• Shutterstock added gen AI to its stock-content library to generate $104 million in revenue.
• The company has partnered with tech giants including Meta, Amazon, Apple, OpenAI, and Nvidia.
• This article is part of "CXO AI Playbook" — straight talk from business leaders on how they're testing and using AI.

Shutterstock, founded in 2003 and based in New York, is a global leader in licensed digital content. It offers stock photos, videos, and music to creative professionals and enterprises.

In late 2022, Shutterstock made a strategic decision to embrace generative AI, becoming one of the first stock-content providers to integrate the tech into its platform.

Dade Orgeron, the vice president of innovation at Shutterstock, leads the company's artificial-intelligence initiatives. During his tenure, Shutterstock has transitioned from a traditional stock-content provider into one that provides several generative-AI services.

While Shutterstock's generative-AI offerings are focused on images, the company has an application programming interface for generating 3D models and plans to offer video generation.

Situation analysis: What problem was the company trying to solve?

When the first mainstream image-generation models, such as Dall-E, Stable Diffusion, and Midjourney, were released in late 2022, Shutterstock recognized generative AI's potential to disrupt its business.

"It would be silly for me to say that we didn't see generative AI as a potential threat," Orgeron said. "I think we were fortunate at the beginning to realize that it was more of an opportunity."

He said Shutterstock embraced the technology ahead of many of its customers. He recalled attending CES in 2023 and said that many creative professionals there were unaware of generative AI and the impact it could have on the industry.

Orgeron said that many industry leaders he encountered had the misconception that generative AI would "come in and take everything from everyone." But that perspective felt pessimistic, he added. But Shutterstock recognized early that AI-powered prompting "was design," Orgeron told Business Insider.

Key staff and stakeholders

Orgeron's position as vice president of innovation made him responsible for guiding the company's generative-AI strategy and development.

However, the move toward generative AI was preceded by earlier acquisitions. Orgeron himself joined the company in 2021 as part of its acquisition of TurboSquid, a company focused on 3D assets.

Shutterstock also acquired three AI companies that same year: Pattern89, Datasine, and Shotzr. While they primarily used AI for data analytics, Orgeron said the expertise Shutterstock gained from these acquisitions helped it move aggressively on generative AI.

Externally, Shutterstock established partnerships with major tech companies including Meta, Alphabet, Amazon, Apple, OpenAI, Nvidia, and Reka. For example, Shutterstock's partnership with Nvidia enabled its generative 3D service.

AI in action

Shutterstock's approach to AI integration focused on the user experience.

Orgeron said the company's debut in image generation was "probably the easiest-to-use solution at that time," with a simple web interface that made AI image generation accessible to creative professionals unfamiliar with the technology.

That stood in contrast to competitors such as Midjourney and Stable Diffusion, which, at the time Shutterstock launched its service in January 2023, had a basic user interface. Midjourney, for instance, was initially available only through Discord, an online chat service more often used to communicate in multiplayer games.

This focus on accessibility set the stage for Shutterstock.AI, the company's dedicated AI-powered image-generation platform. While Shutterstock designed the tool's front end and integrated it into its online offerings, the images it generates rely on a combination of internally trained AI models and solutions from external partners.

Shutterstock.AI, like other image generators, lets customers request their desired image with a text prompt and then choose a specific image style, such as a watercolor painting or a photo taken with a fish-eye lens.

However, unlike many competitors, Shutterstock uses information about user interactions to decide on the most appropriate model to meet the prompt and style request. Orgeron said Shutterstock's various models provide an edge over other prominent image-generation services, which often rely on a single model.

But generative AI posed risks to Shutterstock's core business and to the photographers who contribute to the company's library. To curb this, Orgeron said, all of its AI models, whether internal or from partners, are trained exclusively on Shutterstock's legally owned data. The company also established a contributor fund to compensate content creators whose work was used in the models' training.

Orgeron said initial interest in Shutterstock.AI came from individual creators and small businesses. Enterprise customers followed more cautiously, taking time to address legal concerns and establish internal AI policies before adopting the tech. However, Orgeron said, enterprise interest has accelerated as companies recognize AI's competitive advantages.

Did it work, and how did leaders know?

Paul Hennessy, the CEO of Shutterstock, said in June the company earned $104 million in annual revenue from AI licensing agreements in 2023. He also projected that this revenue could reach up to $250 million annually by 2027.

Looking ahead, Shutterstock hopes to expand AI into its video and 3D offerings. The company's generative 3D API is in beta. While it doesn't offer an AI video-generation service yet, Orgeron said Shutterstock plans to launch a service soon. "The video front is where everyone is excited right now, and we are as well," he said. "For example, we see tremendous opportunity in being able to convert imagery into videos."

The company also sees value in AI beyond revenue figures. Orgeron said Shutterstock is expanding its partnerships, which now include many of the biggest names in Silicon Valley. In some cases, partners allow Shutterstock to use their tech to build new services; in others, they license data from Shutterstock to train AI.

