Finding the Right Balance for Efficient and Scalable GenAI Deployment
Article
As generative AI (GenAI) usage accelerates, many organisations grapple with the challenge of structuring AI-related functions. Recent McKinsey data reveals a trend toward centralised governance for risk management and compliance, coupled with more distributed or “hybrid” models for AI talent and solution deployment.
1. Why Create AI Centres of Excellence (CoEs)?
Standardised Best Practices: CoEs house critical knowledge, frameworks, and compliance protocols under one umbrella, ensuring consistency across business units.
Rapid Scalability: When emerging technologies like GenAI demand quick adoption, a central hub can streamline decision-making and resource allocation.
Resource Optimisation: CoEs consolidate high-level AI expertise—data scientists, AI ethicists, and governance professionals—leading to more efficient skill-sharing and mentorship.
2. The Hybrid Model Explained
Risk and Compliance: Typically handled by a fully centralised hub to maintain uniform governance and legal standards.
Tech Talent and Adoption: Frequently organised via a partially centralised model, empowering local business units to customise AI solutions according to functional needs while still relying on a central team for overarching guidelines.
Collaboration and Innovation: Hybrid models encourage cross-functional synergy, allowing business units to share insights and best practices without fragmenting the organisation’s core AI strategy.
3. Key Considerations for Implementation
Stakeholder Alignment: Clear communication channels between CoEs and business units ensure everyone operates under unified objectives.
Change Management: Structural shifts toward a CoE model may encounter resistance. Ongoing training and transparent transition plans are vital for smooth adoption.
Continuous Evolution: As AI technologies mature, CoEs must remain flexible—adapting frameworks, updating best practices, and periodically revisiting governance models.
Key Takeaway:
Finding the optimal blend of centralised and distributed approaches can supercharge AI adoption. CoEs offer standardised risk management and shared expertise, while hybrid models infuse local agility and innovation. Ultimately, the best structure depends on a company’s size, culture, and long-term vision for GenAI.
Author’s Bio
“ Authored by Vineet Baveja, Founder of Conceptualise, a leader in digital marketing and transformative strategies. With two decades of guiding businesses through complex digital landscapes, Vineet offers practical insights for aligning AI adoption with organisational culture and goals.”