ChatGPT for Product Marketing: Positioning and Messaging at Scale

There's a peculiar machine masquerading as strategy.

800 million people use ChatGPT every week.

Among them: product marketers drowning in positioning workshops, messaging frameworks, and GTM chaos. They open the same blank chat window, type the same prompts, and receive the same algorithmic reassurance that this time, the messaging will land.

And yet.

95% of new products fail to meet their launch goals. 80% of product launches by 2025 will require significant changes after the initial rollout due to market disruptions and misalignment. 50% of tech product marketing leaders indicate that a lack of effective collaboration with revenue functions is a top barrier to reaching expansion goals.

The problem isn't a lack of words. God knows we have enough words.

The problem is that everyone's using the same word generator—and wondering why their positioning sounds like a Mad Libs exercise in corporate jargon.

The Illusion of Strategic Depth

Let me paint you a picture of modern product marketing:

You're a product marketing manager at a mid-stage B2B SaaS company. Your CEO wants differentiated positioning. Your head of sales needs clearer messaging that actually converts. Your product team keeps shipping features that don't align with what marketing promised. Your customer success team is fielding questions about capabilities you never mentioned in the launch docs.

You need positioning that unifies. Messaging that resonates. A GTM strategy that doesn't implode when sales gets their hands on it.

So you do what 61% of marketers are already doing: you open ChatGPT.

You type: "Create a product positioning statement for our AI-powered marketing analytics platform targeting mid-market B2B companies."

Thirty seconds later, you have your answer. It's clean. Professional. Structured precisely the way positioning statements should be structured.

It's also completely, devastatingly generic.

Here's what nobody wants to admit: Gartner predicts that 30% of outbound marketing messages from large organizations will be synthetically generated by 2025. When everyone's using AI to generate positioning, and the AI was trained on the same corpus of positioning documents from the same companies in the same categories, you end up with positioning that sounds plausible—and means absolutely nothing.

Simply put — I love unique machines. Difficult machines. Machines that make you 'work for it' in order to achieve the best out of their intended use case. There's a simplicity and art to mastering something that, without the direction of a skilled hand, is simply a dormant mishmash of periodic elements arranged in a carefully designed order.

A Stradivarius is an objectively beautiful piece of craftsmanship, but in the hands of Antonio Vivaldi it is transformed into an act of poetry. A Formula 1 car is a fascinating marvel of engineering, but only Ayrton Senna can make it dance in the rain.

ChatGPT is a remarkable instrument. But product marketing isn't about generating text—it's about orchestrating alignment, enforcing consistency, and executing across fragmented teams who operate with fundamentally different assumptions about who your product is even for.

And that's not something you can prompt your way into.

The Product Marketing Execution Crisis

The real challenges plaguing product marketing in 2026 have nothing to do with finding the right words.

They have everything to do with coordination chaos.

The Alignment Apocalypse

50% of tech CMO and product marketing leaders indicate that a lack of effective collaboration with revenue functions is the top barrier to customer expansion. Translation: your product, sales, and marketing teams are executing different strategies for different customers using different language.

More than half of large product teams (50+ people) cite maintaining consistency across roadmaps and processes as their top challenge. Your positioning might be brilliant in the deck. But if product ships features that don't support it, if sales pitches something entirely different, and if customer success has no idea what messaging you used to close the deal—your positioning is fiction.

As one product marketing leader at the Go-to-Market Alliance put it: "If you're the product marketer, you could come up with a fantastic positioning workshop exercise, but if the CEO doesn't care, you're sunk. Even if you get the CEO's buy-in, if the sales team and marketing team aren't aligned with that messaging, you're sunk. If that positioning doesn't turn into a sales pitch that the sales team will actually use, you're sunk." It's all an interconnected web, where if one piece fails, the rest doesn't matter.

This is the unglamorous truth of product marketing: execution beats strategy. Coordination beats cleverness. And alignment beats all the positioning frameworks in the world.

