The CX Execution Crisis

We’re witnessing something unprecedented in customer support (CS) and customer experience (CX) Operations: a widening gap between what organizations say they want and what they can actually deliver.

Our recently published research, surveying these functions’ decision-makers across multiple industries between October and November 2025, reveals a market approaching an inflection point.

The data tells a story of strategic clarity colliding with operational reality, and the consequences of this collision will reshape how we think about building versus partnering for CX excellence. It points to gaps in AI implementation, and also in measurement, support, and global capability.

The Worrying Numbers

Let me share the statistics that stopped me in my tracks: 75.7% of organizations prioritize AI and automation investments in the next 12 months. That’s three-quarters of the market moving in the same direction (also see FIGURE 1).

But here’s where it gets interesting. 48.6% simultaneously struggle with agentic AI implementation, and 64.9% face limited budgets and resources.

Read those numbers again. Nearly half the organizations racing toward AI lack the capability to implement it. Two-thirds are trying to do so with inadequate resources. The result is an AI implementation gap.

This isn’t a technology problem. Instead, it’s an execution crisis.

I’ve spent years building organizations that deliver CX excellence at scale. What this data reveals is that AI investment is increasingly being mistaken for AI progress. Organizations are committing to strategies their operating models are structurally unable to deliver.

Understanding the AI Gap

Our research identifies two distinct cohorts emerging: AI-Capable organizations (51.4%) and AI-Aspirational organizations (48.6%). The difference between these groups isn’t budget size or strategic vision; it’s execution infrastructure.

AI-Capable organizations have moved beyond AI ambition into repeatable deployment. They still face complexity, but they have:

• Technical infrastructure and data foundations that support automation at scale (clean data, integrated knowledge, and operational analytics).
• Internal AI expertise and delivery capacity (dedicated owners, implementation resources, and governance to ship and iterate).
• Change management and adoption frameworks that drive agent and customer uptake (training, playbooks, and performance reinforcement).
• Integration capabilities across the existing technology stack so AI can operate end-to-end (CRM, ticketing, WFM, QA, and reporting).

These organizations tend to treat AI as an operating model upgrade: measuring time-to-value, redesigning workflows, and building feedback loops to improve outcomes over time.

AI-Aspirational organizations demonstrate consensus on AI’s strategic importance. They’ve allocated a budget. They’ve made commitments. But they lack:

• The technical infrastructure and data foundations necessary for implementation; 35.1% struggle with digitalization and advanced analytics.
• Internal expertise and implementation resources.
• Change management and adoption frameworks.
• Integration capabilities with existing technology stacks.

These organizations face a critical decision: build internal capabilities (requiring 18-24 months and significant investment) or access capabilities through strategic partnerships. Given that nearly 65% already face resource constraints, the math on internal builds becomes increasingly challenging.

Organizations are committing to strategies their operating models are structurally unable to deliver.

Taken together, these two cohorts define the AI implementation gap: nearly everyone agrees AI is the next lever for efficiency and experience. But only about half have the infrastructure, talent, and operating discipline to turn spend into measurable impact.

For AI-Aspirational teams, the risk is obvious; AI becomes a line item without ROI. For AI-Capable teams, the risk is different: the bar rises quickly, and sustaining investment depends on proving value continuously.

The Measurement Gap

Our survey reveals a fundamental shift in how organizations conceptualize CS and CX Operations value. Revenue impact and customer retention are now tied as the top CX priority, each at 29.7%, while traditional metrics like CSAT (16.2%) and NPS (10.8%) are being deprioritized.

This represents CS and CX Operations function maturation. Organizations increasingly view support as revenue drivers, retention mechanisms, and as growth catalysts: not just as cost centers.

The problem? 35.1% have difficulty measuring impact on business results, and 24.3% struggle to justify investments to C-suite executives.

Organizations have achieved strategic clarity; they understand revenue metrics matter but they lack the frameworks, data infrastructure, and analytical capabilities to measure effectively.

This measurement gap undermines investment justification efforts and resource acquisition, creating a self-reinforcing constraint cycle.

CS and CX Operations leaders who are unable to demonstrate revenue impacts will see their budget allocations decline by 15%-20% according to our projections.

This reduction in financing, but also in prestige and internal organization respect, will accelerate the talent exodus, which I will discuss next; 21.6% already perceive their departments’ functions as cost centers despite this strategic shift.

The Support Gap

The data on organizational support reveals a leadership crisis in CS and CX Operations functions. Only 18.9% of CS and CX leaders feel highly supported by their organizations, while 56.8% struggle to secure resources. The average organizational support score is just 3.7 out of 5.

Despite the rhetorical elevation of CX’s importance, leaders report insufficient resources. 64.9% face organizational resource constraints, measurement and credibility challenges, and limited strategic integration.

This tells us that most organizations operate in environments that expect high performance but provide low institutional support for their employees.

This support gap creates critical mid/senior-level management retention risks, which, in turn, could result in lowered CX and higher frontline, including contact center agent performance, burnout, and turnover.

