Rethinking Enterprise Technology for the AI Era

Organizations have spent years modernizing enterprise applications, yet employees still spend much of their day navigating between systems to get work done. A simple approval, customer response or workforce request can require jumping across multiple platforms.

The issue is not that enterprise applications lack capability. It is that work rarely happens inside a single application. It is instead executed through workflows that span multiple systems.

As organizations look to improve productivity, agility, and value from technology investments, many are beginning to rethink the role of enterprise applications such as their enterprise resource planning (ERP) and customer relationship management (CRM) software. AI is opening up an exciting new range of possibilities.

Tried and true SaaS isn’t going away. Its user interface is evolving. More precisely, a new work surface is emerging.

A Different Way of Working: Employees and Superagents

For decades, enterprise applications served as both the system of record and the primary place where work happened. Employees logged into individual systems to find information, make decisions, and complete tasks. Work became fragmented across applications, with people often acting as the connective tissue between systems.

That model is beginning to change. Enterprise applications such as ERP, CRM, and HCM systems continue to play a critical role as systems of record, managing data, transactions, controls, and governance. What changes is where the work happens.

Rather than requiring employees to navigate multiple applications, an AI-powered work surface sits above these systems that combines the context, intelligence, decisions, and actions needed to achieve a business outcome. This new AI-native experience layer is the interface for employees and customers, supported by a bench of specialized agents that perform discrete tasks and more advanced superagents that coordinate work across the enterprise systems to pursue outcomes.

A Deliberate Approach to Transformation, not Wholesale Reinvention

This shift also changes how organizations think about how their investments in emerging AI capabilities and enterprise software interact at scale. Technology investments have traditionally been organized around applications, yet business value is created in end-to-end processes that are built with an eye toward the outcomes and experiences they can deliver. Customer journeys, supply chains, and workforce experiences do not follow application boundaries.  Each has its own risk profile, data requirements, and potential for differentiation.

Technology leaders have the opportunity to make deliberate decisions about which value streams are candidates for reinvention. Work that spans multiple systems, teams, decisions, and handoffs is particularly well suited to new ways of operating. In these areas, organizations should consider how they integrate new AI-powered experiences, workflows, and superagents to orchestrate the work across functions, systems and processes. In other areas, the same workflows that have been in place for years may continue to be the best fit.

The most successful organizations will be deliberate about where they reinvent—and where they do not.

Orchestration as Competitive Advantage

The organizations that rethink how work is orchestrated across their operations may be better positioned to create competitive advantage: connecting systems, teams, and AI agents so workflows around outcomes rather than application boundaries. Done well, an experience layer can reduce friction, improve decision-making, and help organizations unlock greater value from the systems they already have.

But orchestration only creates durable advantage when it has clear process ownership, trusted data, defined decision rights, and controls for when AI can act, when humans stay involved and how exceptions are escalated. And your outcomes are only as strong as the data foundation that sits below it. Organizations should ensure their foundation is ready by investing in the data products, governance, and documenting context, or institutional knowledge, that will give agents the information they need to act confidently and in a trustworthy manner.

A New Chapter for Enterprise Transformation

At KPMG, we see the future as a series of decisions that organizations need to make for themselves. There is no one-size-fits-all approach. Rather a menu of options to modernize how and where work happens. The next wave of enterprise transformation will belong to organizations that make these choices deliberately, treating agentic AI as a portfolio of business decisions to be made, not a technology migration.