The Launch Failure Pattern

Let's talk numbers.

95% of new products fail to meet launch goals. Only 15% of CPG products remain commercially viable after two years. 23% of product development investments fail due to unclear company strategies.

But here's what's interesting: the why behind these failures isn't mysterious.

35% of failures stem from inadequate market research—teams misunderstanding customer needs or market conditions. 30% fail because of poor product-market fit—they don't solve a meaningful problem. Cross-functional teams often operate with different assumptions about target customers, market size, and success metrics, creating internal inconsistencies that go undetected.

In other words: the launch fails not because the messaging was wrong, but because the teams building, positioning, selling, and supporting the product were fundamentally misaligned about what they were even launching.

ChatGPT can draft your positioning statement. It cannot reconcile the fact that your product team thinks you're building for enterprise while sales is pitching to mid-market, or that your messaging emphasizes ease-of-use while engineering prioritizes power-user features.

The Messaging Consistency Nightmare

Launches with strong cross-functional alignment consistently outperform those where teams operate in silos. Yet achieving that alignment is brutally difficult.

You need:

• A comprehensive messaging guide with core value prop, key benefits, use cases, and technical specs

• Channel-specific variations that maintain consistent core messaging while adapting to platform requirements

• A central asset repository where all teams access approved messaging

• Regular cross-functional meetings to ensure alignment on priorities

• Project management tools to coordinate publishing schedules

Only 37% of CMOs have developed successful cross-functional collaboration methods. 41% of marketers say they can't effectively measure marketing across channels.

This isn't a writing problem. It's an orchestration problem. And orchestration is precisely where ChatGPT—brilliant as it is at generating text—falls catastrophically short.

What ChatGPT Actually Does for Product Marketing

Let's be pragmatic. ChatGPT can accelerate certain tactical elements of product marketing. Here's what actually works:

Phase 1: Research and Brainstorming

What it handles well:

• Generating initial ICP frameworks based on market category

• Brainstorming positioning angle variations

• Creating competitive comparison tables from provided data

• Drafting messaging frameworks to iterate on

The prompt:

You're a product marketing strategist. Our B2B SaaS product [DESCRIPTION] 
targets [ICP]. Our main competitors are [LIST]

What you actually get: Five plausible positioning angles that sound professional and use the right frameworks... and could apply to literally any product in your category. ChatGPT can simulate different personas or customer mindsets, but it's never experienced the pain your product solves. It's never sat through a lost deal debrief. It's never heard a customer describe the moment they realized they needed your solution.

Phase 2: Messaging Development

What it handles well:

• Drafting initial value proposition statements

• Creating feature-benefit-outcome matrices

• Generating messaging variations for A/B testing

• Writing competitive battlecards from your inputs

The prompt:

Based on this positioning: [YOUR POSITIONING]

Create a comprehensive messaging framework including:
- Primary value proposition (under 20 words)
- Three supporting value pillars
- For each pillar: benefit statement, proof point, customer example hook
- Objection handling for [KEY OBJECTION]

What you actually get: A structured framework that follows best practices... with messaging that feels like it came from a template. Because it did. ChatGPT's training data includes thousands of messaging frameworks from successful companies. What you're getting back is the statistical average of what messaging looks like—not messaging that captures your specific, differentiated truth.

Positioning in product marketing is about answering: When your ideal customer thinks of the problem your product solves, what do you want them to think of first? ChatGPT can tell you what positioning frameworks suggest. It cannot tell you what will actually stick in a buyer's mind when they're choosing between you and three competitors who all sound exactly like the output ChatGPT just gave you.

Phase 3: Content Creation

What it handles well:

• Drafting landing page copy variations

• Creating email sequences for launch campaigns

• Writing sales enablement summaries

• Generating FAQ content from positioning docs

The prompt:

Using our messaging framework [PASTE FRAMEWORK], write a product 
launch announcement that:
- Leads with the problem, not the solution
- Uses conversational, benefit-driven language
- Includes a clear CTA for [TARGET ACTION]

What you actually get: Professional copy that hits all the structural requirements. But ChatGPT has never felt a need to own a product, fantasized about one, bought or loved one. It can't experience or imagine the intense feelings that buyer motivation is built upon. That's a massive gap.

