Who “Owns” AI In a Company? #LeadAi

I recently sat down with Courtney Baker for a fascinating discussion about one of the most pressing questions facing businesses today: who should own AI within an organization?

As companies scramble to implement artificial intelligence, there’s widespread confusion about where this responsibility should land. Should it be IT? The CIO? Should every department manage their own AI initiatives? Or do we need an entirely new position like Chief AI Officer?

The answer, it turns out, is more nuanced than you might think.

Why AI Isn’t Just Another Technology Project

One of the first misconceptions Courtney highlighted is the tendency to view AI as primarily a technology problem. As she pointed out:

“A lot of perceptions are that AI is a technology project, problem, whatever your standpoint on AI is. But I started thinking about analogies for that. Is it like when the Internet was created, being like, ‘Okay, technology, that’s your thing’? But that doesn’t work for this case.”

Courtney compared it instead to remote work. While remote work definitely requires technology, no one would suggest making the IT department solely responsible for managing it. Remote work fundamentally changes how teams collaborate, communicate, and operate – impacting every aspect of company culture.

AI is similar but even more pervasive. It’s not just a new tool; it’s a transformative force that will touch every department, function, and process in your organization.

The Current State: Everyone Owns Their Own AI

Right now, most organizations are in what I’d call the “decentralized phase” of AI adoption. Department leaders are figuring out how to implement AI within their own teams:

• Sales leaders are looking at AI for prospecting and conversation intelligence
• Marketing teams are experimenting with content generation and analytics
• Finance departments are exploring forecasting and fraud detection
• HR is testing recruitment and employee experience applications

This makes sense in the early stages. As Courtney put it: “I think we should all have the mentality that ‘I need to be learning this technology as if I am going to be the one in charge of it.'”

But as AI becomes more deeply integrated into company operations, this decentralized approach will create challenges – from duplicated efforts to inconsistent implementations and security concerns.

The Case for Centralized Leadership

As our conversation progressed, it became increasingly clear that while everyone needs to be involved in AI adoption, there’s also a need for centralized coordination.

I initially leaned toward the CIO (Chief Information Officer) as the natural owner, and here’s why: the secret sauce of effective AI isn’t just the algorithms – it’s the data.

Organizations that will gain competitive advantage through AI are those that can effectively:

1. Centralize and clean their data
2. Create systems for departments to access this data through AI
3. Establish governance for how AI is implemented across the organization

These responsibilities align naturally with the information management role of a CIO. The more I work with custom GPTs and other AI tools, the more I realize that the differentiator isn’t the model itself – it’s the proprietary knowledge and data you feed into it.

The Leadership Gap Courtney Identified

Courtney raised an important caveat to the CIO-ownership model: the change management component.

“My one caveat with that is the change management, the actual rallying of people to leverage the technology in the organization. Certainly, I’m sure there are CIOs out there that have that skill set. I don’t know how many there are.”

This highlights what might be the biggest challenge with AI implementation – it’s not just a technical challenge but a human one. AI requires organizations to rethink processes, roles, and even business models.

The ideal AI leader needs a rare combination of:

• Technical understanding of AI capabilities and limitations
• Strategic vision to see how AI could transform the business
• Change management expertise to guide the organization through transformation
• Ethics and governance understanding to implement AI responsibly

As Courtney noted, “The skill set that we’re looking for feels a little bit like a unicorn.”

Why Marketers Should Lead the AI Charge

Here’s where things get interesting for marketers. Both Courtney and I believe that marketing departments are uniquely positioned to lead organizational AI adoption, even if they don’t “own” it entirely.

Why? Several reasons:

1. Marketers are natural early adopters

As Courtney put it: “Marketers, I have almost always found, are forward thinking. That is the unique seat that we hold in the organization.”

When ChatGPT launched, who were the first to experiment with it? Marketers looking for content creation efficiencies. This willingness to embrace new technologies makes marketers natural pioneers.

2. Marketing can demonstrate clear ROI

Courtney made an excellent point near the end of our conversation: “Anytime you can put revenue dollars behind a project, you’re more likely to get it going faster.”

Marketing can easily demonstrate the business impact of AI implementations through improved conversion rates, increased content production, better targeting, and ultimately, revenue growth. This makes it easier to build organizational support.

3. Marketing sits at the intersection of technology and people

Successful AI implementation requires both technical understanding and human empathy. Marketers typically have both – they’re comfortable with technology while also understanding human behavior and organizational change.

A Dual Approach: Bottom-Up and Top-Down

Throughout our conversation, it became clear that successful AI adoption requires both bottom-up experimentation and top-down coordination.

“This is a really unique moment where the bottom up can be speaking into it and really leveraging how important this is for there to be a top down response and a real strategic emphasis on how it’s deployed in the organization,” Courtney noted.

Here’s what this dual approach looks like in practice:

Bottom-Up: Individual Experimentation

Smart marketing leaders are already:

• Creating KPIs around AI tool experimentation for team members
• Discussing AI applications in one-on-ones
• Upgrading to team versions of tools like ChatGPT to share custom GPTs
• Building use cases that can inspire other departments

Courtney shared a great example: “I recently talked to an executive who literally has their team using their KPIs on how are they leveraging AI, which new tool have they experimented with.”

Top-Down: CEO-Led Vision

While department leaders can drive AI in their areas, truly transformative implementation requires CEO support:

• Setting the strategic vision for how AI will transform the business
• Allocating resources for company-wide AI initiatives
• Establishing ethical guidelines and governance
• Creating cross-functional collaboration structures

As I mentioned in our conversation: “If it’s going to impact the whole company that you’re a part of, there’s only one champion – it’s the CEO.”

The Warning We Both Share

Courtney and I both expressed concern about one particular scenario: executives making decisions about AI without actually using the tools themselves.

“I have a slight concern that executives aren’t actually using these tools enough,” Courtney shared. “One of my concerns is an over-index on what AI can actually do and replace.”

She gave the example of an executive who might think, “We don’t need marketing copywriters anymore. ChatGPT can be our copywriter,” without having enough hands-on experience to understand the limitations.

I agree completely. In fact, one of my 2024 predictions is that several major companies will take big swings with AI implementation, lay off workers prematurely, and fail miserably as a result.

Pete Buer, Chief Strategy Officer at Knownwell, goes even further – predicting that 90% of enterprise AI projects will fail due to inadequate change management.

Your AI Leadership Action Plan

If you’re a marketing leader, here’s how to position yourself and your team at the forefront of AI transformation:

1. Start with your team: Establish clear expectations that everyone should be experimenting with AI tools relevant to their role
2. Document success stories: Create case studies of how AI has improved marketing outcomes – with specific metrics and ROI calculations
3. Build cross-departmental bridges: Initiate conversations with sales, IT, and other departments about shared AI opportunities
4. Advocate for centralized leadership: Use your success stories to make the case for organized, company-wide AI strategy
5. Be the change management expert: Position yourself as someone who understands not just the technology, but how to help people adapt to it

As Courtney summarized perfectly: “This is our moment. It’s your moment. So let’s go do it.”

The companies that thrive in the AI era won’t necessarily be those with the most advanced technology – they’ll be the ones that implement it most effectively throughout their organization. And marketers have a unique opportunity to lead that charge.

If you’re interested in learning more about implementing AI marketing strategies in your business, I’d love to hear about your experiences and challenges.