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Masters of Scale

How Adobe is leveraging AI (with CEO & Chair Shantanu Narayen) | Masters of Scale

Shantanu Narayen has weathered plenty of storms for Adobe, the iconic software company that earned more than $21 billion in revenue last year.

Shantanu NarayenguestReid Hoffmanhost

Feb 28, 202530mWatch on YouTube

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Chapter summaries

Why Adobe is facing another market reset—this time from generative AI
The host frames the episode around how AI is reshaping creative tools, and positions Adobe’s CEO as someone who has already led the company through massive change. Shantanu Narayen previews that Adobe’s biggest shifts involved learning along the way, not having perfect foresight.
- •The host says AI models are upending the market for illustration and animation tools.
- •The host highlights Adobe’s earlier shift to cloud-based subscriptions as a prior transformational moment under Shantanu Narayen.
- •Shantanu Narayen emphasizes that the company didn’t know all the benefits of its big changes up front.
- •The episode sets up a focus on staying nimble, curious, and competitive while leading a large global team.
Joining Adobe in 1998: Building InDesign to challenge desktop publishing incumbents
Shantanu Narayen describes what Adobe was working on when he joined and the product focus of the company at the time. He recounts his early work on InDesign and the ambition to build a new layout platform from scratch.
- •Reid Hoffman asks what Adobe and software were like when Shantanu Narayen joined in 1998.
- •Shantanu Narayen says Adobe was hard at work on InDesign, with Quark as a leader in desktop publishing.
- •He describes Adobe’s vision to create a brand-new platform for professional layout.
- •He notes InDesign was one of the first products he worked on at Adobe.
Becoming CEO: Flexibility, timing, and earning opportunities through transformations
Shantanu Narayen explains that becoming CEO was a surprise and traces it to being adaptable through company upheaval and shifting roles. He credits being the right person at the right time and complementary to the prior CEO’s strengths.
- •Shantanu Narayen says he didn’t plan a step-by-step path to becoming CEO and that it came as a surprise.
- •He recounts an economic shock in Japan in 1998 that led to a significant layoff and a shift in his responsibilities.
- •He says he leaned into being a “product guy at heart” and doing what the company needed.
- •He describes how Bruce Chizen’s sales/marketing orientation and his own business/product background complemented each other.
- •He frames the CEO tap on the shoulder as a major professional moment.
Early CEO lessons: Stop doing your old job, disrupt yourself, and focus limited time
Shantanu Narayen reflects on mistakes he made when he first became CEO, especially trying to keep operating like a COO or product leader. He explains how his approach evolved toward choosing a few high-impact focus areas and being comfortable with ambiguity and direction-setting.
- •Shantanu Narayen says he initially assumed he should keep doing what he did in prior roles, and later saw that as a mistake.
- •He describes an annual practice of stepping back to find where he can uniquely have impact.
- •He emphasizes time as leaders’ most valuable commodity, citing AI as a recent disproportionate time focus.
- •He says leaders must be more comfortable with ambiguity and providing direction as the company scales.
- •He notes he was surprised by how much people want the CEO to opine and set direction.
A simple leadership framework: vision, the right team, and a cadence for execution
Asked about balancing strategy, coordination, and culture, Shantanu Narayen lays out three core leadership responsibilities. He argues these apply at any level, with scale changing the “how,” not the fundamentals.
- •Shantanu Narayen identifies three leadership jobs: create a vision, build/shape the team, and establish execution cadence.
- •He says vision applies from first-line managers to CEOs, just at different scopes.
- •He focuses on leveraging the “superpowers” of the existing team and ensuring the right team is in place.
- •He stresses that strategy without execution won’t be effective.
- •He notes that even at scale, he still works through a relatively small number of direct reports and must empower them.
Creative Cloud pivot: Stability after the 2009 recession and faster innovation cycles
Shantanu Narayen explains the forces that pushed Adobe toward subscriptions and the cloud. He describes revenue volatility during the recession, the people impact of layoffs, and product teams’ need to innovate faster than long release cycles allowed.
- •Shantanu Narayen says Adobe was doing well but saw revenue drop sharply during the 2009 recession as it was a “considered” or discretionary purchase.
- •He highlights that revenue declines forced layoffs, which impacted him deeply because they were driven by external conditions.
- •He says achieving financial stability and growth became a key priority.
- •He describes product teams pushing back on 12–18 month cycles, arguing innovation needed to move faster amid cloud and mobile shifts.
- •He frames the shift less as “risk” and more as an investment that would require adaptation if it didn’t work.
Executing the shift and rebuilding trust: parallel models, reliability, and customer transparency
Shantanu Narayen recounts the mixed customer reaction and the operational complexity of moving to an always-on subscription service while still offering perpetual licenses. He emphasizes deliberate execution and describes how transparency with customers became an unexpected advantage.
- •Shantanu Narayen describes two customer camps: early adopters excited by change and others resistant due to inertia.
- •He says there was opposition from existing customers who were skeptical or cynical about Adobe’s motives.
- •He argues the strategic decision was easier than execution, which required delivering always-on software and maintaining compatibility across versions.
- •He highlights deliberate communication with customers as critical during the transition.
- •He says moving away from secret long release cycles enabled Adobe to openly share planned features and gather customer voting/feedback—an unintended benefit they didn’t fully anticipate.
Measuring what matters: Adobe’s data-driven operating model replaces “loudest voice” decisions
With subscriptions, Adobe needed new definitions of success. Shantanu Narayen outlines a customer lifecycle model that uses product usage and customer behavior to guide priorities, reducing internal debates driven by opinion.
- •Shantanu Narayen says Adobe instituted a “data-driven operating model” alongside the new business model.
- •He lists the lifecycle stages as discover, trial, buy, use, and renew.
