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The last few years have been an AI-powered rollercoaster ride for marketers. When ChatGPT burst onto the scene a couple of years ago, it put AI on a hype cycle climb that seemingly had no peak. The rush to AI-ify all the things in marketing SaaS was on. Marketers of every stripe were quickly pushed by leadership (and the fear of looking like an unemployable luddite) to experiment with every AI tool and LLM use case that came their way.
Now, the gut-dropping, 100-mile-per-hour decent at the end of the coaster climb has arrived, with marketing leaders increasing velocity to end the ride with a stack of AI tools and use cases that deliver on their ROI promises.
AI strategy now requires clear leadership to prevent budget-burning AI boondoggles, so CMOs and marketing executives must take the helm to keep the ride on track and up to speed. These five reasons for taking ownership of your strategy can help you make it a smoother ride.
Turning the frenzy of AI experimentation into results-driven action requires clear leadership. This isn’t just another “you have to do the AI to be a good CMO” thing—it’s actually expected. We found that over 90% of marketers say it’s important to have clear ownership of AI initiatives In our latest State of AI in B2C Digital Marketing Report. This is where marketing leaders’ ears need to perk up.
In last year’s report, there was no consensus about who owned marketing AI initiatives, and only 18% said executives were responsible for AI. This year, AI is clearly in the hands of CMOs and other executives, as nearly 40% said they should be responsible for AI adoption.
To successfully shift from a “What can you do with it?” approach to AI to a “What results can we get?” strategy, marketing leadership must take a more directive approach to AI adoption and ensure that quantifiable goals are used to prove the effectiveness of every use case.
While leadership direction on AI strategy is desired and required, putting the kibosh on innovation is the last thing you want. Continue to encourage your team to research and experiment with AI martech. However, it should now be expected that they are developing a hypothesis, KPIs, and goals ahead of time to set expectations for what the tool should do and what the ROI is.
It’s up to the CMO to establish these kinds of guardrails to prevent using (and paying for) AI for AI’s sake.
While you need to drive the strategy, be mindful that facing a push from leadership to simply “do more with AI” is incredibly overwhelming for individuals and teams. A careful approach should be taken to give clear direction and goals without micromanaging to the point of crushing the innovative spirit. AI is everywhere but still nascent in many use cases, so the ability to experiment—and fail—has to continue.
However, to realize failure has occurred, a strategy and KPIs must exist to provide guardrails and exit ramps. It’s up to marketing leaders to work with their teams to establish what is expected from AI tools, whether that’s increased productivity, an ROI target, or contribution to boosting other marketing KPIs like pipeline and revenue.
The CMO should be the one who best understands the overarching business goals and how marketing contributes to them. Not to mention that they are ultimately responsible for achieving said goals.
Executive ownership of the AI strategy ensures that investments and initiatives align directly with revenue growth, customer experience improvement, brand awareness, or whatever your organization's goals are. Without this alignment, there’s a risk of fragmented or misaligned AI use cases that fail to drive meaningful results and waste your precious budget.
Each tool and use case is different, so a universal KPI edict for AI won’t work. The most effective thing for marketing execs to do is to push their teams away from the shiny objects that deliver squishy results to the ones that can be measured with dollars and cents. Look for AI tools that can help drive revenue growth, spend ad budgets more efficiently, increase conversions, or otherwise contribute to the bottom line. Make sure your team has this top-of-mind when vetting new AI tech.
Investing in AI can be one of the most transformative decisions a marketing leader makes—but only if the focus stays on driving real business impact. As a CMO, it’s easy to get caught up in the hype around AI-powered tools promising efficiency gains or operational automation. However, to truly move the needle on revenue, marketing leaders need to anchor their AI strategy in areas that directly fuel customer acquisition, retention, and overall business growth.
Consider lead generation, one of the most critical drivers of revenue. AI excels at surfacing potential customers through predictive modeling, intent analysis, and automated optimization. These capabilities allow marketing teams to scale their outreach, identify high-value leads faster, and create a more predictable pipeline. But deploying AI for improving lead generation isn’t just about using the latest tech—it’s about ensuring that marketing efforts focus on the right prospects at the right time, multiplying the team’s impact without ballooning budgets.
Owning the AI strategy means more than just selecting the right tools—it’s about ensuring that every AI investment is tied to business outcomes that matter. A CMO’s leadership ensures AI becomes a true growth driver, creating a marketing organization that isn’t just efficient, but also agile, scalable, and relentlessly focused on driving revenue. This strategic ownership helps marketing move beyond campaign management to become a core business growth engine.
Your customer’s buying journey—and your job—doesn’t end with lead and pipeline creation. If sales don’t happen, customers aren’t happy, and sustainable revenue growth isn’t generated, it’s all for naught.
The challenge for CMOs is that marketing bridges functions across sales, eCommerce, customer experience, and even offline channels like the contact center. This is why marketing needs to treat cross-functional teams like these as stakeholders and even users in their AI adoption strategies. It’s an opportunity to break down silos, find more opportunities for collaboration, and create a shared language of success.
The CMO can ensure AI solutions integrate seamlessly across teams and prevent siloed adoption of AI tools that might undermine broader strategic efforts.
It’s easy to get blinded by all of the AI excitement and disregard the potential risks that adopting a bunch of new AI tools brings. As AI becomes deeply embedded in your processes, ethical implementation, brand safety, and data security need to be a clearly documented piece of your strategy. In fact, data security was cited as the #1 roadblock to AI adoption in our recent State of AI report for two consecutive years.
Is this the most exciting part of doing new things with AI? Not by a longshot. Is it the most important? If you’d like to keep your job, it could well be.
Partnership with IT, security, and legal teams is critical, as they are often responsible for implementing technical controls and maintaining compliance standards. Marketing leaders should collaborate closely with these teams to ensure that AI marketing tools comply with data protection laws (e.g., GDPR, CCPA) and industry best practices.
Hopefully, your legal and security teams can do most of the heavy lifting documenting all that fun stuff, but it’s up to marketing leadership to ensure everyone is aware of the standards you set and validate them with potential AI vendors.
This is one of the most exciting parts of our AI-powered future and the most crucial point to create a strategy that ensures your team’s future success. There will still be fits and starts and a lot of sudden turns, so buckle up and hang on for the ride!
Get the State of AI in B2C Digital Marketing to learn more about how marketers are feeling about AI.
