What is AI Center of Gravity?
An AI Center of Gravity is the organisational unit, team, or function that serves as the primary driving force for AI adoption and coordination across a company. It concentrates AI expertise, sets standards, manages shared resources, and ensures that AI initiatives align with business strategy rather than emerging in uncoordinated silos.
What is an AI Center of Gravity?
An AI Center of Gravity is the organisational anchor point for all things AI within your company. It is the team, function, or structural unit that pulls together the people, knowledge, tools, and processes needed to make AI work across the entire business. Without this gravitational centre, AI efforts tend to scatter across departments in uncoordinated, duplicative, and sometimes contradictory directions.
The concept borrows from military strategy, where "center of gravity" refers to the source of power that provides moral or physical strength, freedom of action, or will to act. Applied to AI, it identifies the organisational element whose strength and focus determine whether AI succeeds company-wide or remains a collection of disconnected experiments.
Why Organisations Need an AI Center of Gravity
Preventing AI Fragmentation
Without a centre of gravity, AI adoption typically follows a pattern: individual teams hear about AI, experiment on their own, select different tools, build incompatible solutions, and create data silos. The marketing team uses one AI vendor, finance uses another, and operations builds something custom. The result is duplicated costs, incompatible systems, and no way to leverage learnings or data across the organisation.
Ensuring Strategic Alignment
An AI Center of Gravity connects AI initiatives to business strategy. Rather than deploying AI wherever someone has enthusiasm, a centre of gravity ensures that AI investments are prioritised based on strategic importance, potential return, and organisational readiness. This prevents the common pattern of investing heavily in technically impressive but strategically marginal AI projects.
Building Reusable Capability
When AI efforts are centralised through a centre of gravity, the organisation builds reusable assets: shared data pipelines, common model frameworks, proven deployment processes, and institutional knowledge. Each new AI project benefits from what was learned and built in previous projects, creating an accelerating capability that fragmented efforts can never achieve.
Managing Risk and Governance
AI governance becomes exponentially more difficult when AI initiatives are scattered across the organisation. An AI Center of Gravity can establish and enforce consistent governance standards, ensuring that all AI deployments meet regulatory requirements, ethical standards, and security policies.
Models for an AI Center of Gravity
The Dedicated AI Team
A standalone team reporting directly to the CEO or CTO, focused entirely on AI strategy, development, and deployment. This model provides the clearest mandate and strongest focus but requires sufficient budget and talent to staff a dedicated team.
Best for: Organisations making AI a core strategic pillar with significant investment
The Augmented IT or Data Team
AI responsibilities are added to an existing IT, data, or digital transformation team. This model leverages existing technical infrastructure and relationships but risks AI being deprioritised when competing with other IT demands.
Best for: SMBs that cannot justify a fully dedicated AI team but have a capable technical function
The Cross-Functional Council
A governing body composed of representatives from multiple departments that collectively directs AI strategy and coordinates initiatives. This model ensures broad business input but can be slow to make decisions and may lack dedicated execution capability.
Best for: Organisations wanting broad stakeholder input who pair the council with a small execution team
The Executive-Led Function
AI is placed under a specific C-suite leader, such as a Chief AI Officer, Chief Data Officer, or Chief Digital Officer, who has budget authority and direct reports. This model provides clear accountability and executive-level visibility.
Best for: Mid-to-large organisations with mature AI ambitions
Building Your AI Center of Gravity
Step 1: Assess Your Starting Point
Before choosing a model, understand where you are:
- Current AI activities: What AI initiatives already exist? Who is driving them? Where are the gaps and overlaps?
- Talent inventory: What AI skills exist within the organisation? Where are the expertise gaps?
- Technology landscape: What AI tools and platforms are already in use? How compatible are they?
- Strategic priorities: Which business challenges would benefit most from coordinated AI efforts?
Step 2: Define the Mandate
Clearly articulate what the AI Center of Gravity is responsible for:
- Strategy: Setting AI priorities based on business objectives
- Standards: Defining technical standards, governance policies, and quality requirements
- Enablement: Providing tools, platforms, training, and support that help business teams use AI effectively
- Execution: Directly building and deploying AI solutions for complex or cross-functional use cases
- Coordination: Ensuring different teams share learnings, reuse components, and avoid duplication
Step 3: Staff Appropriately
The right staffing depends on your model, but most centres of gravity need:
- AI/ML technical expertise: People who can build, deploy, and maintain AI models
- Business translation: People who can bridge technical AI capabilities and business needs
- Programme management: People who can coordinate multiple AI initiatives and manage stakeholder expectations
- Data expertise: People who understand data governance, quality, and architecture
For an SMB, this might be three to five people combining these skills. For larger organisations, it could be a team of 10 to 20 or more.