- •He contrasts past feature prioritization debates—often won by the loudest voice—with testing and observing what customers actually use.
- •He describes using community engagement and in-product experiments to validate ideas.
- •He says reliance on usage data reduces internal debate and guides continued investment.
Adobe’s AI hypotheses: licensed data, defeating the blank page, and AI as augmentation
Shantanu Narayen explains how Adobe steps back during major tech shifts to set guiding hypotheses. He details Adobe’s stance on model training data, how AI can help creators get started, and why Adobe believes it must embrace AI to avoid being disrupted.
- •Shantanu Narayen says Adobe develops “core hypotheses” to guide development during profound shifts like AI.
- •He states that if Adobe creates models, it must be able to attest it has licenses for the data used.
- •He identifies the blank page as a key fear in creative expression and positions AI as a way to translate ideas into forms via conversational interfaces.
- •He says Adobe is embracing AI even amid fears of human replacement, asserting AI augments users and may replace those who don’t use it.
- •He describes a layered approach: build controllable Adobe models, support third-party models with different behaviors, and focus on interfaces where humans realize value.
Experimentation at scale: multiple model approaches plus Acrobat and document AI use cases
Shantanu Narayen argues against shutting down options too early and describes running parallel experiments across training, open approaches, and partnerships. He gives concrete examples of AI efforts spanning marketing data practices and Acrobat’s AI features, including moving from PDFs to enterprise and vertical documents.
- •Reid Hoffman asks how Adobe balances training its own models, leveraging open source, and partnering.
- •Shantanu Narayen says Adobe is running experiments across different approaches and treats them as learning opportunities.
- •He describes marketing technology customers wanting their data not used for commercialization, while allowing anonymous learning that improves the state of the art.
- •He cites Acrobat’s AI Assistant enabling conversational interaction and summaries for PDFs, and describes a next step of extending across documents in enterprise knowledge systems.
- •He mentions an announcement of Contracts AI to understand contracts and their semantic meaning, and reiterates the need to experiment, then converge on a chosen path.
AI and jobs: disruption, new roles, and shifting humans toward higher-level work
Asked about worker fears, Shantanu Narayen frames AI as consistent with prior automation waves: it disrupts some work but creates more jobs overall. He suggests AI will reduce “grunt work” and push people toward higher-level creative and customer-focused tasks.
- •Reid Hoffman raises concerns about whether AI replaces workers versus augments them.
- •Shantanu Narayen says technology and automation typically create more jobs while disrupting some, and he expects AI to be similar.
- •He says automation will change menial tasks and push individuals to “rise to a higher plane” in the work they do.
- •For creative work, he emphasizes focusing on the emotional story and the customer segment rather than repetitive tasks.
- •He acknowledges some people will find the shift threatening and frames the simultaneous disruption/opportunity as the reality of industrial changes.
“Go to where people are”: treating AI models like platforms and leveraging partnerships
Shantanu Narayen explains Adobe’s pragmatic strategy: focus on what Adobe does well while supporting multiple AI model ecosystems. He compares AI models to operating systems and argues Adobe should meet customers on whatever platform they standardize on, partnering where it makes sense given the scale of investment required.
- •Reid Hoffman asks about balancing internal building with M&A, partnerships, and licensing.
- •Shantanu Narayen says Adobe focuses on areas it does well, like applying AI in products such as Acrobat.
- •He suggests only a few players will have the capital to build the largest language models, implying a mix of open and proprietary options.
- •He compares model ecosystems to operating systems, citing Adobe’s history of supporting multiple platforms (Mac/Windows, iOS/Android).
- •He says Adobe should partner and support multiple models because customers will choose platforms, and the investment scale makes leveraging others’ work pragmatic.
Hollywood’s reaction: cost and speed gains alongside anxiety about roles and likeness
The conversation turns to the entertainment industry’s mixed emotions about AI. Shantanu Narayen describes excitement about reducing production and post-production costs and accelerating timelines, while also noting apprehension about how AI affects specific creative roles and likeness concerns.
- •Reid Hoffman asks about Adobe’s interface with Hollywood and whether creators see AI’s creative potential.
- •Shantanu Narayen says there is excitement about creating more media for the same cost and speeding time to production.
- •He uses animation as an example of an area with significant cost that could be impacted.
- •He notes apprehension around what AI means for roles like scriptwriters and actors and concerns about likeness.
- •He says large studios will be central in shaping adoption and that the “genie is out of the bottle,” with adoption pace varying by position in the industry chain.
AI in the CEO workflow and the next frontier: agents, creativity for all, and vigilance on consequences
Shantanu Narayen says AI hasn’t dramatically changed his job yet, but describes using Acrobat’s AI Assistant to summarize PDF-heavy emails. The episode closes with a discussion of agent-to-agent workflows, Adobe’s “creativity for all” ambition (including richer educational expression), and the need for agility and vigilance around unintended consequences.
- •Shantanu Narayen jokes about an AI avatar, then says AI hasn’t changed his CEO job dramatically yet.
- •He describes using Acrobat’s AI Assistant to summarize PDFs attached to emails to become more efficient.
- •Reid Hoffman predicts professionals will use multiple AI agents, changing information flow and decision-making; Shantanu agrees agents must map to roles and tasks and work with humans and other agents.
- •Shantanu Narayen emphasizes Adobe’s internal belief in “creativity for all,” saying many people can describe what they want more easily than they can use tools.
- •He suggests education could expand beyond text and numbers into animation, video, images, links, and feedback, and says Adobe values vigilance and agility to manage unintended consequences while demonstrating why AI strengthens Adobe’s leadership.

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