The industry analyst published 2026 predictions in early December. Bold forecasts: AI will automate 60% of PMM tasks. Product-led growth will make traditional positioning obsolete. Consumerization of B2B will eliminate the need for sales enablement. PMMs will become "AI orchestrators."
The product marketing director had heard similar predictions for 2024 and 2025. None came true the way analysts predicted.
AI didn't automate PMM work—it changed what PMM work means. PLG didn't kill positioning—it made positioning more important. Consumerization didn't eliminate enablement—it shifted where enablement happens.
The 2026 prediction consensus will be wrong the same way previous predictions were wrong: mistaking tool availability for behavior change, conflating what's possible with what's probable, and underestimating organizational inertia.
Here's what everyone's getting wrong about 2026.
Wrong: AI Will Replace PMM Writing
The prediction: Large language models will generate messaging, positioning, launch materials, and competitive content. PMMs will shift from writing to editing AI output. By 2026, most PMM deliverables will be AI-generated with human refinement.
The reality from late 2025: AI generates plenty of PMM content. Almost none of it gets used externally without substantial human reconstruction.
The enterprise SaaS PMM experimented with AI-generated positioning throughout 2025. She'd feed ChatGPT product specifications, competitive research, and customer interview summaries. Ask it to generate positioning statements.
The output was grammatically perfect and strategically shallow. It identified obvious benefits, used generic value propositions, and produced messaging that sounded like every other B2B vendor.
The AI could synthesize information she provided. It couldn't provide the judgment that made positioning effective: which benefits matter most to which buyers? What language do customers actually use versus corporate marketing speak? How do we differentiate when competitors claim similar value?
She used AI extensively in 2025—for first drafts, research summaries, format conversion. But the strategic decisions that made positioning work remained human.
Research from product marketing teams using AI tools in 2025 shows similar patterns: 78% use AI for content generation, but only 12% publish AI-generated positioning externally without substantial revision. The revision effort often exceeds the time saved by AI generation.
The prediction gets it wrong because it treats PMM writing as a mechanical transformation problem: input data, output positioning. But effective PMM writing is a judgment problem: which truths to emphasize, which language resonates, which differentiation angles withstand competitive pressure.
AI in 2026 will continue making PMM writing faster. It won't make strategic judgment unnecessary.
The PMMs who struggle will be those who thought AI would eliminate the hard part (judgment). The PMMs who thrive will be those who use AI to accelerate the mechanical part (drafting, formatting, research synthesis) so they can spend more time on judgment.
AI won't replace PMM writing. It'll make bad PMM writing faster and cheaper, which makes good PMM judgment more valuable.
Wrong: Product-Led Growth Kills Traditional Positioning
The prediction: PLG companies don't need positioning because users experience the product directly. Self-serve onboarding replaces messaging. Product experience becomes positioning. Traditional PMM work becomes obsolete.
The reality: PLG makes positioning more important, not less.
The developer tools company went fully PLG in 2024. Free tier, self-serve signup, no sales team for deals under $25K. Users should judge the product through experience, not marketing claims.
By mid-2025, they'd learned PLG doesn't eliminate positioning problems—it compresses them into the first five minutes of product experience.
In traditional sales-led models, PMMs have multiple touchpoints to shape perception: website messaging, sales conversations, demo narratives, proposal documents. If initial positioning falls flat, you have opportunities to refine it.
In PLG, you have the homepage and the first product interaction. If positioning doesn't land immediately, users churn before you can course-correct.
They discovered users needed positioning to understand what the product was for: "Is this for data teams or engineering teams? Is it for real-time use cases or batch processing? Does it replace our existing tool or complement it?"
The product couldn't answer those questions through UX alone. Users needed context. Context is positioning.
They rebuilt their PLG experience with clearer positioning: targeted onboarding flows for different user segments, messaging that oriented users to use cases before they encountered features, positioning that explained not just what the product did but when to use it versus alternatives.
