It’s been about fourteen years since martech emerged, and in that time companies have spent billions trying to deliver on its transformational promise. Some have succeeded, but many fail to deliver strategic business outcomes such as revenue growth and customer satisfaction. Can AI change that?
Yes, according to a new report from McKinsey & Company, which says technology is giving marketers a rare opportunity for innovation. However, they must solve the organizational and operational issues that crippled first-generation martech implementations.
The martech sector reached $131 billion globally in 2023 and is expected to grow 13.3% year-on-year to above $215 billion by 2027. The proliferation of tools continues to increase, with the number of platforms growing from approximately 350 in 2012 to an estimated 15,000 in 2025.
But despite 90% of martech decision makers believing the right stack can drive growth and loyalty, most still rely on outdated practices: batch-and-blast email, simplistic A/B testing, and channel silo workflows. According to McKinsey’s ‘Rewiring martech: From cost center to growth engine’, 65% of B2C organizations lack key capabilities such as data unification, omnichannel integration and executive sponsorship.
Four deep-seated martech failures
The report highlights four recurring failure points:
1. Lack of executive ownership. Martech still often operates in a silo without C-suite support or company-wide integration. CMOs tend to prioritize media spend over martech funding and cross-functional alignment between IT, finance and marketing remains rare.
2. Stack Expansion Strategy. Nearly half of respondents say their martech complexity prevents them from realizing value. Older tools often overlap in function, making identity resolution and trajectory orchestration difficult at scale.
3. Misaligned measurement. Few organizations link martech performance to strategic KPIs. Teams use standard vanity metrics like open rates instead of business results like CLV or speed-to-market.
4. Capacity gap. As martech evolves quickly, teams often lack the skills to extract value from it. About a third of decision makers cite underskilled talent as a barrier.
An AI-powered second chance
To break this cycle, McKinsey recommends reframing martech as a strategic operating system infused with AI. Instead of linking tools together, companies must build intelligent, unified systems for real-time personalization and end-to-end journey orchestration.
Key recommendations include:
Bring martech to the C-suite. Senior leaders must embed martech into business strategy, define business-related outcomes, and champion governance across functions. A strong data strategy, focused on a dynamic customer diagram and uniform ID, is fundamental.
Shift from tools to systems. Leaders must rationalize fragmented stacks and consolidate functionality into AI-powered platforms. AI agents can automate data flow, decision making, content generation, and channel orchestration across four key layers: data, decision making, design, and distribution.
Measurement as a growth engine. Map the total cost of ownership (TCO) and link martech investments to revenue increases, speed gains and productivity improvements. One global retailer used controlled A/B testing and time-motion studies to quantify ROI and align finance and purchasing stakeholders.
Close the capacity gap. Continuous learning and onboarding are essential. AI can lower the technical barrier and serve as a co-pilot helping marketers focus on strategy and creativity.
Dig deeper: AI productivity gains, like vendor AI allowances, are hard to find
A roadmap for AI-focused reinvention
McKinsey outlines a four-step approach to rebuilding martech around AI:
- Set the North Star. Define business outcomes that guide the martech architecture.
- Map the future state. Identify high-impact workflows and where AI agents (or human roles) should have their execution.
- Build a road map. Define data, technology and talent requirements. Test out-of-the-box use cases while planning for long-term capabilities.
- Implement and repeat. Launch minimum viable products (MVPs), manage changes, and scale use cases as adoption grows.
In short
AI can do a lot, but not everything (despite the claims of some boosters). It absolutely cannot solve systemic problems. Marketers have a rare opportunity to fix what’s broken in martech. However, success depends on rethinking martech as a key growth driver, measured, governed and integrated across the enterprise.
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