For the past decade, MarTech has expanded in one direction: bigger stacks, more tools, more data, more dashboards.
The assumption was simple – if we stitched enough platforms together, growth would follow.
It didn’t quite work out that way.
Yes, integrations have always been hard. Yes, organisations struggled to unlock the value they expected. But what surprised most leaders wasn’t technical failure it was strategic ambiguity.
Even in organisations where the technology worked, the business impact rarely matched the promise. None of the 50+ senior marketing leaders McKinsey interviewed could clearly articulate the ROI of their MarTech investments.
By 2026, this disconnect is no longer ignorable. Not because of one new tool or trend, but because marketing leaders are being forced to answer three questions they can no longer avoid:
1. Which capabilities actually drive revenue?
Not which tools you own but which capabilities create measurable business impact.
2. How fast can you move from insight to action?
Because in a real-time, AI-mediated world, speed isn’t an advantage. It’s the baseline.
3. Can you prove the value?
According to McKinsey, 90% of C-suite MarTech decision-makers believe best-in-class tools enable strategic outcomes. But belief isn’t enough anymore. Proof is.
Everything that follows in this article ladders back to those three questions. Because in 2026, competitive advantage won’t come from stack size. It will come from clarity.
Here are ten changes senior Marketing and MarTech leaders need to understand. Not as predictions, but as the foundations of how marketing now competes.
1. AI Stops Being About Efficiency and Starts Driving Growth
Walk into most marketing meetings today and someone will mention AI’s productivity benefits: “We can write emails faster!” “Reports take half the time!” “We automated our social posts!”
Great. Now what?
Because here’s the uncomfortable truth: if AI is just making your team faster at doing the same things, you’re missing the plot entirely. Marketing teams using AI report significant productivity gains, with some organisations saving 11-12 hours per week. That’s real. But the companies winning aren’t stopping there. They’re asking a different question: “What can we do now that was impossible before?”
A European telco used AI-driven propensity scoring to identify customers most likely to upgrade to fiber within 30 days. Instead of sending the same upgrade campaign to everyone, they adjusted offers dynamically based on where each customer was in their journey.
Conversions jumped 27%. They didn’t spend more. They didn’t hire more people. They just stopped treating all customers the same.
That’s the shift. Organisations investing in AI see sales ROI improve by 10-20% on average, with leading companies achieving 1.5× higher revenue growth over three years.
AI spending now represents 9% of total marketing budgets, up from 7% in 2024, and 68.6% of organisations have deployed generative AI tools. The technology is mainstream. The question is whether you’re using it to go faster or to go further.
If AI in your organisation only saves time, you’re capturing maybe 10% of its value.
2. Zero-Party Data Becomes Your Competitive Moat
Remember when third-party cookies died and everyone panicked? Turns out, that wasn’t the problem. It was the diagnosis. The end of cookies didn’t kill marketing- it exposed how many organisations were building on sand. How many were inferring what customers wanted instead of actually asking them. Here’s the shift: organisations are moving from collecting data to earning it. Zero-party data is information customers intentionally and proactively share with you – their preferences, purchase intentions, contexts, and feedback. Not inferred from behaviour. Not scraped from browsing. Willingly given in exchange for value. 55% of marketers expect zero-party data to become more important over the next two years, and research shows 84% higher acceptance rates for zero-party data collection when users perceive value exchange. Here’s what it looks like when you get it right: A beauty brand launched a “Find Your Perfect Match” quiz – not a gimmick, but a genuine diagnostic tool. Customers answered questions about their skin type, concerns, goals, and lifestyle. In return, they got personalised product recommendations and a custom skincare routine. The brand didn’t infer preferences from past purchases. They didn’t track behaviour across websites. Customers told them exactly what they wanted. Result: Businesses prioritising zero-party data strategies report 318% ROI increases because they’re able to create hyper-relevant experiences without guessing. The insight was always available. Organisations just weren’t asking the right questions. 89% of marketers say privacy should be a key factor in data strategy, with 77% shifting focus from quantity to quality in customer data collection, according to the Future of Marketing report by eConsultancy. Most organisations are still operating with inferred data – like trying to have a conversation by watching someone through a window instead of actually talking to them. The organisations winning in 2026 understand something fundamental: data you earn is more valuable than data you collect. It’s more accurate, more actionable, and it comes with something you can’t infer – trust. Data volume is no longer a competitive advantage. Data transparency is.Want to learn how to implement a zero party data use case?
