Archilochus, the ancient Greek poet, wrote a line that has spanned 28 centuries and is now part of every Navy SEAL training manual and leadership speech: We are not living up to our expectations. We fall at the level of our training.
This is where most marketers find themselves with AI today.
Expectations are enormous. The training is thin. Every provider has AI functionality. Every conference has a keynote on AI. Each analyst has a framework. And every marketing team is asked to deliver more growth, more personalization, and more efficiency with the same headcount.
The reality, according to Gartner, From effectiveness to impact: how CMOs can bring real value to AI, is that CMOs now allocate an average of 15.3% of their marketing budgets to AI. Yet only 30% of marketing organizations report being mature or fully developed AI ready. The budget is there. Preparation is not.
It’s the ubiquity of AI that defines marketing in 2026. And that’s why the most important question for marketers right now isn’t “”what AI should we buy? It is “Are we really capturing the value of what we have already purchased? »
A May 2025 study commissioned by Optimove, “Forrester Opportunity Snapshot AI: Accelerating Marketing Impact with AI and Agile Workflows“, tells the same story. The study revealed a clear gap between AI ambition and execution. Only 39% of marketers use AI for content creation, 37% for campaign workflows, and just 14% for creating audience segments. This indicates that the features with the greatest impact are those that are least adopted.
The McKinsey diagnosis
In the recently revised book, « Rewired: How Big Businesses Win with Technology and AI“, the McKinsey authors make a pointed argument that applies directly to marketing leaders. Most companies make mistakes when it comes to AI. They chase isolated pilots. They confuse experimentation with transformation. They don’t capture measurable value because they haven’t rethought how their organization actually works.
Are you doing this correctly?
McKinsey identifies six capabilities that distinguish companies that capture value from companies that simply spend money on AI:
Transformation roadmap. Go beyond single drivers. Tie every digital and AI initiative to concrete financial value and strategic business objectives. If you can’t draw a line between an AI tool and a P&L result, the tool doesn’t earn its place.
Talent bench. Train your business leaders in technology and AI. Stop outsourcing your core capabilities. Winning companies build internal talent, not hire it.
Operating model. Break the waterfall. Shift to product- and platform-based operating models in which multidisciplinary teams of technologists and business operators work together as a unit, not a relay race.
Distributed technological environment. Break down monolithic IT systems into modular, API-enabled architectures. The problem is not the architecture itself. The fact is that individual teams can innovate without waiting for a centralized bottleneck to disappear.
Data everywhere. Give hundreds of distributed teams easy access to high-quality, federally regulated data products. Winning AI companies have already solved data accessibility. Losing companies continue to email each other CSV files (data files).
User adoption and enterprise scale. This is where most AI initiatives die. Solve the adoption barrier by changing the way employees actually work. Deliberate management of change. End-to-end process transformation. Not just a training video and a Slack announcement.
If your marketing organization is honest, you will recognize gaps in at least three of these six. It’s not a failure. This is the starting point.
From AI 1.0 to AI 2.0
AI 1.0 was the era of productivity. Tools that wrote faster, generated faster, summarized faster, executed faster. For teams that did it well, productivity translated into real business results. Campaigns delivered at customer speed. Messages arrive at the right time.
AI 2.0 is the era of business results. It builds on what AI 1.0 has made possible, but it measures success differently. Not by the time saved. Through revenue earned, conversion increased, loyalty gained, customer relationships deepened.
Gartner’s data is unambiguous. Only one in three CMOs are getting the returns they expect from AI investments. Most focus on efficiency. They measure time saved and speed. The most successful CMOs take a fresh approach. They prioritize business results, not just productivity. They measure conversion rates, customer satisfaction, retention and revenue impact.
Organizations that automate more of their marketing work are twice as likely to see ROI from AI. Yet short-term productivity gains rarely translate into meaningful business results unless you intentionally measure and optimize for impact.
By 2028, Gartner predicts that only 10% of CMOs who focus on saving time rather than business results will get the budget needed to achieve their strategic goals. This is the alarm signal. CMOs who still measure AI by hours saved will lose the budget argument to CMOs measuring AI by revenue earned.
More advanced companies understand this. Gartner found that the most AI-ready marketing leaders allocate 21.3% of their marketing budgets to AI, compared to the average of 15.3%. Investment evolves with will. Readiness evolves with the discipline needed to measure results.
What this looks like in practice
We’ve seen what this transition looks like for marketing teams who have done the rewiring. A leading iGaming operator is one of the most telling examples. The team reduced campaign execution time from five days to five minutes by combining a unified database with agentic AI for decision-making and orchestration. It was a real productivity gain. And this directly translated into business results, as the team was able to deliver the right message to the right customer, at the right time.
Not to be overlooked is AI 1.0. Real efficiency, with a real impact on the customer, the basis of the next horizon.
AI 1.0 built this capability. AI 2.0 builds on this.
The future without position
Marketing teams winning in AI 2.0 are positionless. They are not locked into rigid roles where the data analyst passes the baton to the campaign manager, who passes the baton to the creative, who passes the baton to the optimization specialist. These are teams where any marketer can perform any task, supported by AI that accompanies them wherever they work.
It’s the rewiring that matters for marketing.
That’s why we’ve integrated AI inside, outside and on top of the platform. It ensures marketing teams are rewired and realize the power of positionless marketing. AI inside the platform via Native AI. AI extends to external tools that marketers already use through MCPs. Customized AI-powered applications on top of the platform for specific customer business needs.
Three pillars, one layer of execution. The marketer chooses where to start. The platform holds the work together.
The marketers who will capture the value of AI are not the ones with the most tools. They are the ones who have the right operating model, the right database, the right talent and the right platform to make it all work together.
The question is not whether your business will be re-engineered for AI. The question is whether you will do it again voluntarily or whether you wait for the market to do it for you.
Archilochus knew the answer twenty-eight centuries ago. We are not living up to our expectations. We fall to our training.
It’s time to practice.
Written by:
By Pini Yakuel, CEO, Optimove
