Global Business Services (GBS) is at an inflection point. For years, the model has created value through scale, standardisation, labour arbitrage and disciplined process management. Those foundations still matter, but digital disruption and rising enterprise expectations are changing what good looks like.
In our recent webinar, “Prevailing trends in Global Business Services”, we explored why efficiency is increasingly the price of admission rather than the prize, how AI is reshaping service delivery, and what leaders need to align now to make GBS a platform for end-to-end enterprise outcomes.
We asked attendees about their ambition for GBS, the trends attracting investment and the barriers to scaling AI. The responses revealed an organisation-wide balancing act:
The 2030 ambition
|
Response |
% of respondents |
|---|---|
|
A Cost-Optimised Efficiency Engine |
53.8% |
|
An Autonomous Service/Operational engine |
42.3% |
|
A Strategic Value Partner |
38.5% |
|
A Digital & Innovation Hub |
30.8% |
|
A Talent & Capability Centre of Excellence |
19.2% |
|
An Enterprise Transformation architect |
15.4% |
|
Unsure / Don’t know |
15.4% |
53.8% of respondents still see GBS primarily as a cost-optimised efficiency engine. However, 42.3% selected an autonomous service or operational engine, 38.5% a strategic value partner and 30.8% a digital and innovation hub. As multiple selections were permitted, the result is less a single destination than a layered ambition: short term priorities with longer term ambition.
Today's priority
|
Response |
% of respondents |
|---|---|
|
Digital, automation, and GenAI enablement |
41.9% |
|
Standardisation and process consistency |
29.0% |
|
Cost efficiency and labour arbitrage |
22.6% |
|
Access to global talent and critical skills |
0.0% |
|
Don’t know/not applicable |
6.5% |
Digital, automation and GenAI enablement led the second poll at 41.9%, ahead of standardisation and process consistency at 29.0% and cost efficiency and labour arbitrage at 22.6%. Investing today in these priorities is crucial to achieving 2030 GBS ambitions.
The biggest constraints
|
Response |
% of respondents |
|---|---|
|
Data quality, security, and governance limitations |
29.2% |
|
Capability: Lack of skills or capability gaps |
25.0% |
|
Capacity: Availability of existing capacity |
16.7% |
|
Clear use cases and measurable value/ROI |
16.7% |
|
Not currently scaling GenAI/no barriers identified/unsure |
8.3% |
|
Capital: Access to capital |
4.2% |
Data quality, security and governance ranked first at 29.2%, closely followed by skills and capability gaps at 25.0% which, interestingly, did not feature in the current priorities poll. Capacity and the need for clear use cases and measurable value each received 16.7%, while access to capital was selected by 4.2%. The message is clear: technology is only one part of the scaling challenge.
These findings reinforce a central theme from the discussion: leaders are not choosing between efficiency and enterprise value. They are being asked to deliver both, while strengthening the foundations needed to scale.
Two imperatives are converging. First, AI and other exponential technologies are absorbing more repeatable activity, reducing the runway for labour arbitrage as the primary source of value. Second, enterprise expectations have moved beyond cost reduction to speed, resilience, customer experience and growth.
The leadership choice is therefore not whether to add technology to today's operating model. It is whether to keep optimising a shrinking pool of transactional work or reposition GBS as the place where end-to-end processes are orchestrated and transformed. That requires a broader mandate, new measures of value and clearer accountability across functions.
Today, much of GBS capacity remains focused on running the business. The future ambition discussed in the webinar is materially different: digital full-time equivalents absorb routine volume while human capacity shifts towards transformation and architecting business solutions.
The reinvestment decision: Automation can release capacity, but the value captured depends on what happens next. If that capacity is treated solely as cost takeout, the organisation receives a one-time benefit. If it is deliberately redirected into transformation, insight and solution architecture, GBS can become an engine for continuous enterprise value.
An integrated system of work: Run teams, transformation teams and enterprise architects need to operate as one system, supported by appropriate roles, governance and funding. The objective is not simply to keep the lights on more cheaply, but to use digital capacity to improve outcomes while maintaining control and service quality.
Agentic AI does more than make existing services cheaper. It changes what customers consider acceptable. As proactive, end-to-end services become possible, they can quickly become the baseline expectation. Three shifts follow: from cost focus to value partnership; from siloed processes to AI-enabled workflows that transcend organisational boundaries and human constraints; and from automation of individual process steps to broad digitalisation
There is no single destination model for GBS. Organisations continue to use outsourcing, centres of excellence, shared services and captive or Global Capability Centre structures, often in combination. Models such as Build-Operate-Transform-Transfer are becoming more popular as the traditional value case for GBS moves from one of mere cost optimisation to creation of value driven by Partners that can transform at speed and scale to then be brought back in-house as a transformed capability.
The right choice depends on current maturity, capability needs, risk appetite and the strategic importance of the work.
India, the US and Poland remain prominent GBS locations, while Mexico and Spain are becoming increasingly important. Yet location decisions are no longer simply a cost exercise. Access to skills, the ability to scale specialised capabilities and delivery resilience are increasingly influential.
What You Should Take Away
The GBS organisations that lead will not simply process transactions faster. They will use integrated data, technology, talent and governance to sense, decide and transform faster across the enterprise. The direction of travel is clear: from an efficiency engine towards an AI-augmented platform for measurable, sustainable value.