2026 Predictions for product teams
With large language models learning while we sleep, and new algorithms released daily, disruption is accelerating across every industry. At the center of this change are product teams . We predict how product organizations will evolve in structure, scope, and their approach to work in 2026.
In this report, you’ll find:
- New opportunities to leverage and derive value from AI.
- Ideas for reshaping your product org to move faster, together.
- How to experiment with AI, without losing competitiveness.
Every company is being forced to answer the same question: will you build the AI-infused experience your customers now expect, or will a faster-moving competitor do it first? Airtable surveyed 550 product leaders across industries and combined those findings with insight from its own product, design, and engineering leadership to build six predictions for how product teams will need to change in 2026 — in scope, structure, and mindset.
6 predictions
for product teams navigating AI disruption in 2026
550 leaders
surveyed across industries on how they're adopting AI today
92%
of product leaders are now responsible for revenue — up from 45% in 2022
66%
of a product leader's week is still spent on manual work like compiling updates and reports
Prediction 1 — Every company will become an AI company or risk disruption
Consumers expect AI-infused experiences. Product teams must embrace AI to deliver.
AI is transforming how we experience brands and products — from personalized recommendations and human-like answers to seamless handoffs between platforms. At the business level, companies look to AI to streamline inventory management, detect fraud, respond to user needs, and adapt to market conditions. To deliver the AI-infused experiences customers expect, product leaders must first embrace AI to transform their own operations: infuse AI into internal operations, and deliver AI experiences into their products.
To understand how product leaders are adopting AI today, Airtable surveyed 550 product leaders across multiple industries and found that 55% are already investing in AI, and 76% expect that investment to grow next year.
“In 2026 and beyond, companies will live or die by the strength of their digital products.” — Howie Liu, CEO, Airtable
Product leaders who report “extensive” use of AI across their teams' daily workflows are significantly more likely to hit their goals, ship releases on time, and scale faster. The top reported benefits: improved feature prioritization (37%), better resource allocation and automation of routine tasks (33% each), enhanced data analysis (32%), and enhanced quality assurance and increased speed to market (31% each).
Inside the guide: the full self-assessment — are you investing in AI fast enough, and educating your teams to reduce uncertainty around it?
Prediction 2 — Successful product leaders will own (and skyrocket) revenue
As you augment your product's impact on the bottom line, don't forget to expand your influence at the same time.
According to Airtable's research, 92% of product leaders are now responsible for revenue — up from 45% in 2022 — and yet, only 26% have very high visibility into the ROI of their product launches. For too long, product teams have thrown their latest innovations over the fence to go-to-market teams. That's no longer enough: product leaders must take on a more strategic role that extends into product marketing and go-to-market outcomes.
In 2026 and beyond, syncing information with marketing and sales becomes mission-critical for understanding how the pitch is landing, why deals are won or lost, and which work will actually drive future revenue — not just the loudest customer feedback. That means accurately reporting against metrics like revenue, feature delivery time, ROI, market share growth, and product quality, not just customer satisfaction.
“This redefined role requires PMs to think 'beyond the roadmap' to influence—not just the product strategy—but the go-to-market strategy for everything that ships.” — Anthony Maggio, head of product management, Airtable
Inside the guide: the full checklist for auditing your cross-functional visibility into ROI, positioning, and win/loss data
Prediction 3 — First-mover “advantage” might actually be a disadvantage
Feel the need for speed? Let go of historical assumptions; the way we approach building products is changing.
It's instinctual to react to the emergence of AI by building as fast as possible. But in this moment of rapid disruption, the companies that move fastest aren't guaranteed to win. “We are shifting from measuring speed to focusing on time to value, and that is a much better representation of return on investment,” Inbal Shani, chief product officer at Twilio, told McKinsey recently.
The paradox shows up everywhere: ChatGPT was first to market, but Claude followed with greater thought around security and user needs. AI copilots and chatbots were an immediate response to the AI boom — more recently, Salesforce CEO Marc Benioff called them “the next Clippy” for failing to deliver on customer expectations. Even at Airtable, the product team was mid-swing on new user activation — templates, assisted onboarding, pre-made apps — when large language models emerged. The instinct was to stay the course. Instead, the team went back to the drawing board with a fresh understanding: it's more important to take the time to deliver truly powerful AI experiences than to ship the first iteration that comes to mind.
