Can AI create a (trustworthy) full marketing strategy?

TL;DR

AI isn't ready to independently create full marketing strategies yet. While generative AI excels at facilitation (summarization, brainstorming, content polishing, and visualization), it falls short on the nuanced, expertise-driven work that defines strategic planning. The tools lack access to crucial first-party data, can't replicate human taste and judgment, and often produce generic outputs when asked to do too much. Right now, AI works best as a collaborative thought partner, accelerating existing processes rather than replacing human expertise. The key? Use AI for tactical support while keeping humans firmly in the decision-making seat.

Your LinkedIn feed is probably drowning in hot takes about AI employees, replacement workflows, and the death of creative roles right now. But here's what we're actually seeing in the performance marketing trenches: AI is powerful, but it's not magic. And it’s not ready to make a full marketing strategy just yet. 

What AI does well (and what it doesn't)

Think of AI as an accelerator, not a replacement. The technology genuinely excels at specific tasks:

Summarization topped the list when Thrive ran internal Gen AI hackathons. AI can condense meeting notes, reports, and research into digestible formats tailored to different audiences (whether you're briefing a CMO or a marketing coordinator).

Brainstorming and ideation work well when you treat AI as a thought partner rather than an answer machine. The tools have remarkable patience for iterating on half-formed ideas, helping you refine concepts through multiple rounds of feedback. Just remember: AI works best on topics with abundant public information (like planning an Italy itinerary) and struggles with proprietary or industry-specific challenges.

Content polishing transforms brain dumps into coherent briefs. Instead of wrestling with lengthy documents, teams can use AI to tidy up ideas and get everyone aligned faster.

Visualization and concepting have become genuine superpowers. AI can mock up creative journeys, limited landing page concepts, and some full-funnel messaging to give teams clearer vision of the end goal without lengthy written briefs. Image generation has evolved remarkably, enabling rapid variation testing and audience customization.

But here's where it breaks down: AI can't do the strategic heavy lifting. It won't find that nugget of gold in your data. It can't replace the depth of knowledge that comes from years of experience. And it definitely can't replicate taste.

The data problem

Want to know why AI can't build a trustworthy marketing strategy? Ask it to explain your competitor's actual marketing strategy. Not generic tactics anyone could guess, but the real approach they're running right now.

The output will be severely lacking. That's because AI only knows what's publicly available, and the really valuable stuff (first-party performance data, proprietary research, customer insights from loyal brand members) isn't sitting in a training dataset somewhere.

A genuine marketing strategy requires inputs that AI simply doesn't have access to:

• Historical performance data across channels and tactics
• Market research locked behind vendor paywalls
• Competitive intelligence beyond surface-level observation
• Stakeholder constraints (CEO non-negotiables, operational realities, budget limitations)
• Institutional knowledge that's never been written down

Even if you could feed all this data into AI, there's the infrastructure problem. We don't yet have easy ways to pipe first-party data into these tools securely and comprehensively.

AI as facilitator, not decision-maker

The most effective AI use cases treat the technology as a collaborative tool that moves through each step with human validation. Here's what that looks like in practice:

Instead of asking AI to "create a full marketing plan," break it into pieces. Use deep research features to gather information on a specific question. Review that output. Then use those findings as input for the next specific task. Keep the process iterative and selective — feeding AI ten files at once typically produces shortcuts and lower-quality work.

Trust yourself as the expert. If you're not an expert in an area, don't rely solely on AI's output for that domain. Get other humans involved. Marketing strategy pulls from multiple stakeholder perspectives, and one person working alone with a chatbot can't validate quality across every dimension.

The infrastructure already does some of this well. AI has been optimizing ad spend allocation in platforms like Google Ads and Meta for years, using first-party conversion data to make tactical decisions. That works because the AI has the right inputs and is operating within defined parameters. The same can't be said for asking ChatGPT to build your entire go-to-market strategy.

Where AI shines brightest right now

Research aggregation might be the most universally useful application. Instead of clicking through dozens of search results to piece together statistics, competitive intelligence, or industry insights, AI packages information faster while still letting you assess source quality through citations. It's not replacing research, it's streamlining the grunt work.

The chameleon aspect matters too. AI can communicate concepts in vastly different styles much faster than any human could. Need to explain the same strategy to a technical team, a C-suite executive, and a creative agency? AI can help you tailor each version appropriately.

The worst AI advice out there

"AI employees" top the list of concepts that need to go away. The term does a disservice to both human expertise and AI capabilities. Yes, AI can handle repeatable tasks brilliantly. No, it can't replace the accumulated knowledge, judgment, and taste that define professional work.

Equally dangerous: blanket statements like "just use AI or you'll fall behind." This advice ignores limitations, governance needs, and accountability. It can push businesses toward panic-driven decisions without understanding what they're actually getting (or losing).

AI will absolutely change how we work. But the businesses that succeed will be the ones that deploy it thoughtfully, not reactively.

What this means for marketers

If you're using AI right now, focus on acceleration rather than replacement. Use it to concept faster, research more efficiently, and communicate more clearly. Let it handle the tedious parts of aggregating information and iterating on ideas.

But keep humans in the driver's seat for strategy. The decisions about channel selection, audience segmentation, messaging hierarchy, and budget allocation still require expertise, taste, and access to data that AI doesn't have.

And please, resist the urge to treat AI as a magic solution. It's a powerful tool in the toolkit and that’s it. The marketers who figure out where it helps and where it hinders will be the ones creating work that actually stands out instead of contributing to the sea of AI sameness.