I recently spoke with Cynthia Stoddard, Senior Vice President and Chief Information Officer at Adobe, about how the company is translating the promise of AI into real productivity gains and cultural change.
Cynthia shared Adobe’s framework for scaling AI adoption and offered a glimpse into the company’s unique approach to innovation, experimentation, and startup collaboration.
This is the seventh installment of a series of interviews with leading CIOs and technology executives at global enterprises.
Asheem Chandna: What parts of Adobe have materially improved with AI?
Cynthia Stoddard: People often view AI as an overwhelming, abstract concept. Questions quickly pile up: What use cases should we focus on? Which ones should we prioritize? How do we drive adoption among employees? — just to name a few.
I began to look at it through three lenses to make it more actionable. We apply this framework internally and externally: the person, the persona, and the workgroup.
It starts with the person. Everyone has a responsibility to understand and engage with the technology. If you’re not familiar with it as an individual contributor, you won’t recognize how it can help you. And if you’re a manager or leader, you won’t be able to guide your team through the change. Familiarity with AI’s capabilities, including how to use it safely and responsibly, is essential. That includes understanding governance. You can’t just feed confidential data into a model and hope for the best.
Next comes the persona: your role. Once someone understands the tools, the question becomes: how can I apply this to my day-to-day responsibilities? Where can AI boost my efficiency or enhance my quality of work?
Finally, we look at the team or work group. As people across roles start sharing tools and best practices, that’s when we see transformation take hold. Teams begin to operate differently, and AI becomes a driver of organizational change—similar in scale to the shift we saw when companies moved to the cloud.
And of course, across every level, we emphasize the importance of security, privacy, and ethics. This is really essential for us at Adobe.
Zooming out, how big is this shift? How far along is Adobe, and your customers, on the AI journey?
It’s a huge change. AI is changing how people think, not just how they work. Familiar routines are being reimagined.
Imagine being an engineer: you used to start your day reading product requirements. Now, you might begin with a prototype generated by AI. That’s a completely different mindset.
That said, we’re still early in the journey. We’re experimenting, supporting early adopters, and giving customers the tools they need. When I speak with other CIOs, the big question is always: “what’s the value?” How do we measure success beyond just adopting new technology? People want proof: productivity gains, faster product cycles, better outcomes.
We’re in a phase of hackathons, pilot projects, and learning. And yes, there’s caution, understandably, because governance and security are top of mind. But make no mistake: this is real, and it’s here to stay.
Applying your framework, how is AI delivering tangible benefits at Adobe?
We’re already seeing strong adoption and measurable productivity gains through targeted AI integration.
Take product management, for example. We recently held training sessions for our product managers, and they estimated that AI could save them at least five hours per week. That kind of impact adds up quickly, especially when teams fully understand the technology and embed it into their workflows.
What are some examples of how people at Adobe are working differently with AI?
Meetings are a simple but good example. I can’t remember the last time someone sent manual meeting notes; transcription is now automatic.
In engineering, AI is improving code generation as well as QA and test coverage. We’re moving away from traditional, manual testing and seeing better results with AI-enhanced approaches.
On the implementation and adoption side, our teams have created a GenAI chatbot-based learning platform to help our global Sales teams transition to a new CRM tool. Users receive pinpoint coaching and support 24/7 through an AI assistant. This homemade tool has successfully resolved 90% of queries and slashed support response times from days to seconds.
We have also been using AI to review the quality of our requirements documents. Instead of relying on manual checks, we now use AI to scan our SharePoint sites and requirement documents, flagging gaps or inconsistencies—something we used to hire outside firms to do.
Beyond these internal tools, my organization also plays a critical role as the first adopters of Adobe’s emerging products and solutions—something we call Customer Zero. This is how Adobe rigorously tests and improves our products to make sure they’re ready for public release. The past few years have been a particularly exciting time for us. Teams across Finance, Procurement, Legal, and IT have been embracing the next generation of Adobe GenAI products, especially around analyzing and gaining insights from large archives of unstructured documents. And this is really just the start.
AI is clearly reshaping internal workflows. How is AI changing things for your customers?
There is so much going on right now with AI at Adobe. Our Firefly models are ushering in a new era of commercially safe creativity across image, video, and design. Creative professionals are totally reimagining their workflows with Generate Video and Text to Vector among many of the powerful AI features now embedded in the Creative Cloud ecosystem.
