What is the status of AI adoption in international organisations? Ahead on investment, behind on value

Internationally operating organisations are leading Europe on AI. They explore it more than domestic/local ones, invest in it more, scale it more. Which makes total sense because the needs are also more. And yet, when it comes to seeing real results, the gap between ambition and outcome is almost identical to that of their domestic peers.

That is the central finding of the SD Worx HR & Payroll Pulse 2026 and it is worth pausing on. 61.8% of internationally operating organisations say they are actively exploring AI's potential for the workplace, nearly 8 points above the European average of 54%. 58% are actively investing, against 50.5% overall. 51.2% have already scaled AI across different business units, compared to 42% on average.

On paper, the numbers look impressive. More than half (58%) are actively investing, and 51.2% have already scaled AI across different business units, well ahead of the 42% European average.

But scaling is not the same as succeeding. When the Pulse asks about real outcomes, only 48.2% of internationally operating organisations say they are actually seeing significant results from AI in HR. That is just 3 points behind the scaling rate: a gap that is almost identical to the European domestic average (42% scaling, 40.1% seeing results).

In other words: international organisations are doing more of everything and arriving at the same frustration as everyone else. More investment. Same problem. Operating across multiple countries does not change the equation.

The instinct to interpret higher adoption rates as progress is understandable. But the Pulse data consistently shows that adoption is no longer the bottleneck. Application is.

Many organisations are still using AI to automate isolated tasks rather than rethinking the workflows those tasks sit within. A payroll team that uses AI to flag anomalies is still processing payroll the same way it always has. A recruiting function that uses AI to screen CVs is still running the same hiring process. The technology is inserted, but the work is not redesigned. And without redesign, the efficiency gains are marginal and the strategic value never materialises.

For internationally operating organisations, this pattern is compounded by scale. When HR and payroll operations run across 10 or 15 countries, each with its own systems, processes and compliance requirements, the temptation is to deploy AI country by country, function by function, solving local problems locally. The result is a fragmented AI landscape that mirrors the fragmented operational landscape it was supposed to simplify.

There is a second gap we can take from the Pulse data, quieter than the adoption numbers but arguably more consequential: the gap between what organisations say they are investing in and what employees actually experience.

50.9% of internationally operating organisations say they are investing in reskilling and upskilling employees to prepare for an AI-driven future, well above the 43.8% European average. That is a significant commitment on paper. But when employees are asked the same question, only 30.1% say their organisation is actually helping them build the skills they need. Nearly 70% of the workforce in internationally operating organisations does not feel that support.

This matters because AI tools are only as effective as the people using them. An organisation that scales AI without scaling capability is building a system that runs faster than its people can steer. And when employees do not feel equipped, they are more likely to distrust AI outputs, work around them or resist adoption altogether quietly undermining the very investment the organisation has made.

That is why training cannot be an afterthought on the rollout. It needs to be budgeted, planned and measured as part of the investment itself with the same rigour applied to selecting a vendor or implementing a platform. Buying the technology is the visible part of the decision, of the investment. Building the capability to use it well is where the return is actually generated. Organisations that treat these as separate workstreams tend to find themselves with sophisticated tools and underwhelming results.

Also, as we stated in this previous article about AI, AI does not reduce the human role in HR, it elevates it if done well. When routine tasks are handled by intelligent systems, HR professionals gain capacity to do something more valuable: ask better questions, spot patterns before they become problems, move from reporting on what happened to shaping what happens next. But that shift only occurs when people are genuinely prepared for it. A global unbranded training programme that has been translated into 15 languages is probably not enough to consider it done.

The age dimension compounds this in multi-country workforces. Employees under 25 are significantly more likely to use AI regularly and report increasing usage. Employees aged 50 to 64 are far less likely to feel supported in building AI skills. In organisations where age demographics vary sharply by market, a single global upskilling approach will not land evenly and the capability gaps it leaves behind will show up in adoption rates, not in training completion metrics.

There is one dimension where internationally operating organisations are clearly ahead, and where that lead matters most. 54.3% say their organisation has governance in place to ensure AI is used ethically and responsibly in HR, compared to 47.1% across Europe. 56.1% say they trust their organisation to use AI in a fair and ethical way, above the 52.1% average.

For international organisations, governance is not optional. The EU AI Act classifies certain HR-related AI applications — in recruitment, performance management and workforce planning — as high-risk systems requiring specific documentation, human oversight and auditability. An organisation operating across multiple EU markets needs that governance to be consistent and explainable across all of them simultaneously. A governance framework that works in one country but cannot be demonstrated in another is a gap waiting to be found.

And employees are paying attention. 30.9% of employees in internationally operating organisations are concerned that AI could make a significant part of their work redundant, higher than the 25.4% European average. Where that concern is not addressed openly, it quietly accumulates. Employees who do not understand how AI decisions are being made, or what protections exist, are employees who are disengaged from the tools their organisation is counting on, increasing significantly the risk of stress or attrition, for example. 

Having governance in place is the starting point, being transparent by making it visible to employees to build trust and keep the community and impulse the adoption. 

• Stop deploying, start redesigning. The organisations seeing real results from AI are not the ones with the most tools. They are the ones that redesigned workflows before deploying technology into them. For international HR teams, that means identifying the processes where AI can deliver the clearest cross-border value: payroll reconciliation, compliance monitoring, workforce scheduling, etc. And rebuilding those processes around AI capability rather than bolting technology onto existing ones.
• Build capability market by market. A global rollout that does not account for local starting points, local concerns about job security, or local attitudes toward AI is unlikely to close the perception gap. Closing it requires building from the employee experience upward understanding where capability feels weakest in each market and designing for that, not for the average.
• Make governance something employees can see. Having a governance framework is necessary. Communicating it clearly: explaining how AI decisions are made, what human oversight exists, and what recourse employees have to redefine their position, etc. It is what converts structure into trust. In international organisations, that communication needs to be localised even when the governance itself is global. Different markets carry different sensitivities, different legal rights and different expectations. Governance that lives only in internal documents is not doing the job.

The story of AI in internationally operating organisations in 2026 is not one of failure. It is one of momentum without traction. The investment is real, the ambition is genuine, and the infrastructure is building, it’s a work in progress. 

The total change does not happen at the tool level but at the leadership one. For international HR leaders, the real question is whether your organisation is positioned to lead it across every market you operate in, or whether you will spend the next few years catching up

*Data sourced from the SD Worx HR & Payroll Pulse 2026, conducted by the SD Worx Research Institute in January and February 2026 across 17 European countries, surveying 5,936 HR decision-makers and 16,500 employees.*