Over the last two years, AI has continued to have a profound impact on the CMO role, in particular on those managing multi-channel in-house teams.
For many marketing leaders, the mandate from CEOs and CFOs has been clear: use AI to deliver more efficiency, lower costs, and better bottom line results.
With the “honeymoon phase” of AI experimentation largely over, the expectation is that CMOs should now be delivering on that mandate. But is that a truly reasonable expectation, and if not, what can CMOs do to make successful AI integration a reality?
As a leading independent agency working closely with CMOs, CEOs, and CFOs, we’ve seen and managed this challenge from both perspectives. Below, we’ve shared some of the biggest challenges we know CMOs are facing along with practical advice in tackling those challenges as AI continues to evolve.
Board-level expectations don’t always align with the reality
Business leaders are flooded with promises of AI saving time, cutting costs, and delivering instant, transformational outcomes, often translating to increased pressure on CMOs to deliver fast bottom-line results. The reality is, within the marketing department, AI mastery goes far beyond onboarding the latest tool, shrinking operational costs, or securing quick wins.
Since day one, the priority around AI has been about operating at the speed of change. In 2025 alone, organic performance was re-written, with the rise of AI-based search and the zero-click phenomenon. Paid Search was led by algorithms. High velocity creative became a primary ROI lever. New capabilities, products, and redefined best practices have also come at an unrelenting pace from platforms like Google, Meta, TikTok, Amazon, and OpenAI. CMOs have had to completely redesign their strategies, onboard and master new channels, and redefine the metrics that matter, all while the ground shifts beneath their feet.
Beyond just the tools they use, the core foundations of the CMO role has undergone a rapid and significant evolution. Marketers will know that success isn’t solely about cutting operational costs through AI. It’s about evolving their strategies along with it to protect performance and revenue and ensure lasting effectiveness.
There is a real AI readiness gap
While 70% of CMOs say becoming an AI leader is a critical goal, Gartner data states that only 30% say their teams are actually ready to scale AI capabilities.
In practice, ‘readiness’ spans everything from basic prompting skills to far more serious matters around responsible use (data compliance, intellectual property, GDPR, etc), all of which require proper training and governance.
The reality is that only 25% of large UK businesses having strict, comprehensive governance frameworks around AI (YouGov), meaning many CMOs lack the support of a business-wide AI strategy, with robust data guardrails, adequate training, and access to enterprise level AI solutions that are designed for business usage.
Shadow AI, where staff use unapproved, non-enterprise accounts for their work, is also a challenge for CMOs to manage. Microsoft UK’s Workforce Report found that 71% of employees admit to using AI in this way, citing Media and Marketing amongst the highest risk departments.
With access to first-party customer data, business performance metrics, and as a department responsible for building brand trust, the AI readiness gap not only poses risks for CMOs and the businesses they work in, but also limits what they can realistically control and deliver against the AI integration mandate.
AI is eating into the marketing budget
According to Gartner’s 2026 CMO Spend Survey, global marketing budgets have remained relatively flat, with business leaders actively expecting efficiency gains to come from AI usage. Gartner also states that 56% of CMOs say their budgets will be cut if they miss their annual goals.
So the challenge is to ultimately do more with less. To shift budget into new and emerging channels, requiring new tools to track performance, new skills and training to execute, and investment in new AI tools to do it all faster, but somehow at a lower cost.
This is why CMOs state that 15.3% of their total budgets are going into AI initiatives (Gartner), effectively forcing a cannibalisation of other marketing operations to fund AI. Given that many CMOs lack the necessary structure, strategic support and investment from their organisations around AI integration, delivering ROI against these AI investments becomes incredibly challenging.
A lack of data maturity creates a growth ceiling
Gartner shows that only 30% of enterprise organisations possess the necessary, fully developed data foundations that CMOs need in order to properly scale AI and prove its effectiveness. Tredence also noted that 60% of enterprise AI initiatives collapse at the pilot stage due to a lack of AI-ready data foundations.
As an example, a report from SalesForce cited that 98% of AI users are hitting at least one data barrier to personalisation, ultimately limiting their ability to provide the necessary targeting and hyper-personalised marketing the algorithmic era demands. Supermetrics also noted that 52% of data strategies are held outside marketing.