Step 4: Establish Operating Rhythms
Create regular cadences for:
- Use case review: Evaluating and prioritising new AI opportunities from across the business
- Portfolio management: Tracking progress and impact across all active AI initiatives
- Technology review: Evaluating new AI tools and platforms as the market evolves
- Governance review: Ensuring all AI deployments remain compliant and well-managed
- Knowledge sharing: Disseminating learnings, successes, and cautionary tales across the organisation
AI Center of Gravity in Southeast Asian Organisations
Regional Coordination
For companies operating across ASEAN, the AI Center of Gravity must balance centralised standards with local flexibility:
- Set common governance frameworks, security standards, and strategic priorities centrally
- Allow local adaptation of AI solutions for market-specific languages, regulations, and customer expectations
- Establish regional hubs in major markets like Singapore or Malaysia for talent-intensive AI development while enabling local deployment
Talent Hubs
Singapore and, increasingly, Malaysia and Thailand serve as natural talent hubs for AI centres of gravity in Southeast Asia due to stronger AI education ecosystems and larger talent pools. However, the centre of gravity should ensure that knowledge flows outward to teams in all markets through training, documentation, and regular collaboration.
Cost-Effective Structures
Not every ASEAN company needs a large, expensive AI centre. Many SMBs effectively operate with a lean centre of gravity comprising a senior AI leader, two to three technical staff, and a network of business-side AI champions. The key is having clear mandate and accountability, not necessarily a large team.
An AI Center of Gravity is the structural decision that determines whether your company approaches AI strategically or chaotically. For CEOs, establishing this centre is among the most consequential organisational decisions in the AI era. Without it, AI investments are scattered, duplicated, and disconnected from strategy. With it, every AI dollar is invested purposefully and every AI initiative builds on what came before.
The cost of not having a centre of gravity is often invisible until it becomes painful: different departments buy overlapping AI tools, incompatible systems prevent data sharing, no one has a complete picture of AI spending or risk, and promising pilots cannot scale because there is no shared infrastructure. For mid-sized companies in Southeast Asia, where budgets are tighter and talent is scarce, this waste is particularly damaging.
For CTOs, the AI Center of Gravity is where technical AI strategy meets operational reality. It is the mechanism for ensuring that technical standards are consistent, that infrastructure investments are shared and leveraged, and that the organisation builds lasting AI capability rather than accumulating disconnected projects. Establishing this centre early, even in a lean form, creates the foundation for everything else in your AI journey.
- Choose an organisational model for your AI Center of Gravity that matches your company size, AI maturity, and available talent. A lean model for SMBs can be just as effective as a large dedicated team.
- Define a clear mandate that covers strategy, standards, enablement, and coordination. Ambiguity about the centre's role leads to turf conflicts and gaps.
- Ensure the AI Center of Gravity has sufficient executive sponsorship and budget authority to set standards and coordinate across departments.
- Staff the centre with a mix of technical AI expertise, business translation skills, and programme management capability.
- Establish regular operating cadences for use case prioritisation, portfolio management, technology evaluation, and knowledge sharing.
- For multi-country ASEAN operations, balance centralised standards with local flexibility to accommodate different regulations, languages, and market needs.
- Start lean and grow the centre of gravity as AI maturity increases. Over-building the team before there are sufficient AI initiatives to manage wastes resources.
Frequently Asked Questions
Where should an AI Center of Gravity report in the organisation?
For maximum effectiveness, the AI Center of Gravity should report to whoever owns the company's strategic transformation agenda, typically the CEO, CTO, or a Chief Digital Officer. Placing it under a single department like IT or marketing limits its ability to drive cross-functional AI adoption. For SMBs, reporting directly to the CEO ensures AI gets the strategic attention and cross-departmental authority it needs. The key principle is that the centre must have the mandate and visibility to work across all functions.
How is an AI Center of Gravity different from a Center of Excellence?
The terms are sometimes used interchangeably, but there is a meaningful distinction. A Center of Excellence typically focuses on building and sharing best practices, training, and standards. An AI Center of Gravity goes further by actively driving AI strategy, making investment prioritisation decisions, and coordinating execution across the organisation. Think of a Center of Excellence as advisory and a Center of Gravity as both advisory and operational, with the authority and resources to make things happen, not just recommend them.
More Questions
Establish one as soon as you have more than two active AI initiatives or when AI spending exceeds a material threshold for your business. For most mid-sized companies, this point arrives when the second or third department begins exploring AI independently. Waiting until AI efforts are already fragmented makes centralisation harder because you must untangle existing investments and overcome departmental ownership of tools and processes. Starting early, even with a lean structure, is significantly easier than retrofitting coordination later.
Need help implementing AI Center of Gravity?
Pertama Partners helps businesses across Southeast Asia adopt AI strategically. Let's discuss how ai center of gravity fits into your AI roadmap.