"We're partnered with Nvidia, with Meta, with HP. These are great companies, and we're working closely with them," he said. "It's another measure to let us know we're on the right track."

• Alaska Airlines partnered with Air Space Intelligence to use an AI tool that suggests flight routes.
• The tool, Flyways AI Platform, factors in data such as historical flight traffic and predicted weather.
• This article is part of "CXO AI Playbook" — straight talk from business leaders on how they're testing and using AI.

For "CXO AI Playbook," Business Insider takes a look at mini case studies about AI adoption across industries, company sizes, and technology DNA. We've asked each of the featured companies to tell us about the problems they're trying to solve with AI, who's making these decisions internally, and their vision for using AI in the future.

Coordinating airline flights seems easy on paper. Nearly all travel routes are planned months in advance, and they're designed to ensure there aren't too many aircraft flying at one time. But frequent airline delays show that this seemingly simple task can become mind-bogglingly complex.

One out of every five flights in the US is delayed by at least 15 minutes. "The fundamental problem is that when a human being sits down to plan a flight, they only have information about their one flight," Pasha Saleh, the head of corporate development at Alaska Airlines, said.

To solve that, Alaska Airlines partnered with an AI startup called Air Space Intelligence, the creator of the Flyways AI Platform, which uses artificial intelligence to suggest optimal flight routes. The partnership started three years ago and was renewed in August. Now, half the flight plans reviewed by Alaska Airlines' dispatchers include a plan suggested by Flyways.

Situation analysis: What problem was the company trying to solve?

All major airline flights are logged with the Federal Aviation Administration and generally filed at least several hours ahead of time. Most commercial passenger flights follow common routes flown on a schedule.

In theory, that means air traffic is predictable. But the reality in the air is often more hectic. Saleh said that air-traffic control is "often very tactical, not strategic."

That leads to last-minute diversions and delays that inconvenience passengers and cost Alaska money as pilots, crews, and planes sit idle.

"Airplanes are expensive assets, and you only make money when they're flying," Saleh said.

Key staff and partners

Alaska Airlines and ASI worked in partnership from the beginning of the partnership.

Saleh met Phillip Buckendorf, the CEO of Air Space Intelligence, in 2018. Buckendorf wanted to use AI to route self-driving cars. Saleh wondered whether the idea could be applied to airlines and invited Buckendorf to visit Alaska Airlines' operations center.

"He looked at those screens expecting to see something out of 'Star Trek.' Instead, he saw something one generation removed from IBM DOS," Saleh said, referring to an operating system that was discontinued over 20 years ago. "Pretty much on the spot, he decided to pivot to airlines."

The resulting product, Flyways, was adopted by Alaska Airlines in 2021.

While Air Space Intelligence developed the Flyways AI Platform, it did so in close cooperation with the airline's stakeholders.

"Airlines are very unionized environments, so we wanted to make sure this wasn't seen as a threat to dispatchers," Saleh said. Alaska Airlines used dispatcher feedback to hone Flyways.

Flyways now works as an assistant to the airline's dispatchers, who see its options presented when creating a flight plan.

AI in action

The partnership between Alaska Airlines and Air Space Intelligence began with a learning period for both organizations.

ASI's staff shadowed the airline's dispatchers to learn how they worked, while Alaska Airlines learned more about how a machine-learning algorithm could be used to route traffic. Saleh said ASI spent about 1 ½ years developing the first version of the Flyways AI Platform.

Flyways trains its AI algorithm on historical flight data. At its most basic level, this includes information like a flight's scheduled departure and arrival, actual departure and arrival, and route.

However, Flyways also ingests data on less obvious variables, like restricted military airspace (including temporary restrictions, like those surrounding Air Force One) and wind speeds at cruising altitude. Even events like the Super Bowl, which causes a surge in demand and leads to airspace restrictions around the event, are considered.

Saleh said Flyways connects to multiple sources of information to acquire this data and automatically ingests it through application programming interfaces. Flyways then runs its AI model to determine the suggested route.

"Suggested" is a keyword: While Flyways uses AI to predict the best route, it's not an automated or agentic system and doesn't claim the reasoning capabilities of generative-AI services like ChatGPT.

Dispatchers see Flyways' flight plans as an option in the software interface they use to plan a flight, but a plan isn't put into use until a human dispatcher approves it.

Did it work, and how did leaders know?

Alaska Airlines' dispatchers accept 23% of Flyways' recommendations. While that might seem low, those accepted routes helped reduce Alaska Airlines' fuel consumption by more than 1.2 million gallons in 2023, according to the airline's annual sustainability report.

Reduced fuel consumption is necessary if Alaska is to reach its goal of becoming the most-fuel-efficient airline by 2025. The airline also ranks well on delays: It was the No. 2 most-on-time US airline in 2023, with some of the fewest cancellations.

Meanwhile, ASI has grown its head count from a handful of engineers to 110 employees across offices in Boston, Denver, Poland, and Washington, DC. In addition to its partnership with Alaska, the company has contracts with the US Air Force and received $34 million in Series B funding in December from Andreessen Horowitz.