Agentic AI: Build, buy or borrow

Agentic artificial intelligence (AI) is rapidly redefining how organisations operate, innovate and compete. As businesses across every sector race to capture value from generative AI, many now face a pivotal decision: should they build, buy or borrow AI agents?

Determining the right path is more than a technical consideration. It is a strategic choice that shapes competitiveness, speed to value, governance and long term differentiation.

New KPMG global research shows that enterprises are moving quickly. More than 40 percent of companies have already integrated AI agents into their workflows, up from just 11 percent in early 2025. With such momentum comes complexity as leaders work to select the right approach for their organisation while safeguarding trust, security and compliance.

This page outlines the build buy borrow framework for agentic AI and explores what Irish organisations should consider as they shape their own strategies.

1. Building AI agents in house:
Maximum control and differentiation

Building proprietary AI agents gives organisations the greatest degree of customisation, security and competitive differentiation. When an agent is developed internally, even if based on widely used frameworks such as LangGraph or the Microsoft Agent Framework, the organisation retains ownership of the architecture, workflows, embedded expertise and long-term roadmap.

This is especially appealing where models interact with high sensitivity data or require extensive domain tuning. For sectors such as healthcare, life sciences, financial services and technology, industries where Ireland has substantial activity, an in-house build can align AI capabilities closely with regulatory obligations, risk management protocols and proprietary workflows.

However, the build path requires significant internal capacity. It depends on strong engineering talent, robust governance, the availability of subject matter experts, a dedicated product management approach and the infrastructure needed to support continuous evaluation and improvement.

For organisations with these capabilities already in place, building agents can deliver long term strategic value. For many others, the development timeline and resource intensity make pure in house builds more challenging.

3. Borrowing through partnership:
Sharing the load and accelerating innovation

The third pathway, borrowing, involves developing AI agents jointly with external partners such as technology providers, cloud hyperscalers or consulting organisations like KPMG. This approach blends an organisation’s proprietary data and domain expertise with a partner’s engineering capability, architecture frameworks and accelerators.

Borrowing is particularly effective for organisations that:

• need to move quickly but lack internal engineering capacity
• want to minimise capital expenditure
• require tailored solutions but cannot support a full internal build
• would benefit from knowledge transfer and capability uplift
• need support integrating AI within complex or legacy environments

Partnership models reduce development risk, maintain strategic flexibility and allow organisations to pilot and refine solutions before scaling.

Why this matters for Irish organisations

Ireland is home to one of the world’s most advanced digital economies, with major multinationals and domestic leaders driving innovation across finance, healthcare, retail, manufacturing and government. As AI adoption accelerates, organisations increasingly need strategies that deliver trust, efficiency and competitive advantage without unnecessary complexity or risk.

Agentic AI provides an opportunity not only to automate but to reimagine how work is done. The organisations that succeed will be those that treat the build buy borrow decision as a strategic choice rooted in governance, capability and a clear understanding of what drives long term value.

KPMG Ireland supports clients across all three pathways, from developing bespoke agentic solutions to deploying proven platforms and co creating with global technology partners. The focus is on transforming AI from experimentation into sustained enterprise value.