“Being first to market or jumping on the latest trend won't cut it; you must deeply understand what you're selling and why someone would use and buy it.” — Jimmy Hillis, head of engineering, Airtable
Inside the guide: the full framework for testing whether an idea is worth building — including the questions Airtable's own product team asks itself
Prediction 4 — Product development will be less about having the right answers, and more about asking the right questions
The roles of engineers and designers will shift from traditional product development, to facilitating conversations with AI.
As teams invest in education and experimentation, the biggest part of the work will no longer be traditional development and design. Instead, it will require “working with AI models to understand how to refine their prompts, and how to translate user intent into prompts that lead to the right results,” says Anthony Maggio, head of product management at Airtable. Design strategy will shift too — shaping conversations between humans and AI, and architecting decision-making on behalf of AI.
“A lot of times, the familiar sequences of buttons and boxes we reach for will need to be replaced with a conversation.” — Jaime McFarland, head of design, Airtable
Users increasingly expect greater contextual awareness, predictive anticipation of needs, human-like interaction, and incredibly fast time to value. In response, product teams must deliver adaptive interfaces, new UI and interaction patterns built for conversational UX, and intuitive design that counterbalances increasingly complex technology.
Inside the guide: the full set of prompts product teams can use to translate customer needs directly into AI outputs
Prediction 5 — Teams that fail to automate generalist tasks will lose; expertise is critical currency in the age of AI
As product teams use AI to automate manual work, the shape of the org will shift. Experts who understand the nuances of the product and the market will rise through the ranks, giving up the grunt work that previously held them back.
The majority of product leaders today report spending at least 66% of their week on manual work — chasing updates, compiling insights, and crafting repetitive documentation. Airtable identifies three emerging roles AI now fills for product teams: AI as a Data Wizard (synthesizing mountains of customer feedback in seconds), AI as a Content Captain (documenting product requirements without missing a beat), and AI as a Prototyping Genie (reaching proof-of-concept with viable design and code).
“Finding the right talent—people who are really uniquely qualified to understand the market, craft vision and narrative, and push the product forward—will be critical to the product organization's success.” — Anthony Maggio, head of product management, Airtable
Inside the guide: the full breakdown of which generalist tasks to automate first, and how to reshape your team around expertise
Prediction 6 — Winning teams will use AI to process and action customer feedback
With everyone talking about automation, one of the strongest AI use cases is the ability to quickly analyze voice of the customer.
Looking at the practices of 550 product leaders not currently running on Airtable, the research found that 40% are still relying on manual processes to understand voice of the customer, and only 31% have deep confidence that they're shipping the right products for their customers. Without an automated way to prioritize the growing volume of feedback, teams risk strategy drift — building whatever feedback is loudest, rather than what actually moves company goals.
Area | Current state | Future state |
|---|---|---|
How teams operate | Teams are flailing in an abundance of information | Easily manage and prioritize feedback at scale with AI |
Risk to strategy | Roadmaps go out the window as teams scramble to address the loudest, most abundant feedback first | Successful teams invest in AI to accelerate feedback analysis and stay aligned to strategy |
Where product leaders spend time | Managing the volume of voice-of-customer data manually | Matching feedback with other inputs and long-term vision to make the right bets |
“There needs to be a technological shift in investing in AI to understand the voice of the customer quickly — and a cultural shift to align product to strategy, pulling teams out of feature-focus and into outcomes and impact.” — Anthony Maggio, head of product management, Airtable
Inside the guide: the full set of questions to ask before scaling AI-driven feedback analysis, including data-source and privacy considerations
That's the shape of product in the era of AI: teams that own revenue, resist the urge to be first just for the sake of speed, trade buttons for conversations, and let AI absorb the generalist grind so expertise can rise to the top. The full report includes every survey stat, the complete self-assessment questions for each prediction, and real examples from product teams at Amazon, Walmart, BlackRock, and Airtable itself.