Archilochus, the ancient Greek poet, wrote a line that has traveled through 28 centuries and now belongs to every Navy SEAL training manual and leadership keynote: We don’t rise to the level of our expectations. We fall to the level of our training.

That is where most marketers find themselves with AI right now.

The expectations are enormous. The training is thin. Every vendor has an AI feature. Every conference has an AI keynote. Every analyst has a framework. And every marketing team is being asked to deliver more growth, more personalization, and more efficiency with the same headcount.

The reality, according to Gartner, From Efficiency to Impact: How CMOs Can Achieve Real AI Value, is that CMOs are now allocating an average of 15.3% of their marketing budgets to AI. Yet only 30% of marketing organizations report mature or fully developed AI readiness. The budget is there. The readiness is not.

This is the AI overwhelm that defines marketing in 2026. And it is the reason the most important question for marketing leaders right now is not “what AI should we buy?” It is “are we actually capturing the value of what we have already bought?”

A May 2025 study commissioned by Optimove, “Forrester Opportunity Snapshot AI: Accelerating Marketing Impact Through AI And Agile Workflows,” tells the same story. It found 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 building audience segments. It indicates that the highest-impact functions are the lowest-adoption.

The McKinsey diagnosis

In the newly revised book, “Rewired: How Leading Companies Win with Technology and AI,” the authors from McKinsey make a sharp argument that applies directly to marketing leaders. Most companies are doing AI wrong. They are chasing isolated pilots. They are confusing experimentation with transformation. They are not capturing measurable value because they have not rewired the way their organization actually operates.

Are you doing this right?

McKinsey identifies six capabilities that distinguish companies that capture value from companies that just spend money on AI:

Transformation roadmap. Move beyond isolated pilots. Tie every digital and AI initiative to concrete financial value and strategic business goals. If you cannot draw a line from an AI tool to a P&L outcome, the tool is not earning its place.

Talent bench. Train the business leaders you have, in tech and AI. Stop outsourcing your core capabilities. The companies winning are building internal talent, not renting it.

Operating model. Break the waterfall. Move to product and platform-based operating models where multidisciplinary teams of technologists and business operators work together as a unit, not as a relay race.

Distributed technology environment. Decompose monolithic IT systems into modular, API-enabled architectures. The point is not the architecture itself. The point is that individual teams can innovate without waiting for a centralized bottleneck to clear.

Data everywhere. Give hundreds of distributed teams easy access to high-quality data products, governed federally. The companies winning at AI have already solved data accessibility. The companies losing are still emailing CSVs (data files) to each other.

User adoption and enterprise scaling. This is where most AI initiatives die. Solve the adoption hurdle by changing how employees actually work. Deliberate change management. 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. That is not a failure. That is the starting point.

From AI 1.0 to AI 2.0

AI 1.0 was the productivity era. Tools that wrote faster, generated faster, summarized faster, executed faster. For the teams that did it well, the productivity translated into real business results. Campaigns shipped at the speed of the customer. Messages landed at the right moment.

AI 2.0 is the business outcomes era. It builds on what AI 1.0 made possible, but it measures success differently. Not by time saved. By revenue gained, conversion lifted, retention earned, customer relationships deepened.

Gartner’s data is unambiguous. Only one in three CMOs are seeing the returns they expect from AI investments. Most focus on efficiency. They measure time saved and speed. High-performing CMOs take a next-step approach. They prioritize business outcomes, not just productivity. They measure conversion rates, customer satisfaction, retention, and revenue impact.

Organizations automating 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 time savings over business outcomes will secure the budget needed to meet strategic goals. That is the wake-up call. The CMOs still measuring AI by hours saved will lose the budget argument to the CMOs measuring AI by revenue gained.

The companies further along understand this. Gartner found that the most AI-ready marketing leaders allocate 21.3% of their marketing budgets to AI, compared with 15.3% for the average. Investment scales with readiness. Readiness scales with the discipline to measure outcomes.

What this looks like in practice

We have seen what this transition looks like for marketing teams that have done the rewiring. A leading iGaming operator is one of the most telling examples. The team cut campaign execution time from five days to five minutes by combining a unified data foundation with agentic AI for decisioning and orchestration. That was a real productivity gain. And it translated directly into business results, because the team could deliver the right message to the right customer at the right time.

Not to be discounted, that is AI 1.0. Real efficiency, with real customer-facing impact, the foundation for the next horizon.

AI 1.0 built the capability. AI 2.0 builds on it.

The Positionless future

The marketing teams winning in AI 2.0 are Positionless. They are not be locked into rigid roles where the data analyst hands off to the campaign manager who hands off to the creative who hands off to the optimization specialist. They are teams where any marketer can do any task, supported by AI that meets them wherever they are working.

That is the rewiring that matters for marketing.

This is why we integrated AI inside, outside, and on top of the platform. It assures marketing teams are rewired and realize the power of Positionless Marketing. AI inside the platform through Native AI. AI extending into the external tools marketers already use through MCPs. AI-powered custom applications on top of the platform for client-specific business needs.

Three pillars, one execution layer. The marketer chooses where to start. The platform holds the work together.

The marketers who will capture value from AI are not the ones with the most tools. They are the ones with the right operating model, the right data foundation, the right talent, and the right platform to make all of it work together.

The question is not whether your company will be rewired for AI. The question is whether you will rewire it on purpose, or wait for the market to do it for you.

Archilochus knew the answer twenty-eight centuries ago. We do not rise to our expectations. We fall to our training.

It is time to train.

---

Written by:
By Pini Yakuel, CEO, Optimove