CMOs will know that AI is only as good as the data it can access, but without a single source of truth to work from, it is unlikely their teams and AI counterparts will be able to deliver, even with flawless execution.
Practical advice for CMOs
Whether all of some of these challenges resonate with CMOs and marketing leaders, our goal here is to acknowledge the very real pressures they face while providing practical advice on how to tackle them:
Tip 1: Push for total C-Suite alignment
As our Co-Founder Michael Leppan shared here, AI needs leadership, not delegation, meaning CEO-level ownership and total C-suite alignment, backed by a clear plan that demonstrates how AI fits into the operational model, compliance frameworks, workforce development, and overall customer experience business wide, not just in marketing.
The questions that all executives should answer (together) include:
- Where is AI already affecting our business that we haven’t acknowledged?
- Do we have a clear, governed approach to its use?
- Are we measuring success with frameworks that actually reflect how people behave today?
- Are we empowering our teams with guidance, or just leaving them to figure it out?
- Are we giving marketing the mandate and tools to support through these shifts?
Without clear answers to these questions and structured plans around them, businesses, and the teams responsible for growing them, are flying blind.
Tip 2: Address the data maturity problem
Again, challenge #1 should ideally open wider conversations about what problems CMOs can feasibly solve on their own. Business-wide data maturity is not one of them.
Ultimately, the ideal scenario is a clean, centralised database with machine-readable architecture. Dissolving multi-platform silos will allow for a unified customer profile that can fuel advertising performance through hypertargeting, personalisation, and faster activation.
This process should involve the CMO, CEO, CFO, CIO and/or CDO, and should be a priority before heavily investing in AI.
Tip 3: Prioritise AI readiness
Working with other business leaders, CMOs need to enforce strong AI governance within their teams. Below is a provocation Michael shared, and one which CMOs can put forward to fellow business leaders to begin the necessary conversations:
When was the last time you knowingly let your employees deploy unregulated, business-critical software without approval?” Because that’s happening with AI today.
AI readiness comes from both the top down and the bottom up. Bottom up is about giving people the tools and enterprise licenses they need, and each team has a centralised strategy on how AI is used. To achieve this, CMOs must create a controlled AI usage environment:
- Provide staff with a clear list of approved tools
- Ensure those tools have enterprise-level memberships, where possible, which will ensure data security and privacy (i.e. ChatGPT and Gemini enterprise assure their models are not trained on any inputs)
- Provide regular, best-in-class training around those specific tools and general AI usage
- Create AI-specific roles, such as an AI officer, whose sole responsibility is to ensure the business and staff are as up to date on best practice
Top down is about ensuring that all business leaders are in total agreement about their AI approach and understand the necessity to invest and use AI responsibly, ensuring that the necessary moves are made to not only protect their business but set the likes of CMOs up for success.
Tip 4: Protect your budget
If CMOs can successfully realign expectations, they stand a better chance of moving some of their budget away from AI tools and preserving it for activation and staffing. Unless marketing specific, solutions like ChatGPT Enterprise should be considered a wider business expense, or split between departments that are using them.
CMOs should work with other department heads to build a business case to secure the CFOs backing when investing in enterprise-wide tools, positioning the investment as a foundational growth asset that unlocks downstream profitability for the entire business.
How we’ve done it at Open Partners
At Open Partners, we call ourselves the Agency of Next because we are relentlessly focused on the future. As part of that ethos, AI has been at the core of our operations for some time. We have achieved total, highly regulated AI integration across our core disciplines, and our people, partners and clients are reaping smarter, faster, and better outcomes.
This integration wasn’t a top down mandate. Our leaders ensured the AI vision was clear and provided a robust investment backing in the right people, tools, licenses, and training that would enable our teams to maximise productivity, experiment, innovate, and move at pace, all within the guardrails of responsible AI use.
Ultimately, even within their own departments, it’s not solely a CMOs responsibility to deliver true AI integration and effectiveness. AI readiness doesn’t operate in silos; it’s a business-wide effort.
As CMOs move at speed to accommodate changes in the advertising landscape, business leaders must provide a clear AI strategy that ensures their teams have the necessary investment in the tools they need, the data infrastructure in place for those AI tools to execute, and the proper governance to protect both the business and their customers from potential misuse.