We believe in “Creativity for All” at Adobe. I think that the generative AI capabilities in Adobe Express are bringing this to life. It’s easier than ever for non-designers to create standout content on mobile or web. With AI, users can now easily localize content into different languages, generate video from text or image prompts, and even add fun, natural-looking animations in a few clicks. We’re using generative AI to turn everyone into a creator.
For business professionals, I mentioned that there’s a lot on the horizon, but people can already get started with Acrobat AI Assistant. Users are already seeing huge benefits to their productivity here. Anyone can summarize, search, and even chat with PDFs to accelerate understanding and insights.
Finally, marketers are seeing some of the biggest changes. For example, Adobe’s new Agent Orchestrator tool in Adobe Experience Platform (AEP) allows businesses to create and manage custom AI agents. This means that marketers can now engage customers with truly personalized experiences, uniquely relevant to each person, at scale. It’s helping to really drive impact for marketers. That’s just one of many ways we are using AI to bring creativity and marketing closer together.
Fast forward a few years, what will AI at Adobe look like?
I imagine a workplace where every employee has a personal AI agent library as part of onboarding.
These agents will support your role, understand your permissions, and help you work more effectively, essentially serving as teammates.
It’s about building intelligent support systems around each employee to maximize their productivity and creativity.
In our product offerings, we will see reimagined digital content and experiences that are created and delivered with our suite of products. My favorite way to peek into the future is to watch the Adobe MAX sneaks—our Creative Cloud conference. You get to see where we are experimenting, and I always walk away in awe of what is now possible.
How do you balance targeted AI investments with broad experimentation?
We do both.
I mentioned how we are using AI to improve our requirements gathering and testing. That was a focused solution, built to solve the needs for specific roles and personas here.
But we also embrace broad experimentation. Innovation has always been a core value at Adobe. During our Innovation Weeks, employees pitch ideas and get support to build them. It’s evolved into a “Shark Tank”-style event with judges, prize money, and pathways to production.
We’ve had great results:
- AI in customer support automation
- Natural language front ends on data warehouses
- AI support in treasury for email and payment processing
We encourage teams to form around these ideas, and everything goes through ethics reviews before moving forward.
What’s your experience working with startups and what advice would you give them?
Startups are fantastic. They bring a lot of energy and fresh ideas.
We’ve had great success working with startups to build meta-agent frameworks for product managers, requirement evaluators and generators, and test studios for engineers.
One startup helped us analyze test cases during our SAP migration. That ensured comprehensive coverage and helped us catch potential gaps before going live.
My advice for startups? Understand that big companies have strict procurement and ethics processes. Be ready with the required documentation up front. And share ideas proactively! We don’t always know what’s possible, and startups often see opportunities we don’t.
We’re also working to streamline how we onboard and scale those partnerships more quickly.
Some companies worry that too much experimentation can create chaos or distraction. How has “open innovation” worked in practice at Adobe?
It’s been very positive.
Open innovation has brought teams together from finance, engineering, and product management in ways we hadn’t seen before. It’s also made AI adoption easier. When people are invited to explore and experiment, fear and resistance go down. Curiosity takes over.
Instead of being afraid of AI, people are embracing it faster because they’re encouraged to play with it, ask questions, and see how it applies to their jobs.
If you could wave a magic wand and solve one AI challenge, what would it be?
Content and knowledge management.
Finding, organizing, and making sense of content is still a major hurdle, especially for end users. Most people aren’t prompt engineers. They just want to ask a question and get a useful answer.
AI that helps clean up stale data, flag outdated documents, and surface what’s truly valuable—that’s a huge opportunity for innovation.
How should public company boards be thinking about AI?
Boards need to start with security and governance. They need to understand the importance of clear guardrails around AI adoption.
But they also need to recognize that AI isn’t optional. Companies that ignore it risk falling behind. Boards should push for adoption with intention and oversight.
Will AI shift how boardrooms function?
Governance will evolve.
AI can help analyze board composition, surface gaps in expertise, assess risk profiles, and suggest where additional oversight may be needed.
There’s real potential to bring more intelligence and structure into how boards govern and adapt.
