AI Ambition Is Outpacing Marketing Readiness
Marketing leaders are racing to embed AI into their stacks, but their organizations are struggling to keep up. Gartner’s CMO Spend Survey shows CMOs now direct an average of 15.3% of their marketing budgets to AI initiatives, with 70% viewing AI leadership as a critical goal. Yet only 30% say they have mature AI readiness, underscoring a widening gap between ambition and operational reality. Many teams lack the governance, data foundations, workflows, and talent models required to operationalize AI at scale. This disconnect fuels a new wave of enterprise platform replacement: CMOs invest in AI-layered suites expecting transformation, while day-to-day users encounter clunky integrations and fragile processes. As a result, AI adoption strategy is shifting from “buy more tools” to “rationalize the stack,” pushing organizations to question whether incumbent platforms can realistically deliver the promised AI-powered growth and efficiency.
Martech Consolidation: Replacing Working Software to Make Room for AI
Across the business, martech consolidation is becoming a prerequisite for AI adoption rather than a side effect. A Software Finder study reports that 55% of businesses are consolidating software tools as part of their AI adoption strategy, while 30% have already replaced software with AI-powered alternatives in the past year. Strikingly, 78% say they replaced tools that were still functioning properly, and 44% feel pressure to swap out working software simply because AI alternatives exist. Budgets are following this shift, with more than half of respondents allocating between 10% and 24% of their software spend to AI platforms. For marketing software tools, this translates into ruthless vendor selection: platforms that cannot embed automation, insights, and AI-native capabilities are being retired, even if they “work.” Flexibility, interoperability, and AI depth increasingly trump the traditional arguments for suite stability or long-standing vendor relationships.
Shadow IT Reveals How Marketers Really Vote on Their Stack
When enterprise platforms fail to deliver value, marketers quietly route around them. What looks like adoption resistance is often deliberate non-use. Research on digital adoption found executives believe their organizations run about 35 apps, but the reality is 661, illustrating how deeply unofficial tooling has penetrated daily work. In marketing, this shows up as teams embracing specialist apps instead of central platforms. The MarTech Composability Survey reports that 82.7% of marketers routinely choose specialist tools over what their main platform offers, most often citing superior functionality and user experience. This silent divergence effectively becomes a bottom-up vendor selection process. While leadership defends prior investments in DXPs or suites, practitioners assemble their own AI-friendly workflows. The result is a bifurcated stack: an official enterprise platform on paper and a parallel ecosystem of AI-first, fit-for-purpose tools that get the actual work done.
When Voice of Customer Platforms Stop Making Customers Feel Heard
The crisis around a major Voice of Customer provider highlights a deeper issue: legacy VoC systems are failing to make customers feel genuinely heard. The Medallia–Thoma Bravo story is more than a leverage problem; it signals that an entire category is expiring. Traditional VoC platforms often reduce rich, emotional feedback to static Net Promoter Scores and long, generic surveys. Customers are not tired of being asked—they are tired of being asked badly and seeing nothing change. Meanwhile, some organizations misread the moment and swing hard toward behavioral observability alone, assuming AI summaries of clicks and sessions can substitute for direct customer voice. The emerging CX battleground is different: brands need listening infrastructure that closes feedback loops quickly, captures qualitative signals, personalizes outreach, and shows visible action. Marketing teams are increasingly replacing legacy VoC tools with AI-enhanced, real-time feedback systems that deliver insight, not just dashboards.
Private Equity, Vendor Crises, and the New Rules of Vendor Selection
Private equity ownership is quietly reshaping martech stability and feature roadmaps. The Medallia transaction, with control shifting to a creditor group after Thoma Bravo reportedly walked away, is a warning shot for buyers that financial engineering can directly impact product continuity. When leading investors exit a flagship platform that helped institutionalize Net Promoter Score, the signal is not simply balance-sheet stress; it suggests underlying category fatigue and an innovation gap. For marketing leaders evaluating enterprise platform replacement, this changes the risk calculus. Vendor selection can no longer rely only on feature checklists and reference calls. Teams must scrutinize ownership structures, debt levels, and investment horizons alongside AI capabilities and roadmap transparency. In a market where 55% of businesses are consolidating tools to support AI, marketers will increasingly prioritize vendors that combine AI-native functionality with organizational resilience and a credible path to continuous product evolution.