Phase 4: Launch Coordination

What fails spectacularly:

ChatGPT has zero capability for:

• Coordinating asset creation across teams

• Ensuring messaging consistency across 15+ touchpoints

• Managing stakeholder feedback loops

• Tracking who's using which version of which message

• Updating messaging when product specs change mid-launch

• Getting sales, product, and exec alignment on final messaging

• Actually publishing or distributing anything

You're copy-pasting between ChatGPT, Google Docs, Figma comments, Slack threads, email chains, and your project management tool, manually keeping track of which version is current and who approved what.

This isn't product marketing. This is administrative hell with better-written drafts.

The Uncomfortable Truth About AI-Generated Positioning

Here's what product marketers don't want to admit: the positioning you're generating in ChatGPT is probably the same positioning your competitors are generating in ChatGPT.

Think about the mechanics.

72% of marketers are using AI for personalization. Over 92% of Fortune 500 companies are using ChatGPT, with applicability expanding into marketing and product development.

Everyone's feeding ChatGPT similar inputs:

• "Our product is a [category] solution for [market]"

• "We differentiate through [feature set]"

• "Our competitors are [list]"

And ChatGPT—trained on positioning documents from the most successful companies in every category—returns the statistical average of what "good positioning" looks like for that category.

The result? Positioning that sounds professional but lacks soul. Value props that tick all the boxes but don't actually land. Competitive differentiation that reads like everyone else's competitive differentiation.

As April Dunford writes in Obviously Awesome: "Positioning is the act of deliberately defining how you are the best at something that a defined market cares a lot about."

ChatGPT can't tell you what your market actually cares a lot about. It can tell you what other positioning documents say markets care about. Those are entirely different things.

The Brand Voice Erosion Problem

Consistent brand presentation can increase revenue by up to 23%. Yet ChatGPT struggles to maintain brand voice consistency without extensive custom training.

Brand voice erosion happens gradually—one AI-generated product description at a time, one sales deck written by ChatGPT at a time, one launch email that sounds just like every other launch email at a time.

Your sales team starts using ChatGPT to personalize pitch decks. Your product team uses it to write release notes. Your marketing team uses it for launch copy. None of them are using the same prompts, the same brand voice guidelines, or even the same version of ChatGPT.

Six months later, your product sounds like it was marketed by committee. Because it was—an algorithmic committee that averages everything toward the median.

What Product Marketing Actually Requires in 2026

Strip away the tactical work, and here's what product marketing fundamentally demands:

1. Market Intelligence

Not generic market research. Real intelligence about:

• How buyers actually evaluate solutions in your category

• Which competitors are gaining traction and why

• What messaging is breaking through the noise

• Where your positioning is weak or misaligned with market perception

According to Gartner, clarity of target audience understanding lies at the heart of GTM strategy. Product marketing leaders must ensure sales, marketing, and product leaders agree upon and have shared definitions of their ideal customer profiles, segments, and personas.

2. Cross-Functional Alignment

Getting everyone to execute the same strategy:

• Product teams building features that support the positioning

• Sales teams pitching what you actually position around

• Marketing creating campaigns aligned with core messaging

• Customer success reinforcing the same value propositions

Launches with strong cross-functional alignment consistently outperform those where teams operate in silos. Yet only 37% of CMOs have developed successful cross-functional collaboration methods.

3. Execution Speed Without Chaos

Top-performing firms have development cycle times that are consistently 20%-25% faster than other companies. Speed matters—but only if it doesn't sacrifice alignment.

The challenge: moving fast while keeping messaging consistent, positioning clear, and teams coordinated.

4. Institutional Learning

Every launch should inform the next. Every piece of buyer feedback should refine positioning. Every competitive move should sharpen differentiation.

