Marketing Leaders Face an AI Literacy Gap

A recent Gartner finding reveals that CMOs are falling behind both consumers and their own teams in AI execution, creating a readiness gap as AI transforms marketing. The report highlights a striking disconnect: only 15% of CEOs view their CMOs as strongly AI-savvy for 2026, while 65% of CMOs expect AI to dramatically change the role. Yet only 32% see a need to upgrade their own skills.

That finding is relevant well beyond enterprise marketing departments.

In promotional products, AI is already entering familiar areas: product copy, catalogs, mockups, virtual samples, customer follow-ups, email routing, product search, proposal creation, and sales support.

Many teams first experience AI as a productivity tool because it helps them create faster or automate repetitive work.

While it is useful, it is only the first layer.

The larger question is whether leaders understand where AI should influence the business model: how products are discovered, how distributors build recommendations, how suppliers support channel partners, how CRM data guides outreach, how customer intent is interpreted, and how operational decisions are made.

For suppliers, AI literacy means knowing what makes products easier to find, understand, recommend, quote, and order. Product data quality, pricing accuracy, inventory visibility, decoration details, use-case context, and merchandising logic all affect whether AI-enabled tools can surface the right product at the right moment.

For distributors, AI literacy means understanding how buyer history, budget, industry, timing, event type, brand rules, and sales activity can shape better recommendations. AI can create a proposal quickly, but the quality of that proposal depends on the context behind it.

At the leadership level, if AI is treated only as a content shortcut, businesses may create more assets without improving relevance, conversion, or customer experience.

But if leaders understand the data, workflow, and measurement requirements behind AI, they can prioritize use cases that improve selling speed, product discovery, customer engagement, and operational efficiency.

Gartner’s point about the “productivity trap” is especially useful here. When leaders first see AI through content generation, analytics, or workflow automation, they may treat AI as a team efficiency issue rather than a strategic growth capability.

Promo businesses should avoid that trap.

The next phase of AI adoption in branded merch will require leaders to ask better questions:

  • Which use cases matter most?
  • What data must be trusted?
  • Where should humans stay in the loop?
  • How will success be measured?
  • Which workflows need to change before AI can create real value?

AI literacy is becoming part of leadership credibility. The companies that build it early will be better positioned to turn AI from scattered experimentation into a practical advantage across sales, marketing, customer experience, and operations.

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