Council Post: Why Marketing Teams Should Appoint An 'AI Quarterback'

Anna Convery is CMO at Verint, a leader in CX Automation serving customers worldwide, including more than 80 of the Fortune 100 companies.

Marketing teams have moved quickly to adopt AI -- some so quickly that the result is myriad tools, unclear return on investment and inconsistent results.

My team has been using AI tactically to create content and execute campaigns. However, it wasn't integrated, experimentation was siloed, and learnings weren't being shared broadly. And, as AI token cost concerns started to factor prominently, I, like many marketers, wanted to get a lock on the ROI and the long-term financial implications of our AI usage.

Without a single owner, AI initiatives tend to stall, be project-responsive, lack accountability or remain siloed. Deploying new tech is easy; getting people on the same page is often way harder.

I'm not the only one who holds this belief. According to McKinsey's State of Organizations 2026, based on a survey of more than 10,000 senior executives, 86% of leaders believe their organizations are not prepared to integrate AI into day-to-day operations.

This is why I appointed an AI quarterback, a purpose-built role with oversight over AI strategy, tool sets and change management within marketing.

The AI quarterback works across functions such as demand gen, content, operations, digital, analytics and CX and helps translate technical capabilities into business outcomes. The role also coordinates with external teams like AI, legal and others across the company.

Five Focus Areas

Below is an AI quarterback playbook that marketers can adopt. The role has a broad remit, but it's focused on five areas:

1. Reining In Tool Sprawl

When team members independently adopt their own tooling, outputs are inconsistent across the organization.

AI quarterbacks should evaluate the stack, ensure the number of licenses is warranted and help determine which tools to standardize on, prioritizing cost, interoperability and alignment with broader martech investments.

2. Defining Success Metrics

Many AI initiatives lack KPIs that tie to business outcomes.

An AI quarterback should determine what success looks like. For example, can we connect metrics such as shorter customer support call times and content productivity to tangible impacts on revenue, customer satisfaction, increased conversion rates and brand equity?

3. Scaling Innovation

At my company, we ask marketers to spend one hour a week focusing on AI -- whether it's training, exploring new use cases or thinking differently about their role and impact.

AI quarterbacks should guide purposeful experimentation, elevating and scaling what works across the function. This ensures AI innovation is leveled up so that great use cases are identified and replicated.

4. Facilitating Change Management And Workforce Enablement

AI is changing marketing roles, and many are worried about their jobs.

A big part of the AI quarterback's role is setting the agenda for AI upskilling and training, based on the tools and success metrics previously established, and determining where AI augments or replaces tasks and/or where roles need to be redefined.

Clearly defined pathways to build the right skills and a transparent plan around how roles will evolve can ease fears and empower employees to embrace AI, rather than fear it.

5. Quantifying AI impact

CMOs aspire to drive revenue and brand equity, and to make the company more competitive. An AI quarterback can help measure and report on AI initiatives and impact in these areas.

Winning Attributes Of An AI Quarterback

The first step in our AI quarterback's approach is to identify high-frequency, rote tasks that can be automated.

Second, the quarterback defines and documents the data plumbing, skills and agents so that anyone in the department can confidently get valid outputs.

Finally, the quarterback disseminates these capabilities to the team, evaluates improvement and iterates as needed.

AI quarterbacks don't need great technical skills. What they do need are cross-functional visibility, change management expertise and a high-level understanding of strategic marketing priorities.

Just as important is strong marketing domain expertise, because knowing where AI fits in the workflow is what turns experimentation into measurable impact. The best AI leaders can identify the use cases that matter most to marketers and apply AI where it can improve speed, quality and business outcomes.

Based on where we've seen value from this position, look for someone who is enthused about AI and a "power user." It's essential for this individual to have a marketing operations background. Finally, the quarterback should be a leader who is respected across the team.

Ushering In A New Era

AI quarterbacks are crucial to ushering in the next era of marketing, which requires a disciplined, logical strategy for where we use AI, where we don't and what results we can expect.

The key to AI success isn't about adopting the technology -- it's about putting in place the right ownership, governance, metrics and accountability.

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