Demystifying Generative AI for Global Capability Centers (GCCs)

Global Capability Centers (GCCs) are nerve centers for many organizations, handling critical tasks and driving innovation. In this interview, Sameer Dhanrajani, CEO of AIQRATE and 3AI, shares his insights into the creation of GCC SPHERE, its unique value proposition, and how it leverages Generative AI to drive transformation and operational efficiency in GCCs. He also delves into the ethical considerations, governance structures, and data strategies necessary for effectively managing AI applications within GCCs. With over 400 GCCs in its network, 3AI is poised to become a key player in helping organizations navigate the complex landscape of AI and digital innovation.

AI, Data, and Innovation in GCCs

Could you provide an overview of the GCC SPHERE initiative? What prompted the creation of this integrated marketplace for GCCs?

3AI GCC Sphere is an integrated marketplace & hub created exclusively for the Global Capabilities Centers(GCCs) segment to augment ecosystem outreach and attain premier thought leadership.

3AI GCC Sphere aims to work as an Integrated Marketplace for (GCCs) to cater to their consulting, services, solutions, talent, L&D, academia, workplace & allied requirements. 

With deep association amongst 412+ GCCs through MDs, Country Heads, Data, Analytics, AI & Technology Heads; 3AI has deep inroads within GCCs and 3AI GCC SPHERE, A first-of-its kind initiative by 3AI aims to redefine the GCC landscape with one stop shop fulfilment of requirements and being an integrated marketplace that will spur innovation and transformation through curated and nuanced solutions services, and offerings aggregated by SPHERE partners. 

In addition, GCC SPHERE will showcase itself as a one-stop marketplace with an array of select yet proven partners from the 3AI ecosystem for GCCs. 

How does GCC SPHERE cater to the specific consulting, services, solutions, talent, and workplace requirements of Global Capability Centres? What sets it apart from other platforms?

3AI will onboard select & proven partners across consulting, services, solutions, talent, L&D, academia, workplace & allied areas and will suggest and recommend GCCs the credible partners to build and scale on their respective GCC journey.

With 1100+ by-invite, seasoned Data, AI & Analytics leaders from 975+ organisations, 3AI is well poised to leverage the wider ecosystem amongst Indian enterprises, global enterprises, cloud, technology , BPM & consulting players, pure play analytics providers, startups , academia to bring the best of partners for the GCCs.

How do you see Generative AI opening new pathways for innovation within Global Capability Centres? Could you share specific examples where AI has led to significant breakthroughs?

In today’s volatile & fungible scenario, GCCs are becoming nerve centres for the parent organizations by driving & delivering core innovative and transformative work spheres of the parent enterprises. 

GCCs are morphing themselves into hubs of Gen AI, AI and new age technologies and are accelerating business strategy implementation and accentuating business performance for the enterprises.

AI CoE, AI capability hubs covering end to end AI innovation & transformation across enterprise business value chain are being driven by GCCs with top end Gen AI use cases, functional intelligence platforms, nuanced LLMs and Gen AI application areas driven by GCCs . 

Further, few GCCs are also performing AI projects that are part of business strategy for the enterprises and GCCs are building new AI capabilities and solutions for the parent organisations. 

How is Generative AI reshaping the day-to-day operations of GCCs? What operational efficiencies are being realized through the adoption of this technology?

Gen AI is enabled within GCCs across business functions through defined and specific uses cases – HR, FP& A, supply chain, CX, Marketing whilst others are creating new areas of business enhancement and performance by leveraging Gen AI and that is with the intent to optimise and bring in operational and cost efficiencies that impacts the overall business metrics. GCCs are closely working with parent enterprises stakeholders to look at reimagining the business functions and businesses with Gen AI.

There are wide business scenarios wherein Gen AI is getting adopted ranging from sales enablement, marketing promotions, digital campaigns , audit reconciliation, logistics & delivery, talent hiring etc. 

How are GCCs addressing the ethical implications of deploying Generative AI? What frameworks are in place to ensure responsible AI use?

GCCs have put in guardrails and adequate compliance mechanisms that is conjunction with the parent organisation on the data strategy side that ensures the right data sets comes in the Gen AI systems along with building robust data architecture & engineering capabilities for the foundational intelligence. Further.

Customized large language models are being developed with nuanced variables and assumptions. 

GCCs are working in unison with parent organisations on the local data privacy and compliance policies to mitigate hallucinations or regulatory non-compliances. 

What governance structures are GCCs adopting to manage the risks and challenges associated with Generative AI? How are these models evolving?

GCCs are building Gen AI applications in complete alignment with global risk mitigation and governance structures basis the industry regulations; however, in few situations, Gen AI leverages Open AI tools and platforms and accordingly, GCCs need to configure adequate risk mitigation approaches to avoid non-compliance or data breach. 

The Models have to be properly configured to manage right assumptions, variables to avoid possible hallucinations . 

How are GCCs balancing global AI strategies with local market needs and regulations? What challenges arise in aligning global AI capabilities with regional requirements?

Data & AI strategies of the parent organizations and GCCs are completely aligned and the execution approach is duly managed in conjunction with local market scenarios and regulations. 

The gyrations, seasonality and nuanced data approaches of the local or regional markets and regulations need to be baked in before the Gen AI systems and architecture are configured.

Data mesh, data engineering, AI applications and functionalities have to be in complete alignment to ensure global AI capabilities are executed in full entirety. 

How are GCCs managing the vast amounts of data required for training Generative AI models? What data strategies are proving most effective?

GCCs are leveraging the parent organizations structured data strategy and data harnessing capabilities to build robust data sets to train the Gen AI models and algorithms.

Further, the unstructured, digital side of data is being calibrated to build clean data engineering layers and architecture. Data strategies ranging from right data aggregation techniques, comprehensive data massaging aspects, robust data mediation scenarios to exhaustive data engineering architecture are being deployed at scale by GCCs. 

How are GCCs fostering collaboration between AI systems and human decision-makers? What are the best practices for balancing AI insights with human judgment? 

With democratisation of intelligence at scale; AI –enabled or AI-first enterprise is becoming a norm. Enterprises are deploying cognition at scale with rule based engines and creating fine balance between machine- human for seamless interfaces.

AI led intelligence, insights are becoming mainstream along with real time recommendation engines creating decision making processes smoother for enterprises; however organisations need to avoid human biases, vested interests, misinterpreted data or deploy unethical systems that can cloud machines ability to generate sound judgments. 

This can be avoided with putting in ethical and regulated data and AI practices and frameworks in place.