In 2025, marketers took their biggest step yet into AI. Chatbots, predictive engines, AI dataset analysis, and real-time personalization reshaped digital marketing workflows almost overnight. Teams tested everything from AI data analysis tools to generative AI for marketing, proving how powerful automation can be when paired with strong human oversight.
In MiQ’s first global edition of the ‘AI confidence curve’ report, we found that nearly all marketers were using at least one AI tool for their digital marketing. Most were actually using several, with content creation, marketing automation, and social media management tools topping the popularity charts. When it comes to how often marketers used the tools, 66% said they applied AI to most - if not all - of their projects.
Given this, it’s no surprise that the industry plans to invest more in AI. Looking ahead to 2026, 72% of marketers said they planned to use AI either “somewhat more” or “much more” in their role. While this varied by country, no market showed any plans to decrease usage overall.
You’d be forgiven for thinking that all of this points towards a high level of satisfaction. But we’re very much in the first stage on the AI confidence curve: learning and exploring. We’re beginning to understand what AI can do, and prove the benefit of applying AI tools to our workflows to improve efficiency and increase performance. But there’s a lot more to it, and proving results can be harder than we thought.
As we head into 2026, marketers are re-evaluating their AI setups, their partners, and their expectations. So here are five ways to move forward with confidence in AI, and get the most from your technology, your teams, and your data.
1. Turn personas into plans
Gen-AI tools like ChatGPT have made it easier than ever to build AI personas and run rapid consumer research. Many marketers now generate early-stage personas, audience hypotheses, or even AI personas for B2B marketing in minutes. Some tools can even ingest first-party data to create richer AI generated personas using signals from search, browsing, social interactions, and CRM inputs.
But while these personas look great on paper, marketers still lack confidence when translating them into real, tangible audiences.
AI can tell you who your audience might be, but building segments inside platforms, shaping bidding rules, and mapping creative messaging still requires strategic expertise and deep data integrations.
In 2026, marketers will need tools or partners that go beyond surface-level personas. It’s no longer enough to create profiles. You need a system capable of:
- Turning persona signals into actionable audience segments
- Feeding persona insights into AI campaign management tools
- Connecting persona traits to channel optimization
- Aligning AI personas with AI for personalized advertising.
Platforms like MiQ Sigma enable this leap. By pulling together fragmented datasets and running AI tools for data analysis, Sigma helps marketers convert AI personas directly into programmatically activated audiences.
2. Transform analysis into action
AI excels at analysis. It can parse millions of data signals, far more than humans ever could, and run deep AI data analysis to identify underperforming segments, rising trends, and behavioral shifts. Tools today can:
- Run AI datasets at scaleFlag anomalies in performance
- Provide reporting faster than any analyst
- Surface optimization opportunities instantly.
But analysis is not action. And this is where confidence can drop.
Marketers trust AI-driven reporting, but they struggle to connect insights with execution. They want insights to automatically feed into:
- Audience creation
- Bidding rules
- Frequency caps
- DSP decisioning
- Creative rotations.
In 2026, the marketers ahead of the curve will move beyond standalone Gen-AI tools and adopt integrated systems designed specifically for AI campaign management. Purpose-built platforms take analysis and push it straight into activation, delivering continuous optimization without losing human oversight.
3. Meet consumers in the moment
The classic marketing funnel simply doesn’t map to real consumer behavior anymore. People don’t move from awareness to consideration to conversion. Today’s consumers:
- See a social post and buy immediately
- Hear an influencer recommendation and skip straight to checkout
- Move between channels fluidly and unpredictably.
This means that mapping AI tools to funnel stages often creates blind spots. Marketers need new models that understand moments. What mindset is the consumer in right now? What signals predict their readiness to engage or convert? This is where AI becomes a differentiator.
- AI excels at moment-based decisioning because it can:
- Spot behavior readiness signals
- Identify channel patterns tied to conversion
- Recognize emotional or contextual triggers
- Adjust strategies dynamically.
In other words, this is how AI is used in advertising at its most powerful: unlocking intent in real time.
In 2026, the strongest marketers will focus on moment-driven frameworks supported by:
- Predictive algorithms
- Real-time bidding logic
- Adaptive creative
- Contextual understanding informed by AI tools for data analysis.
Marketers who understand which channels spark action, and deploy AI advertising tools to meet consumers at the right second, will outperform competitors relying on traditional funnel thinking.
4. Create the perfect channel mix
In the first edition of MiQ’s ‘AI confidence curve’ report, we saw that almost half of marketers felt fully confident using AI to pick the right channels. But fewer than half think their budgets and channels are effectively mapped to their audience across the purchase journey.
There’s a clear gap: confidence in the tools vs confidence in the outcomes. To bridge this, marketers need an ideal AI marketing workflow. That workflow should include:
- AI data analysis to surface channel performance
- Persona insights feeding into targeting logic
- Multi-platform activation via a partner-agnostic platform
- Creative testing powered by AI creative tools
- Measurement systems validating and improving AI confidence over time.
A ‘closed-loop’ structure ensures AI does more than optimize channels, it teaches itself to get better with every cycle.
5. Build and test better creative
Around a third of marketers already use AI to design and optimize creative. But this number will climb as AI creative tools get smarter and AI tools with creative analysis gain adoption.
The real power of AI is not just producing creative quickly; it’s understanding why creative works.
In 2026, marketers will rely on AI to:
- Evaluate creative performance in real time
- Identify which messages resonate
- Map creative impact to channels
- Understand which elements drive conversion
- Test hundreds of variations without slowing campaigns
Yet fewer than half of marketers feel they truly understand how targeting and creative work together. This lack of connection weakens performance and reduces AI confidence.
Sigma helps close this gap by:
- Running creative and audience data through unified AI models
- Linking performance insights to persona traits
- Using real trader expertise to validate the machine logic
- Generating feedback loops that help creative, targeting, and bidding improve simultaneously.
The brands that pair fast production with fast analysis will win in 2026.
Ready to confidently jump into 2026?
As an industry, we’re only at the start of the AI confidence curve. We’re beginning to realize the potential of AI, but it’s still challenging to use it effectively. To continue our journey along the AI confidence curve and push performance forward, marketing leaders now need to invest in AI and lean into purpose-built tools.
Watch this space…
