UK firms prefer pre-built AI agents over custom code

SOFIAH NICHOLE SALIVIO

News Editor

Jitterbit has published research showing a divide between UK and US technology leaders over whether to buy or build AI agents, highlighting a split in enterprise preferences for agentic automation.

Its data shows that 51% of UK organisations prefer pre-built agents for building and deploying AI agent automations, while 48% rely on custom-made systems. In the US, the pattern is reversed: 55% of respondents favour custom-built code developed entirely in-house, while 45% lean toward pre-built agents.

The figures come from Jitterbit’s 2026 AI Automation Benchmark Report, which examines how IT decision-makers are approaching AI and automation. It suggests UK companies place greater value on speed and efficiency than on bespoke development as they expand their use of AI agents.

Among UK respondents, 43% preferred agents embedded in pre-built software-as-a-service applications. By contrast, 28% preferred building their own low-code or no-code integration platforms, while 20% favoured in-house custom-coded agents built through tools such as Lovable or similar services. Only 8% chose off-the-shelf agents as their primary source.

Cost pressure

Jitterbit linked the strategic divide to the changing economics of AI deployment, arguing that rising token costs and heavier use of large language models are making bespoke development less attractive, particularly for companies weighing the ongoing cost of maintaining internal systems.

This reflects a wider market concern over the total cost of AI projects. Many companies have invested heavily in internal engineering teams and AI experimentation, but spending on inference, integration and model usage has become a more visible budget issue as projects move into broader business use.

The report also found that 81% of organisations plan to increase funding for AI and automation over the next 12 months, suggesting demand remains strong even as businesses become more selective about deployment and expected returns.

Build or buy

The contrast between the UK and the US also points to different corporate cultures around software development. US engineering teams appear more willing to keep AI agent development in-house, while British organisations show greater readiness to adopt pre-built options from software vendors.

The distinction matters because AI agents are moving from pilot projects into mainstream operational tools. Companies are using them for process automation, application integration and task orchestration, so decisions on whether to build internally or buy ready-made systems can affect budgets, deployment times and the level of technical oversight required.

Pre-built systems can offer faster implementation and more predictable supplier support, while custom builds can provide greater control over workflows and internal data handling. The findings suggest this trade-off is becoming sharper as AI consumption costs rise and boards demand clearer evidence of value.

For UK businesses, the research indicates that caution over custom development is not simply technical conservatism. It also reflects a pragmatic response to the pressure of deploying AI tools at scale without taking on open-ended costs tied to internal development and token use.

Bill Conner, president and chief executive officer of Jitterbit, said the market is moving into a new phase as AI projects become more integrated into core operations.

“We are moving past the era of siloed AI experimentation and entering the era of pure orchestration,” Conner said.

He said economic pressure is reshaping how companies assess custom systems against pre-built alternatives.

“The market is waking up to the true total cost of ownership of custom AI. Between developer bottlenecks and soaring token costs, building everything from scratch is a luxury few can sustain. The UK’s slight preference for pre-built applications may have previously been considered cautious, but it’s proving to be highly strategic as economic pressures force a shift from development to intelligent integration,” Conner said.