Archilochus, an ancient Greek poet, wrote a line that has survived for 28 centuries and is now owned by every Navy SEAL training manual and leadership keynote: We don’t rise to our expectations. We fall at the level of our training.
This is where most marketers find themselves with AI right now.
Expectations are high. The training is small. Every broker has an AI feature. Every conference has an AI keynote. Every analyst has a framework. And every marketing team is asked to deliver more growth, more personalization, and more efficiency with the same calculation.
In fact, according to Gartner, From Action to Impact: How CMOs Can Get the True Value of AI, that CMOs now allocate an average of 15.3% of their marketing budget to AI. However only 30% of marketing organizations report mature or fully developed AI readiness. The budget is there. Being ready is not.
This is the influx of AI that will define marketing in 2026. And that’s why the most important question for marketing leaders right now isn’t “which AI should we buy?” Icon “Are we actually getting the value of what we have bought?”
May 2025 study presented by Optimove, “Forrester Opportunity Snapshot AI: Accelerating Marketing Impact with AI and Agile Workflows.,” tells the same story. It found a clear gap between AI ambitions and execution. Only 39% of marketers use AI for content creation, 37% for campaign workflow, and only 14% for building audience segments. It shows that high impact activities are the lowest adoption.
McKinsey Diagnostics
In a recently revised book, “Rewired: How Leading Companies Win With Technology and AI,” McKinsey authors make a sharp argument that applies directly to marketing leaders. Many companies are doing AI wrong. They are chasing single pilots. They confuse testing with change. They are not capturing measurable value because they have not re-engineered the way their organization works.
Are you doing this right?
McKinsey identifies six capabilities that separate companies that capture value from companies that have just invested in AI:
A roadmap for change. Go beyond single pilots. Tie all digital and AI initiatives to tangible financial values and strategic business objectives. If you can’t draw a line from an AI tool to a P&L result, the tool has no place.
A bench of talent. Train the business leaders you have, on technology and AI. Stop putting off your valuable skills. Winning companies build talent internally, they don’t hire them.
A working model. Break the waterfall. Move to product-based and platform-based operating models where multidisciplinary teams of professionals and business operators work together as a unit, not as a relay race.
Distributed technology environment. Break down monolithic IT systems into modular, API-enabled architectures. The point is not the architecture itself. The point is that each group can innovate without waiting for the bottleneck to be removed.
Data is everywhere. Give hundreds of distributed teams easy access to high-quality, government-controlled data products. Companies that are winning in AI have already solved data accessibility. Losing companies are still emailing each other CSVs (data files).
User adoption and business scalability. This is where most AI systems die. Solve the barrier to adoption by changing the way employees work. Deliberate change management. End-to-end process transformation. Not just a training video and a Slack announcement.
If your marketing organization is reliable, you will be able to identify gaps in at least three of these six. That is not failure. That’s the beginning.
From AI 1.0 to AI 2.0
AI 1.0 was the era of productivity. Tools write faster, produce faster, compile faster, run faster. For teams that have done it right, productivity has translated into real business results. Campaigns are sent at the customer’s speed. The messages arrived at the right time.
AI 2.0 is the era of business results. It builds on what AI 1.0 made possible, but measures success differently. Not in the time saved. With profit achieved, conversions increased, retention achieved, customer relationships deepened.
Gartner’s data is ambiguous. Only one in three CMOs are seeing the return they expect on AI investments. Most focus on efficiency. Measure the time saved and the speed. The most effective CMOs take the next step. They prioritize business results, not just productivity. They measure conversion rates, customer satisfaction, retention, and revenue impact.
Organizations that automate most 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 over business results will secure the budget needed to meet strategic goals. That is the awakening. CMOs who measure AI by hours saved will lose the budget argument to CMOs who measure AI by profit earned.
Companies also understand this. Gartner found that the most AI-ready marketing leaders are allocating 21.3% of their marketing budget to AI, compared to 15.3% on average. Readiness investment scales. Readiness measures with discipline to measure results.
Here’s what this looks like in practice
We’ve seen what this change looks like in reorganized sales teams. A leading iGaming operator is one of the most telling examples. The team cut campaign execution time from five days to five minutes by integrating a unified database with agent AI for decision-making 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 underestimated, that’s AI 1.0. Real performance, with real customer-facing impact, is the foundation of the next horizon.
AI 1.0 has built in capability. AI 2.0 builds on it.
Future without form
Sales teams that win in AI 2.0 are Positionless. They are not locked into rigid roles where the data analyst passes to the campaign manager who assigns to the creatives who assign to the development specialist. They are teams where any salesperson can do any job, supported by AI that meets them wherever they work.
That’s an important regrouping in marketing.
That’s why we’ve integrated AI inside, outside, and on top of the platform. It ensures that marketing teams are rewired and realize the power of Positionless Marketing. AI within the platform with Native AI. AI expands on external tools marketers already use with MCPs. AI-powered customized applications on top of the platform for customer-specific business needs.
Three pillars, one layer of killing. The marketer chooses where to start. The platform holds the work together.
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 base, the right talent, and the right platform to make it all work together.
The question is not whether your company will be rewired for AI. The question is whether you will deliberately restock it, or wait for the market to do it for you.
Archilochus knew the answer twenty-eight centuries ago. We don’t live up to our expectations. We fall into our training.
Time to train.
Written by:
By Pini Yakuel, CEO, Optimove