But if all your positioning work lives in ChatGPT conversations that disappear when you close the browser, there's no institutional memory. No compounding learning. Just an infinite treadmill of re-prompting the same questions.

5. Human Judgment

Here's the thing about positioning: in marketing, perception is reality. You might have the best-engineered product in your category. But if customers don't perceive it that way, you're toast.

ChatGPT can simulate personas and generate positioning suggestions, but you still must use your own judgment to determine which angles feel most real. That judgment comes from:

• Actually talking to customers

• Sitting through sales calls

• Reading competitor positioning and seeing what lands

• Understanding market dynamics that aren't in ChatGPT's training data

No prompt can replace that.

The Averi Approach: Orchestration, Not Generation

This is where platforms like Averi fundamentally restructure the problem.

Averi isn't trying to be "ChatGPT but for product marketing." It's solving the coordination and execution challenges that ChatGPT can't touch.

The Difference in DNA

While ChatGPT asks "What do you want me to write?", Averi asks "What are you trying to launch, who needs to be aligned, and how do we orchestrate execution across all of them?"

Behind the scenes, Averi's architecture does something ChatGPT fundamentally cannot:

Averi isn't generating positioning from scratch. It's:

• Understanding your brand guidelines from documents you've already created

• Analyzing your past positioning work and what performed

• Connecting to competitive intelligence about market shifts

• Maintaining consistency across every piece of messaging automatically

• Learning from every launch to improve the next one

Synapse orchestration doesn't just draft text. It:

• Routes different aspects of positioning work to different specialized models or experts based on what each piece actually needs

• Coordinates between AI-powered drafting and human expertise from positioning specialists

• Ensures every piece of messaging flows from a single source of truth

• Tracks which teams are using which messages and where inconsistencies emerge

Human Cortex doesn't replace strategy with algorithms. It:

• Connects you with positioning experts who've done this 100+ times

• Provides access to messaging specialists who can translate positioning into campaign copy

• Gives you competitive intelligence analysts who track market shifts in real-time

• Offers launch coordination experts who've orchestrated complex GTM motions

This is the critical distinction. ChatGPT generates text. Averi orchestrates execution.

The Workflow Comparison: ChatGPT vs. Averi

ChatGPT Workflow:

1. Open ChatGPT

2. Prompt for positioning framework

3. Get generic positioning back

4. Copy to Google Doc

5. Send to stakeholders for feedback via email

6. Get conflicting feedback in five different email threads

7. Manually reconcile feedback

8. Update positioning

9. Send updated version to sales (who may or may not use it)

10. Create separate messaging doc for marketing

11. Hope product team sees the final version

12. Discover six weeks later that everyone's using different language

13. Start over

Averi Workflow:

1. Open Averi, type /create launch positioning

2. AI structures positioning framework based on your brand knowledge and past launches

3. Competitive intelligence surfaces automatically from market data

4. Human expert reviews strategic positioning for market fit

5. Messaging variations generated consistently across all channels

6. Sales, product, and marketing review in unified workspace

7. Comments and feedback consolidated in one place

8. Final positioning pushed to all teams simultaneously

9. Every subsequent piece of launch content pulls from same source

10. Analytics show which messages perform best

11. Learnings automatically inform next launch positioning

12. Everyone stays aligned because they're working from the same platform

Notice what's missing? The chaos. The version control nightmare. The misalignment. The forgetting what worked last time.

When Human Expertise Multiplies AI Intelligence

Here's the sophisticated reality: product marketing in 2025 is about combining AI speed with human strategic judgment.

Averi's Human Cortex doesn't "add a human review step." It routes specific aspects of positioning and messaging to vetted specialists based on what the work actually demands:

• A positioning strategist who understands category dynamics and can pressure-test differentiation

• A messaging specialist who knows how to translate technical features into benefit-driven language

• A competitive intelligence analyst who tracks what positioning angles are working for competitors

• A launch coordinator who ensures messaging stays consistent across 15+ touchpoints

The AI handles speed and structure. The humans handle strategy and judgment. Together, they produce positioning that neither could create alone.

