AI Training Leads Planned Tech Investments, Liferay Survey Finds

What happened

A new survey from digital experience platform provider Liferay finds that AI training is the single most commonly planned technology investment among organisations over the next twelve months. The research points to a broader shift already under way: agentic AI is moving out of pilot projects and experimentation and into structured, business-wide rollouts.

According to the findings, reported by No Jitter, organisations are prioritising building internal capability — training people to work with AI tools and agents — ahead of many other planned technology spends. The emphasis on training suggests that leaders see workforce readiness, rather than raw technology procurement, as the bigger constraint on getting value from agentic AI.

Why it matters

The finding signals a maturing phase for agentic AI adoption. Early enterprise AI initiatives were largely about testing what the technology could do; this survey suggests attention is now turning to how organisations operationalise it — embedding AI agents into everyday workflows, governance and decision-making rather than treating them as isolated experiments.

For leaders in digital transformation, this reframes the investment conversation. Buying or building AI capability is only half the task; the other half is equipping employees to direct, supervise and collaborate with AI agents effectively. That has implications for L&D budgets, change-management programmes and how quickly organisations can convert AI pilots into measurable business outcomes.

The Renascence take

The headline finding is unsurprising on its face — of course training matters — but it is a useful signal of where the agentic AI conversation is heading next.

Most coverage of agentic AI still fixates on the technology itself: which model, which agent framework, which vendor. This survey is a reminder that the binding constraint on value is almost always human, not technical. Organisations that treat AI training as a compliance checkbox — a one-off onboarding module — will lag behind those that treat it as an ongoing behavioural design problem: how employees build trust in an agent, when they override it, and how service and decision quality change as a result. The operators who get ahead here won't be the ones with the most sophisticated agents; they'll be the ones who invested earliest in the human systems around them.