Data from PLG companies in 2025 shows that time-to-value correlates more strongly with positioning clarity than with onboarding UX quality. Users who understood the product's intended use case (positioning question) reached value metrics 60% faster than users who understood the features (product question).
PLG doesn't eliminate positioning. It increases the cost of unclear positioning because users leave faster than enterprise buyers.
In 2026, PLG companies will invest more in positioning, not less. But they'll measure positioning effectiveness differently: not through sales enablement adoption but through user activation rates, time-to-value metrics, and self-serve conversion.
The prediction gets it wrong by conflating "users experience the product" with "users don't need positioning." Users always need positioning. PLG just moves positioning earlier in the journey and makes it more urgent.
Wrong: Consumerization of B2B Eliminates Sales Enablement
The prediction: B2B buying will resemble consumer buying. Self-education through content, transparent pricing, instant purchasing. Sales teams shrink, enablement becomes unnecessary. PMMs focus on content instead of sales support.
The reality: B2B buying got more complex in 2025, not simpler.
The B2B SaaS company adopted transparent pricing and self-serve checkout in 2024. They'd eliminate sales friction by making buying as easy as consumer software.
What happened: small deals ($5K-$15K) moved to self-serve. Everything above $15K still required sales involvement—not because they forced it but because buyers demanded it.
Enterprise buyers weren't confused about how to buy. They were confused about how to buy correctly for their specific context: which tier fit their compliance requirements? How did pricing scale with their growth plan? What integrations mattered for their tech stack? What happened if their use case changed mid-contract?
Consumer-style simplicity worked when decisions were simple. B2B decisions remained complex even when purchasing mechanisms got simpler.
Sales enablement demand increased in 2025 because the buyers who reached sales had already self-educated. They arrived with specific, sophisticated questions that required reps to go deeper than standard pitches.
The fintech PMM tracked enablement requests across 2025. Volume didn't decrease with self-serve adoption. It shifted from "explain basic value prop" to "explain technical differentiation in our architecture" and "justify ROI for this specific use case."
Sales needed more enablement, not less. Different enablement—less pitch deck training, more objection handling for sophisticated questions.
Research on B2B buying committees shows average stakeholder count increased from 5.4 in 2022 to 6.8 in 2025. More stakeholders means more decision complexity, which means more need for sales guidance, not less.
The prediction gets it wrong by assuming simpler purchasing mechanisms mean simpler decisions. Purchasing got easier. Deciding what to purchase remained hard.
In 2026, sales enablement will remain central to PMM work. But the format will shift from "how to explain our value" to "how to navigate complex buying decisions where buyers already understand basic value."
PMMs who thought consumerization meant less sales engagement will miss where the actual work moved.
Wrong: PMMs Will Become 'AI Orchestrators'
The prediction: PMMs won't write positioning—they'll manage AI agents that write positioning. The role shifts from creator to conductor: orchestrating multiple AI tools, editing outputs, and ensuring quality control.
The reality: This prediction mistakes tools for strategy.
The cloud infrastructure PMM tried the "AI orchestrator" approach in Q3 2025. Use AI for competitive research, AI for positioning drafts, AI for enablement materials. Her role: manage the workflows and refine outputs.
It failed quickly. Because the hard part of PMM work isn't producing deliverables—it's deciding which deliverables matter.
Should she focus on competitive differentiation or customer outcome messaging? Which buyer segment needed attention? Was the positioning problem about feature communication or strategic value? How should she navigate conflicting stakeholder opinions on messaging?
AI couldn't answer those questions. They required organizational context, strategic judgment, and political awareness that no amount of prompt engineering delivered.
She ended 2025 using AI extensively but not as an orchestration model. AI helped her work faster. It didn't make the strategic decisions that determined whether work mattered.
The "AI orchestrator" framing appeals to vendors selling AI tools. It doesn't match how PMM work actually operates.
PMM work in 2026 will remain fundamentally about judgment: What positioning angle differentiates us credibly? Which sales enablement gaps actually affect deals? How do we message this feature without creating confusion? Which competitive threats deserve response?
