How To Turn AI Potential into Performance for Modern Marketing Teams
Marketing leaders turn AI potential into performance when every initiative ties to real business value, supports people through change, and reinforces a culture that knows how to adopt new ways of working. This perspective shaped a recent conversation on “The Campaign”, the 97th Floor podcast, hosted by my friend and their CEO, Paxton Grey. By Aby Varma from Spark Novus.
AI is no longer a side experiment. Most marketing teams have already used large language models, testing prompts, tools, and early workflows. Yet many still struggle to convert early curiosity into durable capability. That gap rarely comes from the technology. It comes from the questions leaders ask, the priorities they set, and how they support their people as their work evolves.
The discussion with Paxton revealed a pattern across organizations. AI becomes impactful when leaders shift the narrative away from tools and toward purpose. This article distills that conversation into the principles and mindset shifts that help marketing teams turn possibility into performance.
What It Really Means To Turn AI Potential into Performance
Turning AI potential into performance means achieving outcomes that matter. Not faster production for its own sake, but clarity in what the organization is trying to accomplish. That includes:
Building pipeline in new markets
Improving retention and customer lifetime value
Reducing time spent on manual work so teams have more space for creative and strategic thinking
Making insights accessible to everyone, not just analysts
When AI is not anchored in these outcomes, teams end up with disconnected pilots and inflated content volume that does little to shift results.
Why “Can AI Do This” Is the Wrong First Question
The most common question leaders ask is “Can AI do this” which accidentally casts the technology as the story’s protagonist. The more useful question is “What can we do with AI” which centers people and outcomes instead of tools.
This shift moves attention to:
The marketer or analyst who owns the workflow
The business objective behind the task
The opportunity to redesign how value is created
AI becomes a collaborator. Human judgment shapes direction. Human intuition verifies quality. The work becomes a human to AI to human loop that strengthens both speed and rigor.
How CMOs Should Select AI Use Cases That Truly Matter
Choosing the right use cases begins with defining a strategic north star grounded in pain points or opportunities.
Pain points often include:
Slow planning and production cycles
Difficulty finding assets or institutional knowledge
Fragmented customer experiences
Opportunities include:
Entering a new vertical
Strengthening demand generation
Improving personalization at scale
In the conversation, one enterprise team considered two AI projects. One focused on re organizing years of digital assets. The other focused on supporting cold prospecting for a new vertical. Both were valuable. Only one had immediate impact on pipeline growth.
By ranking each use case by relative business value, the team focused first on demand generation and saved the asset work for a later cycle. Strategy guided sequencing. AI supported the priorities rather than setting them.
Why People and Culture Determine Whether AI Sticks
Technology does not create adoption. People do. Most marketers have already experimented with AI individually. Moving from individual experimentation to organizational capability requires:
A culture that encourages testing and tolerates thoughtful risk
Clear guidelines for acceptable use and brand safety
Training programs that match the pace of change
Leadership communication that reduces uncertainty
Change management is the most overlooked part of AI adoption. Surveys consistently show that the biggest barrier is not the technology. It is knowledge, clarity, and confidence.
The Emotional Realities Leaders Must Acknowledge
AI lands differently across an organization. Patterns often look like this:
Middle managers worry about staying relevant in a rapidly evolving landscape
Senior leaders feel pressure to define an AI infused strategy without full clarity • Early career professionals want structured training and clearer guardrails • Everyone wants to do the right thing but does not always know what “right” looks like
Leaders who acknowledge these realities create the psychological safety necessary for adoption to accelerate.
How Leaders Encourage Adoption Even When Tools Change Fast
The pace of AI innovation makes hesitation understandable. Instead of anchoring learning in specific tools, leaders can help teams build durable capabilities:
Structured prompting habits
Critical evaluation and verification of outputs
Ability to integrate AI into workflow steps
Comfort with iteration and ambiguity
These skills endure even as models evolve.
The Mindset Shifts That Turn AI Into Real Performance
The conversation landed on four shifts that help marketing teams move from experimentation to meaningful value.
Shift #1: From “Can AI do this” to “What can we do with AI”
Shift #2: From outputs to outcomes
Shift #3: Toward reclaiming time to think, imagine, lead, and inspire
Shift #4: Toward embracing ideas the team would never have considered without AI
These shifts allow teams to see AI not as a shortcut, but as a catalyst for deeper thinking and higher value work.
Rethinking How Teams Access and Use Data
In some cases, AI will accelerate existing workflows. In others, it will change them entirely. One analytics team initially wanted AI to speed up the path from data pipelines to dashboards. When they reframed the problem, a better solution emerged: a conversational interface that allowed marketers to ask direct questions and receive insights instantly.
The lesson is simple. Improve existing processes where it makes sense, but stay open to redesigning the work altogether.
Practical First Steps for Individual Marketers
A grounded way to begin includes:
Identify one workflow you own
Define the outcome you want to improve
Insert AI into a small part of that workflow
Keep yourself in the loop to review and refine
Share what you learn
Consistent practice builds confidence. Confidence builds capability.
Why Community Matters
AI adoption accelerates when marketers learn from other practitioners. Communities surface patterns, reveal blind spots, and offer encouragement during periods of uncertainty. Collective learning amplifies individual progress.
Ready to Turn AI Potential into Performance
Many marketing teams are experimenting with AI but still struggle to translate that activity into measurable business outcomes. Spark Novus works with marketing leaders to clarify priorities, identify high impact use cases, and design practical pilots that support people, process, and culture. The focus is not more tools, but better decisions and durable capability.
Let’s talk about how Spark Novus can support your AI goals across your marketing team.