CS and CX Operations leaders who are unable to demonstrate revenue impacts will see their budget allocations decline by 15%-20% according to our projections.

Simply put, high-pressure environments with inadequate support drive burnout. Organizations risk losing CX leadership talent to:

• Competitors offering better support and resources.
• Consulting firms seeking practitioners with real-world experience.
• Technology vendors building customer success functions.

Our research identifies four organizational maturity segments: Champions (18.9% highly supported), Progressives (37.8% well supported), Traditionalists (29.7% moderately supported), and Laggards (13.5% poorly supported).

There is an upside in our data. The concentration of organizations in the middle segments suggests significant opportunity for differentiation through CX investment.

The Global Capability Gap

Our research reveals persistent operational deficits that have real competitive consequences. 32.4% of organizations lack 24/7 coverage and 18.9% lack multilingual support capabilities, even as businesses expand digital channels and global customer reach.

The alignment between these capability gaps and outsourcing priorities is striking: 32.4% cite 24/7 coverage as an important outsourcing factor and 29.7% cite multilingual support.

For organizations that prioritize revenue impact and customer retention, these capability gaps directly undermine strategic objectives.

But organizations that recognize these deficits, and understand external partnerships, may be able to address them more effectively than those that are building them internally.

Digital channels create 24/7 access expectations while geographic expansion requires multilingual support. Competitors with these capabilities capture demand while organizations without them experience revenue leakage.

The In-House Paradox

Perhaps the most revealing finding from our CS and CX Operations survey is what I call the “In-House Paradox.”

75.7% of organizations maintain fully in-house support teams, yet the average satisfaction with current setups is just 7.0 out of 10. Only 40.5% rate their model as high performing (scores of 9-10).

Think about what this means: organizations are tolerating mediocre performance rather than pursuing alternative operational models.

A 7.0 satisfaction score signals that most in-house teams are delivering “good enough,” not excellence. In a competitive landscape where CX increasingly determines market winners and losers, “good enough” is a strategic liability.

Why do organizations cling to in-house models? Several factors drive this paradox.

• There’s concern about brand representation and customer relationship ownership.
• There are previous experiences with legacy BPO models and the call center nightmares of decades past.
• Influenced by the legacy model’s most visible failure modes: cost-driven staffing, inconsistent training, script dependency, fragmented systems, and “ticket ping-pong” that made customers repeat themselves and stretched simple issues into multi-contact journeys.
• And there’s a belief that CS and CX Operations represent core competitive differentiation requiring internal ownership.

The last point deserves scrutiny. If customer support is truly a competitive differentiator, why accept mediocre outcomes? Organizations are clinging to in-house models not because they work well, but because switching feels riskier than tolerating underperformance. That calculus is about to change.

The Path Forward

The data reveals no single path to CX excellence. Success depends on honest capability assessment, strategic prioritization, and a willingness to access external expertise where internal builds prove impractical.

Organizations that embrace hybrid models, combining internal strategic ownership with external capability access, will achieve superior outcomes compared to purely internal or fully outsourced approaches.

The key is moving beyond the In-House Paradox: the preference for internal control despite mediocre outcomes.

For CS and CX leaders, the imperative is clear.

First, audit your AI implementation capability honestly. If you’re in the 48.6% struggling with agentic AI implementation, acknowledge that reality rather than hope your way through it.

Second, quantify your measurement gaps. If you can’t demonstrate revenue impact, you can’t justify investment, and you can’t break the resource constraint cycle.

Third, evaluate hybrid models seriously. The BPO industry has evolved dramatically from the offshore call center nightmares of the past. Modern partnerships can feel like extensions of internal teams while delivering capabilities that would take years to build.

Fourth, advocate for organizational support elevation. The current support deficit (3.7/5 average) undermines execution and creates talent retention risks. CS and CX Operations leaders must make the case for strategic integration, not just operational resources.

The 2026 Inflection Point

We project that sometime this year (2026), 70% of organizations maintaining fully in-house CS and CX Operations will face critical scaling challenges due to AI capability gaps and resource constraints, forcing strategic decisions about build-versus-partner models.

Organizations that fail to resolve the AI implementation gap will also experience 25%-30% higher customer acquisition costs compared to competitors with mature AI-enabled operations.

Success depends on honest capability assessment, strategic prioritization, and a willingness to access external expertise...

The convergence of AI capability requirements, resource constraints, and evolving success metrics creates both risk and opportunity.

Organizations must resolve the fundamental tension between AI ambition and implementation capability, closing that gap, while simultaneously addressing operational gaps in measurement, support, and global capabilities and their frameworks.

The organizations that bridge these gaps, whether through internal builds, strategic partnerships, or hybrid models, will transform CS and CX Operations from operational necessities to competitive advantages.

But those that don’t will find themselves on the wrong side of an increasingly unforgiving market.

The data is clear. The clock is ticking. The question for every CX Operations leader is simple: which cohort will you be in?