Transformation priority number one: Augmented care

#1. Bottom line impact

Customer care is the longest-standing AI battleground for organizations across nearly every commercial sector. Most consumers have first-hand experience of augmented care – from scripted chatbots and rule-based IVR back in the early 2000s, right through to agentic AI and outcome-based service. This longevity means that augmented care is a mature discipline in terms of technology, process, and customer acceptance. It has also enabled businesses to identify successful methodologies for generating tangible P&L benefits.

This bottom-line case for augmented care rests on a simple mechanism: every incoming customer request that can be resolved without human intervention removes a unit of cost from the operation. The more of that volume an organization can automate, and the more completely it can resolve a query in a single interaction, the greater the productivity gain realized.

This is not a theoretical model. For example, BearingPoint enabled a global logistics client that delivers 5.2 million parcels and 55 million letters each day to integrate AI-guided automation into its legacy customer service infrastructure.² This reduced the volume of incoming requests requiring human handling by 40%, a shift that converted directly into bottom-line savings at the same scale.

#2. Driving competitive advantage through CX

Augmented care improves customer experience (CX) through the same mechanism that reduces cost. Resolving a query correctly on first contact, without requiring a customer to repeat information across multiple channels or follow-up exchanges, is the foundation of great customer experience.

Well-implemented AI-augmented automation delivers this consistently, alongside faster response times and increasingly personalized handling based on account history and prior interactions. Among BearingPoint clients, this operational discipline has translated into measurable increases in Net Promoter Score (NPS) alongside cost reduction.

Customer experience measures such as NPS have taken on greater strategic importance as CX is increasingly accepted as a core business objective. Forrester has reported that ‘customer-obsessed’ organizations prioritizing CX enjoy 41% faster revenue growth, 49% faster profit growth, and 51% better customer retention.³ More recent research suggests that as many as 76% of consumers have chosen one brand over a competitor based solely on service quality⁴, making customer service a key determinant of competitive position rather than a secondary concern.

#3. A lower barrier to entry

The third argument for prioritizing augmented care is structural rather than technological. Elsewhere in the enterprise, AI adoption is often slowed not by the technology itself but by the organizational change it requires.

Realizing productivity gains from automation can require either retraining and reallocating staff to different work, a genuine and time-consuming transformation in itself, or headcount reductions that organizations rightly approach with caution. Augmenting customer care has a different starting point.

Many industries already use business process outsourcing (BPO) providers for some or all of their customer care rather than internal headcount. The outsourced customer care market has grown to over $77 billion and is projected to exceed $113 billion by 2030⁵, with customer service representing 31% of global BPO purchases and activity.⁶ Since this workforce sits outside the organization, the initial burden of AI-driven automation – retraining, redeployment, headcount reduction – falls first to the provider, as part of its own operating model, rather than requiring an internal workforce transition.

This lowers the barrier to starting AI-driven optimization in customer care relative to functions where the affected workforce is internal. Conversely, however, as AI reduces the labor intensity of customer care, some organizations are opting to bring elements of it back in-house rather than continuing to pay a provider's margin on work that no longer requires the same scale of external headcount. 

The more durable opportunity, then, is optionality rather than permanent delegation. As BPO providers absorb the early workforce disruption, the organization can pursue automation with minimal internal upheaval and later decide whether to internalize a leaner, AI-enabled version of the function. In this way augmenting customer care shifts the competitive differentiator from headcount to the quality and engagement of the remaining workforce, both on the front line and in management.

#4. The ideal fit for Outcome-as-a-Service

The fourth consideration in our call for prioritization of AI-augmented customer care returns to commercial grounds.

Across enterprise services, AI pricing is shifting away from licenses, seats, and time-and-materials, toward payment for outcomes actually delivered. This shift toward outcome-based contracting is sometimes termed outcome-as-a-service (OaaS). One independent study projects that by 2029, 30% of all service provider contracts will be outcome-based, a shift attributed directly to the capabilities agentic AI is introducing.⁷

Customer care sits at the front of this shift simply because a resolved customer query is one of the clearest, most measurable outcomes available in any business function. Augmented care is therefore easier to define, price, and audit within this OaaS model than other functional areas of an enterprise. Organizations that build this capability in customer care now secure both an immediate return and a structural headstart on how AI-driven services will be bought and sold more broadly in the future.