Editorial
Case Study
Why So Many Digital Modernization Efforts Stall
The Gist
- AI use is spreading faster than policy. Employees are already bringing AI into marketing workflows on their own, creating a gap between adoption and organizational visibility.
- Guardrails and fluency must grow together. Marketing leaders need clear standards, approved tools and ongoing training so teams can use AI responsibly, consistently and in line with business goals.
- AI belongs in strategy, not just execution. Beyond speeding up copy and reporting, AI can help marketing leaders improve segmentation, audience prioritization and campaign investment decisions.
AI adoption in marketing isn't coming—it's already here. While part of this shift has been driven by the significant investments organizations have made to bring AI into the center of their business strategies, it's also being fueled by employees' own curiosity and initiative.
Data from Slingshot's Digital Work Trends Report, shows that 87% of employees use AI voluntarily, even though only 28% of companies require it. This gap tells us something important: AI use is being driven from the ground up.
Marketing teams are using AI to draft campaign copy, analyze customer data, refine messaging and speed up go-to-market timelines. In many organizations, AI is already embedded in daily marketing workflows. But when that happens quietly, leaders don't have the visibility into how it's being used or whether it's aligned with brand, compliance and business goals.
Here's how marketing leaders can turn their scattered AI experimentation into a more coordinated, measurable part of their marketing strategy.
Table of Contents
- 1. Create Clear AI Standards for Marketing Teams
- 2. Make AI Fluency Part of the Marketing Skill Set
- 3. Elevate AI From A Productivity Tool to Strategic Partner
- Tying AI to Real Marketing Outcomes
1. Create Clear AI Standards for Marketing Teams
Just as marketers have to operate within guardrails—brand standards, content frameworks and approval workflows that protect consistency—AI should operate within that same structure.
Yet in many organizations, it doesn't. Nearly half of employees (45%) don't disclose their AI use at work, which means AI may be influencing content, campaigns and customer communications without leadership having full visibility into how it's being applied. Without that visibility, leaders can't measure impact or understand how AI is influencing campaign performance and pipeline outcomes.
Plus, when AI is used without defined standards, messaging can drift off-brand, data practices can become inconsistent and compliance risks increase. One team member might use AI responsibly to refine campaign copy, while another uploads sensitive data into an unapproved tool or publishes AI-generated material without review. Over time, that lack of coordination can ruin brand consistency, weaken compliance and undermine trust.
Organizations need clear guidance for AI in marketing. This can include everything from defining approved tools and setting data boundaries to transparent review processes so that employees aren't left guessing what's acceptable. With these policies in place, marketers can use AI transparently and confidently—and organizations can ensure its use remains ethical, secure and aligned with business goals.
Related Article: The Maze of AI in Marketing: What Should We Do First?
2. Make AI Fluency Part of the Marketing Skill Set
Once guardrails are in place, the next step is to build upon the skills to use them effectively. As new AI platforms enter the market, many organizations focus on implementation, like integrating tools, piloting use cases and expanding access across departments. But access alone doesn't create impact. Successful adoption requires teaching teams how to integrate AI into everyday workflows in a way that improves execution and supports business outcomes.
Employees are ready for that shift, with 66% of employees saying they're interested in experimenting and innovating with AI. What's often missing is when and how to use AI responsibly, and where it truly adds value.
AI fluency should be treated like any other core marketing competency and embedded into onboarding for marketing hires and reinforced through ongoing skill development, similar to when there are changes to brand or compliance standards. Teams should have room to test, learn and improve their skills, but within defined expectations that protect messaging consistency, data integrity and performance standards.
Most importantly, marketing leaders need to clearly define AI's role within the function: how it supports campaign goals, where a human-in-the-loop is required to guide and validate outputs and what responsible use looks like in practice. In doing so, this will create alignment, reduce uncertainty and encourage disciplined experimentation across teams.
Related Article: 15 Marketing Certifications That Can Help You Earn a Better Salary
3. Elevate AI From A Productivity Tool to Strategic Partner
In many marketing organizations, AI conversations still center on productivity—writing subject lines faster, repurposing blog posts or automating routine reporting. Those use cases matter and can drive meaningful efficiency gains, but they represent only a fraction of what marketers can truly do with AI.
According to the Digital Work Trends Report, most employees rely on AI to check or improve their work (54%) or draft emails and other written content (52%). But, AI can be used on a much higher level. We are already seeing this from company leaders who apply AI more strategically, using it to analyze business and team data (56%), conduct research (52%) and manage team priorities (47%).
The difference isn't capability. It's the mindset.
When marketing teams limit AI to task-level productivity, they risk missing its broader impact on segmentation, positioning, budget allocation and campaign strategy. In order to guide teams on how to uplevel their AI usage, marketing leaders should actively showcase examples of where AI can shape larger business decisions such as where to invest, how to prioritize audiences and how to optimize campaign mix—all decisions that directly impact revenue performance.
To shift that mindset, leaders must model strategic usage, like sharing examples of how AI influenced campaign direction, surfaced audience insights or shaped spend allocation. From there, role-specific training can build on those examples, moving teams beyond basic prompts to deeper analytical and creative applications. When leaders openly demonstrate how they're using AI to guide decisions, it reinforces responsible experimentation and AI's use as a strategic tool embedded across marketing—not just a shortcut for faster output.
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How Marketing Teams Should Be Using AI
These practical focus areas summarize how marketing leaders can move AI from scattered experimentation to coordinated, strategic use across the marketing organization.
| AI Focus Area | What Marketers Should Do | Business Impact |
|---|---|---|
| Establish AI Standards | Define approved tools, data usage rules and review processes so AI-generated work follows brand, legal and compliance guidelines. | Protects brand consistency and reduces compliance risk while improving leadership visibility into AI usage. |
| Build AI Fluency | Train marketing teams to integrate AI into daily workflows through onboarding, role-based training and ongoing experimentation. | Improves productivity and ensures teams use AI responsibly and effectively. |
| Integrate AI Into Campaign Development | Use AI to analyze customer data, refine messaging, test creative variations and accelerate go-to-market timelines. | Creates more responsive campaigns and faster marketing execution. |
| Apply AI to Strategic Decision-Making | Leverage AI for audience segmentation, performance analysis, research and marketing planning. | Helps leaders prioritize investments and improve marketing ROI. |
| Promote Transparent AI Usage | Encourage teams to openly disclose how AI is used in content creation, analysis and campaign planning. | Improves organizational alignment and allows leaders to measure AI’s true business impact. |
| Model Strategic AI Leadership | Marketing leaders should demonstrate how AI informs campaign strategy, audience insights and budget allocation. | Shifts AI from a productivity shortcut to a strategic capability embedded in marketing operations. |
Tying AI to Real Marketing Outcomes
AI is already shaping marketing workflows, from content creation to campaign strategy. It's now up to companies to ensure its use is aligned, transparent and tied to real marketing outcomes. With clear guardrails and stronger AI fluency, marketing leaders can turn quiet and scattered use into a coordinated approach that drives performance, protects the brand and delivers measurable impact.
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