RWS Forrester study models 212% ROI on AI-plus-human localisation

RWS, the AIM-listed language technology and services group, has published a Forrester Consulting Total Economic Impact study claiming its combined AI and human localisation platform generated a modelled 212% return on investment for a composite customer over three years. The study, commissioned by RWS and published in September 2026, calculated $21.7 million in gross benefits against $6.9 million in costs, producing a net present value of $14.7 million and a projected payback period of under six months.

Forrester interviewed four decision-makers at RWS customers and aggregated their responses into a single composite organisation: a global technology company with more than $30 billion in annual revenue, operating multilingual content programmes across 32 languages by the third year of the modelled period. The identified benefits span direct translation cost savings, reduced delays to international product launches, localisation project-management efficiency gains, and lower third-party quality-validation expenditure.

What the model covers

The study examined RWS's integrated stack, which combines Trados Enterprise, its translation-memory and workflow platform, with Language Weaver, its neural machine-translation engine, and a layer of expert linguistic services. According to the research, the composite organisation progressively increased its use of automation, translation memory, machine translation and self-service tooling over the three-year period, with financial returns growing year on year as the model matured.

Ben Faes, chief executive of RWS, said: "The real value comes from combining AI with human expertise in the right way. As organisations increase automation while applying specialist knowledge where it matters most, they can reduce costs, accelerate international launches and create measurable business value."

Beyond the quantified financial metrics, the study noted qualitative benefits including brand-voice consistency, improved compliance and security governance, and greater visibility into translation activity across the enterprise, though these were not included in the ROI calculation.

Market context

The enterprise localisation market sits at the intersection of two live competitive pressures. On one side, large language model providers and general-purpose AI platforms are making it progressively easier for buyers to run basic machine translation without a specialist vendor. On the other, buyers with regulated content, brand-sensitive assets or high-volume multilingual pipelines are discovering that raw MT output requires significant post-editing and governance overhead, sustaining demand for managed services with human-in-the-loop quality controls.

RWS competes in this space with Lionbridge, TransPerfect and a range of specialist technology vendors including Phrase and Smartcat. The "blended" positioning, pairing automation with domain expertise, is a common response across the sector to the commoditisation pressure that large language models are exerting on pure translation technology plays.

It is worth noting the methodological limitations of Total Economic Impact studies: they are commissioned by the vendor, built on a composite organisation rather than a single named customer, and carry Forrester's standard risk-adjusted caveats. The 212% figure is a modelled projection, not a directly observed outcome, and actual returns will vary materially depending on content volume, language complexity, existing tooling and internal change-management capacity.

Regulatory and compliance read-across

RWS's emphasis on governance, security and compliance readiness in the study reflects a real market shift. The EU AI Act's transparency and human-oversight provisions, phasing in through 2025 and 2026, place obligations on organisations deploying AI in content-generation workflows, including localisation pipelines that feed regulated communications. Buyers in financial services, pharmaceuticals and public sector verticals are increasingly requiring audit trails and human sign-off at defined quality gates, which supports the argument for managed hybrid services over fully automated translation.

RWS's next disclosure will be its full-year results; investors will be watching whether the commercial pipeline reflects the ROI narrative the Forrester study is designed to support.