We stand on the brink of a revolutionary age in artificial intelligence (AI), where machines are on the verge of mirroring human behaviours, opening the door to limitless possibilities. Thanks to Generative AI, a technological marvel that produces seemingly new and lifelike content – spanning text, images, music, audio, and videos – straight from its training data. The landscape is shifting profoundly; McKinsey's research signals a seismic impact, with Generative AI (Gen AI) poised to inject an astonishing $4.4 trillion annually into the global economy. Additionally, it can potentially automate up to 70% of business activities across diverse occupations by 2030. However, we witness the initial stages of Gen AI's development and utilisation.

In this dynamic environment charged with innovation, a critical question emerges: How can we not only keep up but thrive in the face of such transformative potential?
Establishing a dedicated Centre of Excellence (COE) for Generative AI is the answer. This is where the fusion of innovation and expertise chart the course for the future. As the technological landscape reshapes, the COE becomes the hub of cutting-edge advancements, propelling organisations towards unprecedented heights of success and adaptation in the age of Generative AI.

1. Strategic Innovation: Charting the course for transformation.
Beyond being a mere technical hub, a Gen AI COE is a strategic powerhouse. Gen AI has the potential to alter business models, create new products and services, revolutionise customer experiences, enhance employee engagement, and streamline operations for cost reduction while amplifying productivity and efficiency. By aligning its objectives with organisational strategies, the COE emerges as a catalyst for innovation. It forges a roadmap pinpointing key business areas where Gen AI can make the most substantial impact. The COE also delves into essential questions about corporate culture's influence on Gen AI adoption, proposes shifts in talent management approaches, and identifies priority business use cases—creating a dynamic strategy for Gen AI enablement over different time horizons.

2. Partnership Ecosystem: Collaboration as a cornerstone.
From navigating the thin line between hype and reality to spearheading the transformation of enterprises, a third of companies have embraced generative AI in at least one business function, as outlined by the McKinsey Global Survey. The rapid evolution of generative AI is nothing short of remarkable. Teaming up with startups, industry bodies, academia, and research institutes creates a space filled with shared knowledge, the latest tech trends, disruptions, and new technology methods. Recently, VOIS joined forces with NASSCOM, the apex body of India's $245 billion technology industry, to introduce the ground-breaking Generative AI Foundry program. This 12-month initiative is meticulously designed to nurture and guide startups in the dynamic realm of Generative AI.

3. Use Case Factory: Turning ideas into reality.
Using Case Factory within the Gen AI COE transforms abstract ideas into practical applications, prioritising those with maximum value, scalability, and minimal risks and complexities. Through incubation and refinement, the COE demonstrates the real-world impact of Generative AI and creates a valuable organisational asset. To effectively harness AI capabilities, businesses should identify business-driven use cases, balancing strategic value with achievability. It's crucial to have a monitored pipeline for production deployment, and determining the appropriate level of ambition involves undertaking smaller, impactful projects to gather management attention and create a roadmap with multiple use cases over time. The AI centre is a guide to help companies 'think big but start small' with AI implementation.
At VOIS, we have undertaken diverse experiments utilising Generative AI in various domains, including Knowledge Management, Operational Transformation encompassing the Incident Management lifecycle, real-time language translation, an employee conversation tool integrated with attrition prediction, and a Coaching platform.

4. Mastering the Data Maze: Building a solid foundation.
Data fuels AI and the Gen AI COE acknowledges the critical role of a robust data architecture covering various data types—structured, unstructured, and external. It sets up guidelines for gathering, storing, and processing data, ensuring the organisation has a robust foundation for supporting the complex needs of Generative AI applications. Yet, handling and organising data remain significant challenges for many organisations, preventing successful generative AI use. Organisations must grasp the optimal utilisation of generative AI technologies within their infrastructure while safeguarding their data, making decisions on on-premises versus cloud options, and choosing between self-maintained open-source solutions and licensed alternatives.

5. AI That Delivers: Charting a course for measurable outcomes.
At VOIS, we have systematically separated metrics across key domains to facilitate a comprehensive evaluation. Embarking on the generative AI era holds immense promise and potential for transformative advancements. Simultaneously, executives aim to ensure optimal returns from their AI investments and realise the promised outcomes. A comprehensive understanding of generative AI is crucial for fully grasping the business value of a model. When assessing the success of an AI project, carefully selecting pertinent metrics becomes critical for a meaningful impact assessment.

• Business Impact: Measuring improvements in customer and employee experiences, cost reduction, increased productivity, and revenue growth.
• Product/Solution Adoption: Assessing metrics like user adoption percentage, daily active users, feature-wise adoption percentage, and average time spent per user.
• Technology: Evaluating accuracy range, latency, availability, response time, etc.
• User Feedback: Utilising metrics such as User Feedback Score and Net Promoter Score to gauge user satisfaction and overall feedback.

6. Spread Success Stories: Inspiring the Organisation.Gen AI COE serves as a beacon by showcasing success stories within the organisation. By disseminating achievements and lessons learned, the COE inspires teams to explore new possibilities and encourages a culture of continuous improvement.

7. Ethics Committees: Navigating ethical challenges.Generative AI brings forth many ethical concerns, ranging from the peril of data misuse, the creation of deepfakes, and copyright infringement to the circulation of toxic content, potential biases, workforce displacement, and a lack of transparency. In addition, businesses harnessing Generative AI must prioritise protecting personal information for customers and employees, aligning with region-specific legal regulations. Proactively addressing these challenges, the Gen AI COE establishes ethics committees that are pivotal in navigating the complexities associated with ethical considerations. The COE adopts ethical frameworks to guide development and deployment processes, aspiring to create transparent, fair algorithms by individual and societal norms, thereby ensuring the responsible use of technology.

8. Future-Ready Workforce: Nurturing AI skills.The Gen AI COE extends beyond technology; it's a commitment to people. How do you prepare the entire organisation for the skills of the future? How do you equip them with the latest tech? Acknowledging the significance of AI skills, the COE dedicates resources to training programs, empowering the workforce with the knowledge and capabilities essential to navigate the future of work in the era of Generative AI. Another facet involves the selection of individuals for your team. A pivotal aspect of successfully establishing an AI centre lies in recruiting, attracting, or cultivating talent—be it cutting-edge AI engineers, data scientists (statisticians), or MBA-level analysts.