We often think of our most brilliant ideas when the house is on fire.
This goes beyond necessity being the mother of all invention, as emergencies in business will often require executives to make huge bets on novel technology.
This is often technology that is unproven in the arena, and sometimes it implodes, but sometimes it works so beautifully that an entire company is saved from the probability of doom reaching 100.
In this inspiring case of a corporate house fire, it was a recently glued together house, still oozing at the seams after the Warner Bros. and Discovery merger in 2022. This is when executives made huge bets on generative AI in the midst of a writer’s strike and numerous other storms.
WBD was not a company full of merger novices by any sense.
In fact, WBD’s CIO Dave Duvall says WBD was “a nesting doll of past transactions, with each integration getting to about 80% before the next one began. The fragmented data and platforms make scaling an AI initiative much harder than it might appear.”
In spite of these challenges, WBD executives bet on AI’s ability to provide the leverage to wedge the company out of a bind on multiple fronts and into the colosseum limelight that is the brutal media landscape of the 2020s.
In a recent piece for MIT Sloan Management Review, authors George Westerman and David Kiron illustrate with great detail how WBD pulled this off.
In fact, they show us how a legacy company’s first two years with AI are spent taking inventory of its own potential.
Rather than a simple inventory of the technology available and its various strategic campaigns, it is an inventory of its own content (for data), workflows (for leverage points), and the limits when creative people will consider handing over their most beloved processes to the machines.
Where It All Began
WBD was seven months into their most recent merger with Discovery when layoffs were ravaging the company as they struggled to get the culture right after blending two very different media giants.
On top of that struggle, strikes were heating up in Hollywood with Writers’ Guilds and Screen Actors’ Guilds members walking out protesting AI creep around 2023, in part due to AI models threatening their jobs that were trained without permission, often on the very types of content WBD owns.
The obvious play for leadership within WBD would have been to take the easy route and push AI heavily as an internal tool to cut costs so the leadership teams could breathe.
The gen AI tools and the models that supported them were getting so good during this time with the rise of ChatGPT post 2022 that adoption turned out to be the easy part.
The use cases were everywhere. The difficult play was fixing the data sewn beneath their surface and the fear flying over their heads, and that focused strategy is why the program survived at all.
There were tons of efficiency initiatives, but what the company lacked was a mission that could re-vitalize the executive team and a creative workforce struggling to pickaxe through a mountain of cost initiatives.
This was happening at the exact moment that the entire media industry was in a philosophical civil war of futurism regarding whether gen AI would displace creative jobs.
What happened next was a perfect example of how gen AI should be positioned: as a growth engine for creators. Many companies in this situation would have positioned it as something being used to cut costs for a workforce that had already gone through two rounds of consolidation, and it would have been ruinous for the culture.
Rebecca Kent, the head of transformation for WBD at the time, played this strategy perfectly as a way to implement AI in the right framing that would inspire employees to find the best use cases to create new IP for WBD, rather than be afraid of it as a cost cutting measure meant to destroy their roles.
They got the creative teams to go as all in as possible on using AI to improve the product without giving up the most treasured parts of the artistic process.
The second decision here was a perfect example of what we also read in McKinsey’s AI Transformation Manifesto a few weeks ago, that business leaders need to own the initiatives with IT serving as the support structure.
Rebecca Kent’s transformation team, boosted by the strength of Matt Chun’s corporate strategy group owned the initiative themselves while IT provided support based on the tooling and architecture needed.
Many leaders in legacy companies today have this totally inverted. While their IT teams nerd out on the newest AI capabilities, company leadership fails to make the jet go supersonic.
Another congruent theme we discussed recently that was also outlined in McKinsey’s AI Transformation Manifesto, appears with how the initiatives to engage with AI tools started at the top of the organization.
Company leaders worked through building a marketing case end to end, complete even with gen AI assisted jingles they created.
It’s hard to believe gen AI tools at this time were producing marketing jingles that were exceptional enough to impress WBD executives, but it must have blown the executives minds on some level, because many bought into the technology.
From this point onward, executive alignment was secured as they began to view it as an imperfect but powerful tool.
Then the team ran workshops across movies, gaming, TV, sports, news, and finance applications, and came back with about one hundred use cases they wanted to explore further.
While this list became a blueprint for future growth with the gen AI technologies, the workshops existed to show a workforce coming out of a strike year that this was happening for real.
This is when a mindset shift was born that helped to propel the company out of the dark wood of the multi-level corporate disaster they found themselves in post 2022.
The Pilots
WBD illustrates for us how we must approach new pilots of AI implementation by working closely with people in the organization who actually have good taste.
This is talked about endlessly online in 2026, how content is now reaching levels of super-abundance, thereby making taste the truly valuable asset.
In this case, WBD used their AI marketing pilot to generate new assets working closely with their marketing team to monitor and judge the outputs.
However, the pilot’s most transformational outcomes had nothing to do with generating asset fodder for social media feeds. The teams in this pilot discovered that WBD could not find its own footage in their databases and a ton of time was being wasted scrubbing through footage.
The company labelled its data on an episodic level that simply stated the names of shows, so finding a usable bit for marketing meant looking through hours of video content.
This is the point the team dedicated themselves to constructing the layer underneath as their primary goal, which contained descriptions at the scene and shot level, tagged for emotion, tone, character, and story location.
One of the greatest outcomes of this was related to data organization (another theme we have researched this month), as the AI did an incredible job at allowing marketers to search databases of footage quickly to find certain scenes they needed for new content, saving endless hours of scrubbing through footage.
The ROI on this endeavor would blow the minds of even the most anti AI executives.
Hilariously, the animation pilot to use AI tools actually failed due to the capabilities of the tools to hold consistency of character faces between scenes.
People may recall the early gen AI videos of Will Smith eating spaghetti (2023), and we imagine the animation pilots probably turned out something like that level of disturbing, even though these pilots started around 2024 so the technology wasn’t as primitive by that time.
By this point it became clear where gen AI impacted the business the most for the creators inside of WBD, as they began using the tools for work far from the finished product and refused to let it touch their primary character work, which they wanted to control to keep the creative artistry intact and pure.
They didn’t want AI generated slop animation to ruin how emotions played out across the screen.
The Outcomes
Two years, three pilots, one shipped tool and one on its way, and Kent says WBD still expects gen AI to transform the media industry, but that the technology for gen AI has improved fastest in areas WBD doesn’t need yet with their current workflows.
So what does this teach us about implementing this new technology in legacy businesses? What WBD managed to create during this time of immense hardship has a greater ROI than the product of any single AI tool.
This was achieved by creating a corporate governance process with a workforce that is charging forward to see how tools can improve their processes, and in turn the product for the customer, rather than something to be an existential threat to creative careers.
If we have learned anything in the wars between the streaming service providers, it is a race to produce the content that will keep audiences enthralled with each new release to keep the monthly recurring revenue flowing with low churn.
Gen AI just so happens to facilitate that, even if it still can’t animate like Walt Disney.
Lastly, resistance to AI adoption follows a pattern in organizations like WBD.
Specifically, the closer the work done by gen AI gets to what the audience will see, the more employees and their love for their craft will hold onto the human element in the loop of the creative process.
Therefore, we should consider that in our own organizations when implementing new pilot programs for AI adoption. It’s all about the framing.
Original Publication:
https://sloanreview.mit.edu/projects/warner-bros-discovery-seeking-growth-with-generative-ai/
G. Westerman and D. Kiron, “Warner Bros. Discovery: Seeking Growth With Generative AI,” MIT Sloan Management Review and EY, July 2026.