Enterprise organizations have never had more powerful technology at their disposal. AI-enabled marketing platforms, customer experience tools, and data infrastructure are more sophisticated than ever. So why do organizations still struggle to see returns? Because they’ve leveled up their technology but haven’t addressed organizational transformation.

That's the central finding from Merkle's latest quantitative study of 100 US C-suite and VP-level executives at enterprises with 500 or more employees. The results shed light on why so many organizations are still working to unlock the full value of their marketing and CX technology investments.

Our research segments enterprises into two groups based on their marketing and CX technology maturity: Early/Developing (48%) and Leading/Advanced (52%). The performance gap between these two groups is striking and has almost nothing to do with the platforms they’re using.

Leading organizations report 3x higher ROI from their marketing and CX technology investments compared to their developing counterparts (46% vs. 15% top-two-box). They’re 6x more agile at adapting operating models and workflows when new technology is introduced, and when they implement a new platform, they are less likely to face multi-quarter delays.

The difference is that mature organizations have built the change management, governance, and work design infrastructure to actually benefit from new platforms. Employees have training, guidelines, and clear reasons to use the technology to improve their work and the business’s performance.

When executives in developing organizations struggle to realize value from their technology investments, it's tempting to blame integration complexity or vendor limitations. But the data tells a different story.

The top causes of technology underutilization are all people and process failures: unclear use cases and limited platform understanding (36%), talent gaps (31%), and insufficient training for end users (28%). The training gap is particularly acute in developing organizations, where 67% report insufficient enablement compared to 42% of leading organizations.

That gap reflects a deeper difference between the two segments. Forty percent of developing organizations rely on informal change management, handled ad hoc by project or department leads, compared to just 15% of leading organizations. Leading organizations are 3.5x more likely to operate with a formalized change management function backed by dedicated resources.

One of the most telling findings in the research is what executives cite as the primary cause of change management barriers: competing transformation initiatives, named by 64% of respondents.

This compounds the enablement problem. When teams are stretched across multiple transformation workstreams, training gets deprioritized, ownership becomes unclear, and new tools go underutilized. The result is change fatigue rather than change momentum.

Confidence in AI adoption is high across both segments. Ninety percent of leading organizations and 77% of developing organizations say they're confident in their ability to adapt to enterprise AI-driven transformation over the next 24 months.

Scratch beneath the surface, though, and a hidden risk emerges. Developing organizations are 6x more likely to have no AI governance framework in place (13% vs. 2% of leading organizations). They are significantly less likely to have formal risk frameworks, AI review committees, human-in-the-loop requirements, or defined roles for AI oversight.

High confidence without governance infrastructure leaves organizations more exposed than they realize. As AI becomes further embedded in marketing and CX operations, organizations without proper guardrails face compounding execution risk that their confidence scores simply don't reflect.

The research points to five practices that distinguish high-maturity organizations from their peers:

1. Unified leadership alignment. Leading organizations are 2.5x more likely to maintain strong alignment across marketing, technology, and data leaders around a shared CX vision.
2. Formalized change management. High-maturity organizations treat change management as a function, not a side responsibility. They resource it, staff it, and hold it accountable to outcomes.
3. Sustained investment in upskilling. Leading organizations are significantly less likely to cite technical skills gaps as a top barrier.
4. Cross-functional work design. More than two-thirds of all organizations report systemic work design failures, including structural silos and fragmented processes. Leaders address this by redesigning roles, codifying how humans and AI work together, and implementing cross-functional operating models.
5. Metrics tied to business health. Leading organizations prioritize revenue impact (67% vs. 48%) and forecasting accuracy (44% vs. 17%) as success metrics. Developing organizations are more likely to track nothing at all, with 8% reporting zero success metrics for their AI and technology initiatives.

The message from this research is clear: technology investments alone will not deliver transformation. The organizations pulling ahead are those that treat change management, talent enablement, and governance as first-class strategic priorities, not afterthoughts.

Re-wiring the enterprise for tech-driven transformation means building the organizational capabilities that allow your technology to actually perform. Developing enterprises that invest in people, process, and structure can start closing the gap between technology purchases and real business impact.