Check out our Zero Party Data module in Dexata Academy for a more detailed explanation of zero party data and how to configure a use case with Tealium and Adobe Target.
3. Context Engineering Replaces Data Hoarding
Here’s a scene playing out right now in hundreds of organisations: someone fires up a new AI tool, feeds it customer data, and gets back… garbage. Not because the AI is bad. Because the data is a mess. 56.3% of marketers cite poor data quality as their biggest challenge. And when AI agents rely on that data to make decisions, quality isn’t just nice to have. It’s everything. Enter Context Engineering. It’s not about having all the data. It’s about getting the right data to the right AI agent at the right moment. Think about it like this: would you rather have 100 people shouting information at you simultaneously, or one person telling you exactly what you need to know right now? Your AI agents face the same problem. 65.7% of organisations struggle with data integration difficulties, with 34% specifically citing integration of tools as a top challenge. Organisations are drowning in data but starving for context. They’re spending hours manually moving data between systems, reconciling conflicting information, and managing duplicate records. It’s like having a world-class chef and handing them rotten ingredients. The winners in 2026? They’re not the ones with the most data. They’re the ones who’ve figured out how to deliver crystal-clear context at the speed of decision-making.4. Real-Time Activation Moves From Ambition to Expectation
Your customer’s intent just changed. How long until your marketing notices?
If the answer is “tomorrow morning when the overnight batch runs,” you’ve already lost.
According to McKinsey research, 71% of customers expect personalised interactions with brands, while 76% get frustrated when they don’t receive them.
And here’s the kicker… they’re not comparing you to your competitors anymore. They’re comparing you to every experience they’ve had today – including the streaming service that knew exactly what they wanted to watch and the travel app that notified them of a price drop three minutes after it happened.
A travel brand started sending price-drop alerts within minutes of fare changes. Not hours. Minutes. Engagement didn’t just improve… it exploded. Booking windows shortened. But here’s what really mattered: customers started talking about the brand as if it understood them.
The creative didn’t change. The offers didn’t change. The speed changed.
Meanwhile, leading organisations still cling to outdated practices like batch-and-blast email campaigns, simple A/B testing, and scheduled social media posting. It’s like watching someone use a typewriter while everyone else is on Slack.
76% of businesses report using real-time behavioural data, but most are still processing it like it’s 2015.
Relevance now has a half-life measured in minutes, not days. The organisations that move fastest aren’t just winning – they’re widening the gap.
5. Personalisation Finally Becomes Adaptive
Let’s be honest: most “personalisation” isn’t personal at all.
Serving ads for products someone has already purchased isn’t relevance — it’s waste. And rules-based segments that lump millions of customers into the same bucket aren’t personalisation at all. They’re a legacy workaround.
Effective personalisation responds to reality in real-time. And it’s finally becoming possible at scale.
89% of marketing decision-makers consider personalisation essential for their business’s success over the next three years, and 92% of businesses are leveraging AI-driven personalisation to drive growth.
Here’s what it looks like when it works:
A streaming service redesigned its homepage to shift dynamically based on time of day and behavioural cues.
Morning? Short-form, upbeat content rises to the top. Evening? Long-form dramas. Weekend afternoon? Different again. And when someone’s viewing patterns changed – say, they started watching more documentaries – the interface adapted within days, not months.
Here’s what users said: nothing. They didn’t notice the personalisation. They just noticed that everything felt… right.
The fastest-growing companies derive 40% more revenue from personalisation than their less successful competitors. And companies that provide personalised experiences can generate 40% more revenue, with US companies potentially generating $1 trillion through better personalisation.
The technology is here. The question is whether you’re still running rule-based campaigns while your competitors are building adaptive experience
6. Owned Media Becomes a Stability Strategy
Here’s a problem every marketing leader knows: you need to innovate, but you can’t break what’s working.
You want to test that new AI tool, but what if it crashes the system? You want to experiment with a new journey, but what about the seven-figure campaign running right now?
So you do neither. Innovation slows. Operations ossify. And you wonder why competitors are moving faster.
The answer? Stop trying to do both in the same place.
Scott Brinker’s December 2025 “Martech for 2026” report introduced a framework that’s rapidly becoming the default: separate your stack into a Laboratory and a Factory.