This is what it means to become something the world has never seen before: product marketers armed with AI, not replaced by it.

The 2026 Playbook: What Actually Works

If you're committed to using ChatGPT for product marketing, here's the honest framework:

Tier 1: ChatGPT as Brainstorming Partner

Use it for:

• Initial positioning angle exploration

• Generating messaging framework templates

• Drafting multiple value prop variations

• Creating competitive comparison structures

Don't use it for:

• Final positioning (it needs human strategic refinement)

• Ensuring cross-team alignment (it has no coordination capability)

• Maintaining messaging consistency across channels (it forgets context)

• Market intelligence (it's trained on historical data, not current competitive moves)

Tier 2: ChatGPT + Coordination Stack

The reality: To actually execute product marketing with ChatGPT, you need:

• ChatGPT Plus ($20/month) for better models

• Project management tool (Asana, Monday) for launch coordination

• Asset management (Brandfolder, Bynder) for messaging docs

• Competitive intelligence (Crayon, Klue) for market tracking

• Sales enablement (Highspot, Seismic) for pitch deck alignment

• Content management for website/landing pages

• Analytics tools to measure what messaging works

Total monthly cost: $300-800+ Total tools to manage: 7-10 Total coordination effort: Constant Risk of misalignment: High

Tier 3: Integrated Marketing Workspace (The Averi Model)

The paradigm: Everything happens in one place. Positioning development. Competitive intelligence. Messaging creation. Cross-team collaboration. Launch execution. Performance analytics. Institutional learning.

Why it works: Because the biggest challenge in product marketing isn't generating words—it's coordinating execution. It's getting sales, product, and marketing aligned on messaging. It's ensuring consistency across every touchpoint. It's actually launching instead of drowning in process.

95% of new products fail to meet launch goals. 80% of product launches require significant changes after rollout. 50% of tech product marketing leaders cite lack of cross-functional collaboration as a top barrier.

The question isn't whether AI will be part of your product marketing workflow. It's whether you're using AI that understands positioning and orchestration—or AI that just understands language.

The Future of Product Marketing Is Orchestrated, Not Automated

Let's talk about what this really means.

We're at an inflection point. More than 1 billion people use LLMs and GenAI platforms each month. 61% of marketers are already using AI tools in their work. The tools are here. The question is: what will we build with them?

Will we use AI to generate more positioning documents that sound exactly like everyone else's positioning documents? More messaging frameworks that follow the same templates? More value props that could apply to any product in the category?

Or will we use AI to multiply human strategic thinking—to handle the coordination chaos so product marketers can focus on what actually matters: understanding customers, finding differentiation angles that competitors haven't claimed, and ensuring every team executes the same strategy?

Because here's the truth that AI automation enthusiasts don't want you to know: the companies winning in 2026 aren't the ones with the most AI-generated positioning. They're the ones using AI to orchestrate better execution of deeply human strategy.

Think about it.

When everyone has access to ChatGPT for positioning, what becomes scarce?

Not words. We have infinite words.

What becomes scarce is strategic clarity. Cross-functional alignment. Positioning that actually differentiates instead of following category templates.

The ability to say something about your product that captures its unique value in a way that sticks in buyers' minds—not because it followed a framework, but because it's true in a way only your product can be true.

Positioning is the act of deliberately defining how you are the best at something that a defined market cares a lot about. ChatGPT can tell you what frameworks suggest markets care about. But only humans who talk to customers, lose deals, win deals, and understand the emotional and functional dynamics of buying decisions can tell you what your market actually cares about.

Simply put: we have become prompters, but now we must become something the world has never seen before—product marketers armed with AI, but driven by the same ancient and hallowed traits of taste, strategic judgment, and market intuition that our predecessors used to build brands worth remembering.

