The Future of Corporate Services

In June 2026, KPMG brought together 250 delegates from 72 organisations for Future of Corporate Services Unleashed at One Great George Street in Westminster. Senior public sector leaders, private sector counterparts and industry specialists explored how corporate services can respond to sustained budget pressure, rising expectations, ageing systems, AI disruption and workforce change.

The discussion reinforced that corporate services can no longer be viewed simply as back-office administration. When designed well, they bring together people, process, technology and data to improve resilience, release capacity, strengthen decision-making and help frontline teams deliver better outcomes for citizens and staff.

Across the day, three priorities came through clearly: redefining efficiency and value for money; modernising digital and legacy environments while protecting live services; and designing services around citizens, staff and users. These priorities are closely connected. Sustainable efficiency depends on simpler processes and clearer accountability, while technology creates value only when it is tied to operating model change and genuine user need.

Candice Sieg

Partner - Global GBS and Outsourcing Advisory Lead

KPMG in the UK

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Redefining efficiency around value

Public services continue to face pressure to do more with less, but the discussion moved beyond traditional cost reduction. Sustainable productivity is less about asking stretched teams to work harder and more about redesigning the work itself: simplifying processes, removing duplication, reducing failure demand and focusing effort where it creates the greatest value.

This matters particularly for crucial services such as payroll, where errors or disruption can have significant consequences. Efficiency therefore needs to be considered alongside service quality, resilience and control. Leading organisations are simplifying before they automate, making deliberate choices about where to standardise and invest, and creating space for higher-value activity.

The strongest transformations also demonstrate value throughout the journey rather than waiting for the end state. Early, visible benefits can build confidence, sustain sponsorship and create headroom for wider change. In a constrained environment, practical no-regret actions can help organisations protect services today while preparing for a more ambitious future model.

Modernising services without losing control

Many organisations still operate in complex legacy environments, but transformation cannot wait for ideal conditions. The discussion pointed towards phased, service-led modernisation that protects live operations while progressively simplifying, integrating and upgrading technology. The aim is not technology change for its own sake, but a more adaptable service model that can evolve without repeatedly recreating legacy.

AI increases both the opportunity and the need for discipline. It can automate routine activity, improve decision support and create more intuitive access to services. However, AI does not replace the foundations of transformation; it amplifies them. Clear use cases, appropriate data, robust governance, standard processes, modular architecture and effective change capability all influence whether early experimentation can scale with appropriate control and deliver measurable value.

Modernisation must also improve the experience of the people who use corporate services. Fragmented, function-led models can create multiple entry points, hand-offs and inconsistent outcomes. Designing around end-to-end user journeys, supported by clearer ownership, connected systems and integrated digital access, can reduce friction and avoidable demand while improving service quality.

What we discussed and key insights

The strongest organisations are using corporate services to connect people, processes, technology and data across the enterprise. This creates a platform for better prioritisation, stronger control, improved service quality and faster response to change.

Key insight:

Leaders should position corporate services as an enterprise capability tied to organisational outcomes, rather than as a collection of separate functional efficiency initiatives.

Lasting efficiency comes from simplifying processes, removing duplication and reducing avoidable demand, not from asking constrained teams to deliver more through unchanged operating models.

Key insight:

Organisations should simplify and standardise work before automating it, focusing investment on changes that release capacity while protecting service quality and resilience.

AI can accelerate automation, insight and service experience, but it cannot compensate for unclear value, weak data, fragmented processes or ineffective governance.

Key insight:

AI investment should be connected to defined outcomes, prioritised use cases, suitable data, robust controls and disciplined change management.

Wholesale replacement is not always practical in complex public service environments. Phased modernisation can enable progress while critical services continue to operate.

Key insight:

Data, security, architecture, governance and change management should be designed in from the outset, with realistic capacity for running and transforming services at the same time.

Multiple entry points, hand-offs and fragmented processes create effort for citizens, staff and service teams. Better experience can reduce friction, rework and avoidable demand while improving outcomes.

Key insight:

Services should be designed around end-to-end user journeys, with integrated access, clearer accountability and strong functional input into the intended outcomes.

Partners can bring expertise and delivery support, but accountability for outcomes, controls, service quality and benefits remains with the organisation.

Key insight:

Transformation needs visible ownership, governance that enables timely decisions, and leaders able to sustain alignment across functions, partners and organisational boundaries.

As routine activity changes, organisations will need greater capability in judgement, decision-making, leadership, AI governance and oversight.

Key insight:

Workforce and learning strategies should be treated as core components of transformation, not activities deferred until the new model or technology has been implemented.