The Laboratory is where you experiment, break things, and learn fast. Synthetic data. Small audiences. Rapid iteration. No revenue at risk.
The Factory is where you run proven systems at scale. Real customers. Real revenue. High reliability. Zero tolerance for chaos.
A large financial services brand now prototypes every new personalisation model in a sandbox first. They test with synthetic data until it proves safe, consistent, and valuable. Only then does it graduate to production. Risk dropped. Speed increased. Innovation accelerated.
Organisations are increasingly building custom and homegrown solutions because commercial platforms can’t keep up with the pace of change. of change.
Lab explores the future. Factory delivers the present. Try to do both in the same place, and you’ll bottleneck both.
7. Experience Operations (ExOps) Emerges as the New Glue
Let’s talk about the AI everyone’s excited about and the problem almost no one’s solving. 90.3% of marketing teams now use AI agents. These agents write content, optimize bids, analyze data, triage support tickets, and test journeys – all at speeds humans can’t match. Sounds great, right? It is. Until it isn’t. A global retailer deployed an AI agent to automate paid search bidding. ROI went up. Everyone celebrated. Then someone noticed the AI occasionally used phrasing that was… off-brand. Not wrong, exactly. Just not them. Most organisations would panic and shut it down. This one didn’t. They added a governance layer: vocabulary restrictions, compliance checks, drift monitoring. The AI kept optimising. The brand stayed protected. Here’s the uncomfortable stat: only 23.3% have AI agents in full production. The other 67%? Experimenting. Piloting. “Planning to scale eventually.” Why? Because capability isn’t the risk. Uncontrolled capability is. The primary challenge? Insufficient team training, cited by 34% of MarTech buyers as a key barrier to getting value from technology, – one off training sessions which are easily forgotten about, followed by unclear use cases, data quality issues, and concerns about cost and ROI. Translation: most organisations have the technology but lack the guardrails. AI without governance is volatility. AI with governance is scale. Choose accordingly.8. Customer-Side AI Rewrites the Discovery Playbook
Here’s the disruption most marketing leaders are sleeping on: your customers are using AI to research products right now. Before they ever visit your website. And you have no idea it’s happening.
50% of all consumers now use AI-powered search, putting up to 50% of traditional search traffic at risk.
Someone asks ChatGPT or Gemini to compare your product to competitors. They get features, pricing, reviews, recommendations. They decide. Then maybe they click through to buy.
Your attribution model sees: Direct traffic. Last-touch. Zero credit to the AI agent that just recommended you.
58% of Gen Z and millennials would trust an AI agent to compare prices and recommend options. According to the World Economic Forum, by 2030, over 55% of purchases will be AI-driven.
The Answer? Optimise for AI, Not Just Search Engines
McKinsey projects $750 billion in consumer spend flowing through AI-powered search by 2028. That’s 36 months away.
The shift: visibility is moving from position to inclusion.
Ranking #1 on Google means nothing if ChatGPT, Perplexity, and Gemini never mention you. And they won’t – unless your content is structured for machines to confidently interpret, extract, and cite.
A financial services brand rebuilt their content around clear entities: loans, rates, calculators, eligibility. They didn’t create more content. They made existing content clearer and more authoritative.
Within weeks, they appeared consistently in AI answer summaries across Google, Bing, and Perplexity. They didn’t scale output. They scaled understanding.
What this means: Answer Engine Optimisation (AEO) is non-negotiable. Apply schema markup (Product, FAQPage, Review, Article) so AI can easily extract your information. But it’s not about gaming algorithms – it’s about clarity.
72% of consumers stay loyal only to brands that meet their needs in the moment. Discovery happens in AI. Loyalty happens in delivery.
The traditional funnel is being compressed or bypassed. Optimise for AI discoverability, then deliver exceptional experiences. The middle? It’s disappearing.
The bottom line: Clarity over volume. Authority over activity. If you’re still optimising for “ranking #3” instead of “being the answer,” you’re already behind
9. Owned Media Becomes Your Stability Strategy
In a world where platforms change algorithms overnight and paid media costs keep climbing, what do you actually control?
Your owned channels. That’s it.
64% of brands plan to scale their owned-media investments in 2025, and the reasons are clear: higher engagement, better use of customer data, and complete control over the experience.