The Verdict: ChatGPT Is a Starting Point, Not a Solution

Let's be crystal clear about what ChatGPT actually offers product marketing in 2026:

What it does well:

• Generates positioning framework templates

• Drafts initial messaging variations

• Creates structured competitive comparisons

• Accelerates content creation for launch materials

What it categorically cannot do:

• Maintain strategic consistency across teams without extensive coordination

• Ensure cross-functional alignment on positioning

• Coordinate messaging across 15+ launch touchpoints

• Connect positioning strategy to actual market intelligence

• Learn and improve from past launches

• Route work to human specialists when strategic judgment is needed

• Actually execute launches (vs. just drafting documents about them)

What happens when everyone uses it: Your positioning sounds exactly like everyone else's. Algorithmic similarity at scale.

The path forward isn't "AI versus humans." That's a false dichotomy designed to generate LinkedIn engagement.

The path forward is AI + human expertise, orchestrated within workflows designed for product marketing execution.

ChatGPT is a remarkable tool. But it's a general tool being asked to solve specific coordination problems it was never built for.

Specialized AI marketing workspaces—platforms that combine marketing-trained AI models (like AGM-2) with human positioning expertise (like Human Cortex) and unified launch orchestration (like Synapse)—solve the actual problems product marketers face: alignment chaos, messaging inconsistency, and the gap between strategy and execution.

The question isn't whether to use AI for product marketing. It's whether to use AI that understands positioning and orchestration, or AI that just understands words.

Choose wisely.

FAQs

Can ChatGPT replace product marketing positioning workshops?

Not even close.

ChatGPT can draft positioning frameworks. It cannot facilitate the strategic conversations that uncover your actual differentiation. It can't pressure-test positioning angles against competitive realities. It can't synthesize conflicting feedback from sales, product, and exec teams into unified strategy.

Positioning is the act of deliberately defining how you are the best at something that a defined market cares a lot about. ChatGPT can tell you what positioning documents look like. It cannot tell you what your market actually cares about or how you're genuinely differentiated.

Positioning workshops fail or succeed based on the quality of strategic thinking and the rigor of customer insight synthesis. AI can support that process. It cannot replace it.

How do I maintain messaging consistency when using ChatGPT?

The honest answer? With extraordinary effort and constant vigilance.

You need to:

• Create detailed brand voice guidelines and paste them into every prompt

• Build custom GPTs trained on your specific messaging

• Manually review every piece of content for voice consistency

• Create a central repository for approved messaging

• Implement approval workflows to catch inconsistencies

• Hope that everyone using ChatGPT follows the same process

Brand voice erosion happens gradually when different teams use generic AI tools without robust governance. One sales deck at a time. One product description at a time.

The easier answer? Use platforms purpose-built for product marketing that enforce messaging consistency automatically across all teams and touchpoints.

What's the ROI of using AI for product marketing?

Depends entirely on what you're measuring and how you're using it.

If you're using ChatGPT to produce 10x more positioning documents that don't actually improve launch performance, your ROI is negative. If you're using specialized AI to coordinate smarter workflows that launch products with higher alignment and less chaos, ROI compounds.

95% of new products fail to meet launch goals. Launches with strong cross-functional alignment consistently outperform those where teams operate in silos. The ROI question isn't "AI yes or no?" It's "which AI, for what purpose, solving which actual problem?"

Will ChatGPT make product marketing easier in 2026?

Define "easier."

Will it generate positioning drafts faster? Yes.

Will it reduce the strategic thinking required to differentiate? No.

Will it coordinate cross-functional alignment? No.

Will it ensure messaging consistency across sales, product, and marketing? No.

Will it help you understand why your positioning isn't landing with buyers? No.

The fundamentals of positioning haven't changed; clarity, consistency, and differentiation still win. What has changed is where that positioning gets discovered. Buyers now build their first shortlist inside ChatGPT before they ever reach your homepage.

That means you need positioning that's clear enough, distinctive enough, and well-distributed enough to break through AI-generated category comparisons. Generic ChatGPT-generated positioning won't cut it.

