Global Capability Centers Lead the Way in AI Innovation: Highlights from 2024 GCC Summit

I had the opportunity to attend and interact with GCC leaders at the recent MachineCon GCC summit in Bengaluru this June, organized by Analytics India Magazine (AIM). The event brought together over 250 leaders from Global Capability Centers (GCCs), discussing the real-life applications, latest trends, future directions in AI and the role of GCCs in shaping these trends. This blog summarizes the various AI use cases that were in focus across different industries, also providing a glimpse into what the future holds for AI at Global Capability Centers.

The State of AI Adoption: A Global Perspective

According to the 2024 Gartner CIO and Tech Executive Survey, 34% of respondents have already adopted AI, and another 22% plan to do so this year. For generative AI, 9% have implemented it, while 34% plan to in 2024. Additionally, 73% of respondents will increase AI funding this year. Reflecting this trend, nearly every client and prospect conversation we have now involves an AI component.

Industries with the highest AI adoption rates include life sciences, sophisticated manufacturing, power management, and specialized financial services, including insurance and healthcare payers. These sectors boast adoption rates exceeding 40%, with substantial proportions of CIOs also planning further AI investments in the coming year. It is clear that AI is more than just a buzzword—it’s a crucial part of the modern enterprise landscape today.

When it comes to AI adoption challenges, among the AI projects that reach production, the primary obstacle, as reported by 49% of a Gartner survey participants, is the difficulty in estimating and demonstrating the value of AI projects. This issue surpasses other barriers such as talent shortages, technical difficulties, data-related problems, and a lack of business alignment and trust in AI.

Real-World AI Use Cases by Industry

At the summit, GCC leaders discussed a range of AI use cases they have successfully implemented and adopted, highlighting the innovative solutions and tangible benefits AI brings to various industries. Below are some of the most notable use cases by sector.

In the fintech sector, GCCs are revolutionizing customer interactions and operational efficiencies using AI. Some examples highlighted include:

• Interactive Investor Chatbots: AI-powered chatbots are transforming customer service by providing investors with personalized recommendations and real-time assistance. For example, these chatbots can help investors understand the vast landscape of available bonds, making informed decisions easier and more efficient.
• Private GPT Models for Wealth Managers: These models are enhancing transaction transparency and streamlining settlements. By providing wealth managers with actionable insights, they facilitate smoother operations. Critical considerations include robust data protection, prevention of data leaks, and enhanced cybersecurity measures to protect sensitive information.
• Generative AI for Market Research: Advanced AI stacks are being used to offer personalized summaries and suggestions to users based on their behavior and interests. This shift from a traditional(pull) search model to a push model wherein users receive timely, relevant information and recommendations proactively, transforming how financial market research is conducted.

While the banking and financial services industry may lead in AI maturity, healthcare GCCs are catching up rapidly. Key trends include:

• Transforming the 5 Ps of Healthcare: AI is driving preventive, predictive, personalized care, providing peace of mind to patients, and enhancing point-of-care services. For instance, AI-enabled healthcare systems can proactively manage patient well-being, similar to how a pizza delivery service uses customer data to recommend healthier options.
• Drug Discovery Automation: AI and machine learning are streamlining the drug discovery process, significantly reducing the time and costs associated with bringing new drugs to market. This automation accelerates research and development, leading to faster delivery of effective treatments.
• Personalized Pharma Rep Briefings: AI is being used to generate personalized briefings for pharmaceutical representatives. These briefings are tailored to the specific needs and interests of the healthcare providers they meet, ensuring more meaningful and productive interactions.

Retail is another sector where AI is making a significant impact. Key use cases supported by Retail GCCs include:

• Hyper-Personalized Product Descriptions: AI creates tailored product descriptions for e-commerce websites, enhancing customer value and reducing the time needed for manual copywriting. By leveraging data and behavioral profiles, AI generates millions of product descriptions on the fly, significantly boosting efficiency and personalization.
• Customer Insights and Personalization: AI integrates data from various channels to personalize customer interactions, optimize marketing efforts, and enhance supply chain operations through real-time tracking and demand forecasting. This integration leads to a more cohesive and personalized shopping experience.
• Adaptive Retail Experiences: The future of retail lies in adaptive retail, which combines physical and virtual shopping experiences. AI enables features like scan-and-go, virtual try-ons, and real-time remote store monitoring, creating a seamless and efficient customer journey. For example, AI-powered chatbots offer personalized customer service and product recommendations, enhancing the shopping experience and boosting satisfaction.

AI’s impact transcends specific industries, with GCCs supporting several cross-industry applications that are gaining traction:

• Conversational AI: AI-powered chatbots and topic search capabilities enable seamless product purchasing and customer interactions across various sectors. These chatbots can engage customers in real-time, providing personalized assistance and enhancing user experiences.
• Company-Specific LLMs: Many organizations are developing their own large language models (LLMs) for internal productivity, customer-facing applications, and content generation. These models support a wide range of functions, from training to legal risk management and contract management, improving efficiency and effectiveness.
• Digital Asset Management: Large organizations with extensive digital assets, such as product catalogs and images, are using Generative AI to automate management processes that previously required significant human effort. This automation ensures consistency and accuracy across multiple platforms.
• Security Threat Detection: AI models are being developed to detect security threats, including hallucinations, biases, and fairness issues in generated prompts. These models provide crucial observability to ensure appropriate and accurate AI outputs, safeguarding against potential risks.

GCCs and the Future of AI

Looking ahead, the future of AI is filled with groundbreaking developments that promise to reshape industries and redefine our interaction with technology. Global Capability Centers (GCCs) will play a pivotal role in this transformation. While numerous use cases will emerge, following three overarching predictions resonated with me:

1. Agentic AI: GCCs will drive the development and adoption of agentic AI, where systems autonomously perform tasks, make decisions, and act independently based on programming and learning. For example, an autonomous delivery drone with agentic AI can navigate environments, avoid obstacles, and optimize routes without human input. As GCCs integrate multiple agents for collaborative intelligence, they will enhance operational efficiency and innovation across sectors.
2. Affordable LLM/SLM Development: GCCs will accelerate the development of cost-effective large language models (LLMs) and small language models (SLMs), making advanced AI capabilities more accessible. By democratizing AI tools, organizations can make sophisticated technology available to all its staff & clients, without prohibitive costs, driving widespread innovation and competitiveness.
3. Ethical and Responsible AI: The emphasis on ethical and responsible AI is set to accelerate, gaining prominence in the coming years. Ethical AI will also play a significant role in sustainability efforts, addressing critical environmental challenges, and promoting a positive societal impact. Ensuring AI solutions contribute to the greater good will become increasingly central to AI development, with a strong focus on ethical guidelines and responsible use.

In Summary…

AI and Generative AI are swiftly transitioning from experimental to production phases, with enterprises across various industries finding innovative ways to leverage this technology. Global Capability Centers are at the forefront of AI experimentation and innovation, paving the way for an AI-enabled future across industries. They offer endless possibilities for enhancing business operations and customer experiences, leading the charge in transforming how businesses operate and interact with their customers. However, GCC leaders agree on the critical importance of implementing proper security measures, ethical guidelines, and observability to ensure responsible and safe AI adoption.

Reach out to learn how Infocepts can assist GCCs in leveraging Data & AI for modernization, innovation, and scalable growth.