Here’s the uncomfortable reality: every dollar you spend on rented platforms (Meta, Google, TikTok) comes with strings attached. Algorithm changes can tank your reach overnight. Ad costs can double with zero warning. Accounts can get suspended. Policies can change.
Owned media doesn’t have that volatility.
A beauty brand watched paid social CPAs spike 40% in six months. Rather than chase algorithm changes and pour more money into the black box, they invested in a loyalty-driven content hub – tutorials, community forums, exclusive product launches, early access for members.
Within 18 months, it became their highest-converting channel at one-tenth the cost of paid social.
The content was theirs. The audience was theirs. The data was theirs. And when Meta changed its algorithm again, they didn’t even notice.
Why owned media matters in 2026:
Platforms are becoming less predictable. Organic reach continues to decline. Brands published an average of 9.5 posts per day across networks in 2024, yet engagement keeps dropping. You’re working harder for less impact on channels you don’t control.
Meanwhile, owned channels e.g. email, newsletters, communities, content hubs, mobile apps, podcasts compound in value over time. Every subscriber is an asset. Every piece of content adds to your library. Every interaction deepens the relationship.
Rented media is a rental. Owned media is an investment.
Here’s what smart organisations are doing:
- Building email lists and newsletters that become primary communication channels, not afterthoughts.
- Creating member communities where customers interact with each other, not just consume content.
- Developing proprietary content that can’t be found anywhere else.
- Using owned channels to nurture relationships, then activating them when needed.
Owned doesn’t replace paid. It makes your entire ecosystem sturdier. When algorithm changes hit, when costs spike, when platforms falter, your owned channels keep running.
In 2026, the organisations with the strongest owned media foundations will weather every platform storm. The ones dependent on rented channels? They’ll be scrambling to adapt every time the wind changes direction.
10. Marketing Ops 3.0: From Tool Managers to Business Value Engineers
For years, Marketing Operations has been the unsung hero -keeping the tech running, managing the CDP or CRM, making sure campaigns don’t break. That era is over.
Team capability gaps are widening. As mentioned earlier, 34% of MarTech buyers cite under-skilled teams as a key barrier to realising their technology’s full value. Tech is evolving faster than teams can keep up. And suddenly, the person who “knows Tealium” or “knows Adobe” isn’t enough. MOps teams are becoming “business value engineers” in 2026 – sitting closer to executive discussions and carrying responsibility for connecting AI, data, and go-to-market strategy.
They’re building revenue cases for new agentic journeys. Designing context flows that feed AI without overwhelming it. Managing cost observability for AI usage. Training marketing teams to work with tools that didn’t exist six months ago. And owning the pipeline between the Lab and the Factory – deciding what experiments graduate to production and what gets killed.
The painful reality: Organisations are achieving far less ROI than possible due to incomplete adoption, with MarTech utilisation dropping to just 33% according to Gartner.
You bought the tools. You integrated the systems. But if your team doesn’t know how to use them – or most importantly why to use them, you’re lighting money on fire.
Marketing Ops 3.0 isn’t about administration. It’s about orchestration. Strategy. Value creation.
Organisations that still treat MOps as “the Tealium admin” are leaving millions on the table.
The Convergence: Why These Trends Matter Together
Here’s why this matters more than any individual trend:
These shifts aren’t happening in isolation. They’re converging into a completely new operating model.
The organisations that win in 2026 won’t be the ones with the largest stacks or the most tools.
They’ll be the ones that have moved beyond debate and can answer three things with absolute clarity:
They know which capabilities actually drive revenue – not which tools they own, but which capabilities create measurable business impact.
They can move from insight to action at speed – because clean architecture and clear context engineering eliminate the friction that slows competitors down.
And they can prove the value – not with belief or intent, but with evidence the C-suite can’t ignore.
If You’re Unsure Where to Begin
You’re not meant to have every answer. The landscape is moving too quickly for that.
But you can understand where your organisation stands and what needs to evolve next.
If you’d like to explore what these trends mean for your organisation – and where your capabilities may need to evolve, let’s set up a short discovery call and we’ll walk you through our unique value realisation framework.
Ready to assess where you stand?
Book a 15-minute conversation to identify where your MarTech, data, and CX investments can unlock greater value.
About The Author
Charlie Nicholls