How do I avoid my positioning sounding like everyone else's?

This is the existential question of 2026.

When 800 million people use the same tool weekly and 61% of marketers are using AI, differentiation requires intentional human input.

The answer isn't avoiding AI. It's using AI that's been trained on your positioning work, your competitive intelligence, your customer insights. It's routing strategic decisions to humans who understand market dynamics AI can't perceive. It's building systems that preserve distinctiveness while gaining efficiency.

Generic AI produces generic positioning. Specialized AI coordinated with human expertise produces positioning that sounds unmistakably like your brand.

What's better than ChatGPT for product marketing?

Better is contextual.

For brainstorming positioning angles? ChatGPT is excellent.

For execution at scale with cross-team alignment? Purpose-built product marketing workspaces that combine:

• Marketing-trained AI models (not general conversational AI)

• Competitive intelligence integration

• Human positioning expert networks

• Unified workflows from strategy to launch

• Institutional memory that compounds learning

• Native alignment tools for cross-functional teams

Platforms like Averi solve the coordination chaos that ChatGPT can't touch. They don't ask "what do you want me to write?" They ask "what are you trying to launch, and what's the smartest combination of AI + human expertise to get every team aligned and executing?"

Should I train ChatGPT on our past positioning work?

You can try, but understand the limitations.

ChatGPT's context window is limited. It can't maintain long-term memory of your positioning evolution across dozens of launches. Custom GPTs help, but they still require manual updates every time positioning changes.

More critically: ChatGPT can learn your language, but it can't learn your strategic judgment. It doesn't know which positioning angles worked and which flopped. It doesn't know why certain messages resonated with buyers. It doesn't track competitive moves that invalidate old positioning.

Platform solutions that train on your positioning work and connect to competitive intelligence and learn from performance analytics and coordinate human expert input provide exponentially more value.

Can AI help with competitive positioning?

Yes, but with major caveats.

ChatGPT can simulate customer mindsets and generate positioning suggestions if you feed it competitive data. It can help you brainstorm differentiation angles. But:

• ChatGPT's market statistics are often hypothetical—it generates plausible-sounding but incorrect data

• It has no access to real-time competitive intelligence

• Buyers now build shortlists inside ChatGPT, so your positioning needs to be AI-readable and correctly represented

• You need to monitor how AI tools describe you and adjust continuously

Real competitive positioning requires: understanding how competitors are actually positioning (not how their websites say they position), tracking which messages are breaking through, and continuously refining differentiation based on market feedback. ChatGPT provides a starting point. It's not the strategy.

What about positioning for AI-native products?

Interesting question.

The impact of AI—including GenAI—on product marketing leaders is twofold. They must understand both how to enhance their team with AI tools AND how AI-enhanced offerings differentiate from competitors.

If you're positioning an AI-native product, you're competing in a category where everyone claims AI-powered capabilities. Generic "AI-driven" positioning means nothing. You need positioning that captures your specific AI architecture, your training approach, your human+AI workflow, and the outcomes that only your implementation delivers.

This requires even more strategic precision—and even less tolerance for generic ChatGPT outputs that sound like every other AI product launch.

Is the future of product marketing fully automated?

God, I hope not.

Product marketing in 2025 is about combining AI speed with human strategic judgment. The human element in storytelling and messaging remains crucial, with product marketers focusing on emotional resonance while AI handles data analysis.

The winners in 2026 will be product marketers who treat AI as an operating system for coordination—not a replacement for strategy. Those who use AI to multiply human expertise, maintain distinctiveness, and orchestrate complex launches efficiently.

The losers will be those who outsource positioning to chatbots and wonder why their launches fail like 95% of launches do.

The future isn't automated. It's orchestrated.

Ready to move beyond ChatGPT's limitations for product marketing? Explore Averi's AI marketing workspace where AGM-2 intelligence, competitive analysis, and human positioning expertise unite in workflows designed for actual GTM execution.