AI helps execute those judgments faster. It doesn't replace the judgment.
In 2026, PMMs will use AI extensively. But they'll use it the way knowledge workers use email—as an accelerant for communication, not as a replacement for deciding what to communicate.
The prediction gets it wrong by focusing on tools (AI agents) instead of outcomes (better positioning, faster enablement, clearer differentiation).
Wrong: Pricing and Packaging Becomes Self-Serve
The prediction: Transparent, usage-based pricing eliminates the need for pricing complexity. Customers pick their tier, pricing scales automatically. PMMs don't need pricing expertise.
The reality: Usage-based pricing created more pricing complexity, not less.
The API-first company adopted pure usage pricing in 2024: pay per API call. Transparent, scalable, simple.
By 2025, they'd added seven pricing tiers, three commitment options, and two discount structures because pure usage pricing created problems:
Customers couldn't predict costs, which made budgeting impossible
Large customers wanted volume commitments for predictable pricing
Sales needed packaging that allowed deal flexibility
High-volume users hit unexpectedly large bills and churned
They rebuilt pricing with complexity: usage-based rates with commitment tiers, volume discounts, and packaging that grouped features into predictable bands.
This required PMM involvement: How do we position tiers without creating confusion? What commitment levels map to customer segments? How do we explain usage-based pricing to finance buyers who need fixed budgets?
Pricing got more complex across B2B in 2025, not simpler. Companies layered usage pricing on top of tiered pricing, added consumption models alongside subscription models, and created hybrid structures that attempted to balance predictability with flexibility.
Data shows B2B pricing structures increased in average complexity from 2.3 tiers in 2022 to 3.8 tiers in 2025, with 45% of companies offering hybrid pricing models combining multiple pricing approaches.
The prediction assumed transparent pricing meant simple pricing. Transparent pricing just made complexity visible.
In 2026, pricing will remain a core PMM competency. But expertise will shift from "help finance set prices" to "make complex pricing comprehensible to buyers and enableable for sales."
PMMs who thought they could avoid pricing work will find it's become more central, not less.
What's Actually Happening
The predictions for 2026 all make the same error: they identify a trend (AI capability improving, PLG adoption growing, B2B purchasing simplifying, pricing models evolving) and extrapolate to maximum impact.
But trends don't eliminate complexity. They relocate it.
AI doesn't eliminate the need for judgment—it makes judgment more important by making execution cheaper.
PLG doesn't eliminate positioning—it compresses positioning into shorter timeframes with higher stakes.
Consumerization doesn't eliminate sales complexity—it shifts complexity from "how to buy" to "what to buy."
Usage pricing doesn't eliminate pricing complexity—it makes pricing harder to predict and explain.
The actual 2026 will look like 2025 with trends incrementally further along. AI more embedded, PLG more common, pricing more complex, sales enablement more technical.
PMMs won't become AI orchestrators or strategic advisors or pricing experts exclusively. They'll remain what they've always been: translators between product capabilities and market needs, navigating organizational politics while delivering positioning that withstands competitive pressure.
The tools will be better. The fundamental work will be the same.
The PMMs who thrive in 2026 won't be those who chase the trend predictions. They'll be those who use new tools (AI, analytics, enablement platforms like Segment8) to do foundational PMM work better: clearer positioning, more effective enablement, stronger competitive intelligence, measurable business impact.
The predictions will say 2026 revolutionizes PMM. The reality will be that 2026 makes PMM incrementally more effective for those who adapt and incrementally harder for those who don't.
That's less dramatic than "AI replaces PMMs." But it's what will actually happen.
The question for your 2026 planning isn't "how do I become an AI orchestrator?" It's "how do I use improving tools to deliver more positioning clarity, enablement effectiveness, and competitive advantage than I delivered in 2025?"
Answer that, and the trend predictions don't matter. Ignore it, and no amount of AI orchestration will save you.