Marketers are used to overcoming challenges. It’s part of the job description — always-changing algorithms, the ebb and flow of new platforms and tools, and now artificial intelligence. While AI might seem like marketers’ most complex challenge yet, with the right strategy, it’s just another routine obstacle — and one you can actually tame in your favor.
While more than three-quarters of executives use generative AI several times a week, regular usage among frontline marketers stalls at just over half, according to BCG’s global AI at Work survey. Leadership enthusiasm alone isn’t enough if day-to-day workflows and skills don’t align.
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What Are Common Barriers to AI Adoption in Marketing?
Before you can fix a problem, you have to know what you’re trying to solve. These five common obstacles are cardinal culprits behind stalled or unoptimized AI initiatives:
- Lack of education and training.
- Absence of a clear AI strategy and governance.
- Fragmented workflows and tool overload.
- Uncertainty about AI ROI.
- Organizational readiness and change resistance.
Ignoring even one of these hurdles can throttle ROI, slow time-to-value and erode internal confidence in AI. Best practice is to address them systematically to unlock faster speed to market, sharper insights and sustainable competitive advantage.
1. Lack of Education and Training
When teams don’t know how to wield new technology, even the best tools gather digital dust. 68% of marketers say that their companies aren’t providing any functional AI training, according to the 2025 State of Marketing AI Report, positioning it among the top barriers to adoption.
There are many ways to implement AI training, from lunch-and-learns to more formal seminars. The right approach will vary between businesses, but one thing should be consistent: Tie small, low-risk AI training experiments to real campaigns so marketers can get a feel for what it’ll really be like to use the tool.
With training up and running, consider setting up a dedicated AI messaging channel on whichever platform you use to encourage knowledge sharing.
Of course, skills alone won’t carry the day if there’s no larger plan for how AI will serve the business.
2. Absence of a Clear AI Strategy and Governance
Operating without an AI road map can only result in unclear milestones and obscured goals. Most marketing teams still lack a documented AI plan, and many have yet to establish ethics guidelines or an AI council. These gaps become easy to trip on when you’re running for scale and consistency.
To build your future-proof AI strategy, start by:
- Forming a cross-functional AI council to set vision, policies and success metrics.
- Auditing current workflows to pinpoint AI opportunities with the greatest potential impact.
- Defining use-case-specific KPIs (e.g., reduced production time, lift in conversion rates) linked to revenue goals.
- Drafting clear generative AI and data-ethics guidelines to safeguard brand integrity and customer trust.
- Revisiting the road map quarterly to align with evolving tech and shifting market priorities.
Even the best plans falter if your stack can’t support it. Enter the thorny issue of legacy integrations.
3. Fragmented Workflows and Tool Overload
There are tons of AI tools out there — many convenient, but not really designed specifically for marketers. When they are, they typically specialize in one or two use cases, leaving those looking for a well-rounded option out to dry. That invariably leads to tool overload and fragmented workflows.
So, prioritize platforms that integrate seamlessly with many daily marketing workflows — ideating, brainstorming, writing, editing, optimizing and more — to streamline things from end-to-end. Ideally, your platform can be a shared ideation and creation environment that multiple stakeholders can access, contribute to and align around.
Once systems and workflows are humming, and leadership inevitably asks, “So, what’s the return?,” you’ll feel much more prepared to provide an answer.
4. Uncertainty About AI ROI
Many marketers find it tricky to quantify AI’s payoff, especially when benefits span time savings, error reduction and capacity gains.
To begin nailing your numbers:
- Calculate time saved: Multiply weekly hours saved by the fully loaded hourly rate, annualized.
- Measure error reduction: Track pre- and post-implementation mistakes, then assign a cost per error.
- Estimate capacity gains: Quantify additional projects or campaigns delivered without new headcount.
- Account for speed to value: Faster turnaround often boosts revenue and customer satisfaction.
Look at these metrics collectively, and you’ll start to form a narrative that leadership can rally around: AI isn’t just a convenience tool, but a measurable operational engine. Analysis grounded in real numbers across time, quality and capacity turns AI from a “nice-to-have” into a provable business driver.
Hard numbers always help, but adoption can still stall if cultural buy-in lags.
5. Organizational Readiness and Change Resistance
Even with budgets and blueprints in place, skepticism stalls progress. BCG notes that frontline usage of GenAI creeps up from 51% to 55% when leaders offer consistent support. That small jump can represent a lot for adoption readiness, yet only a quarter of employees feel they receive such support, which underscores how culture can support AI success.
Create an adoption-friendly culture by:
- Having executives champion AI wins in town halls and internal messaging apps.
- Linking AI projects to clear career-growth and customer-impact stories.
- Embedding continuous learning time into weekly routines rather than one-off workshops.
Taken together, these actions signal that AI isn’t a passing experiment but a priority backed by leadership. When employees see consistent encouragement and clear incentives, and have space to learn, they might be more willing to engage.
Even with an optimistic culture, every AI journey benefits from a few guardrails that instill confidence inside and outside the organization.
Start Your AI-Driven Marketing Transformation
Closing the gap between AI ambition and everyday impact demands not just great tools that slot naturally into a marketer’s workflow — like contentmarketing.ai — but effective training to help everyone make the most of them.
Armed with the right platform and a clear roadmap, you can shift focus from battling hurdles to amplifying creative, data-driven marketing wins.
Every challenge outlined in this guide shares a common thread: each one is solvable when people, process and technology pull in the same direction. The sooner you tackle these barriers, the faster you’ll unlock the creative capacity and competitive agility that modern marketing demands.
The next wave of marketing innovation is already here.
This article was created with help from contentmarketing.ai, and edited and proofread by Chad Hetherington and other members of the Brafton team.
