designed to make it easier for partners to build, sell, and scale AI and hybrid cloud solutions,” says Punjabi.
The updates include simplified incentives, expanded access to cloud credits, and deeper hands-on support from IBM experts. The program places a stronger emphasis on co-innovation, helping partners develop differentiated solutions, accelerate time to market, and reach clients through their preferred buying channels, including cloud marketplaces. AI-driven tools embedded within the partner experience further enable smarter selling and faster execution.
Given India’s rapid digital expansion, Punjabi underscores that the partner ecosystem is core to IBM’s growth strategy. IBM is working closely with business partners, ISVs, system integrators, and startups to expand its reach across thousands of new clients.
“Ultimately, these updates reinforce our belief that progress happens together,” she adds.
Shaping the future of hybrid cloud and AI across industries
Across India and South Asia, ecosystem partnerships are already shaping the future of hybrid cloud and AI adoption across sectors. In BFSI, partners are helping institutions modernise core systems while embedding AI for fraud detection and risk management. In manufacturing, collaborations are driving smarter operations, predictive maintenance, and more resilient supply chains. In telecom, partners help manage scale, security, and regulatory requirements while enabling AI-driven service delivery.
“What’s common across these sectors is the need for trusted collaboration and partners who understand both the technology and the operating environment,” Punjabi observes.
As hybrid cloud and AI move from experimentation to becoming foundational to enterprise strategy, ecosystem-led collaboration is emerging as the decisive differentiator.
“These partnerships are shaping a future where hybrid cloud and AI are not experimental, but foundational to growth, resilience, and competitiveness,” she concludes.