When IBM’s Watson computer competed in "Jeopardy!" and beat two of the show’s champions in 2011, the challenge was presenting sophisticated technology that exemplified, rather than threatened, human innovation. Today, as new AI adopters reconsider their skepticism and embrace its capabilities, the space faces a clear feat: Setting expectations.

“People want AI to be able to do what it can’t,” said John Iwata, former chief brand officer at IBM, “and immature technology companies are not disciplined enough to correct that thinking.”

Recently, IBM partnered with filmmaker Celia Aniskovich and B2B agency Transmission on “Who is…Watson? The Day AI Went Primetime,” an 18-minute documentary recounting the "Jeopardy!" event and targeting B2B buyers who are building AI guardrails themselves.

“We aim to position IBM as the architect of responsible, human-centred AI,” said David Reid, vice president of B2B growth at Transmission. “The documentary underscores IBM’s legacy of innovation while framing its role in shaping an ethical, inclusive future for AI, a critical differentiator in today’s competitive landscape.”

Progress that protects brand identity

Watson competed in the game show during three televised episodes, and while the computer didn’t perform perfectly (the computer answered “Toronto” to a question on US cities) it ultimately beat champions Ken Jennings and Brad Rutter.

• IBM's "Jeopardy!" experiment followed Deep Blue IBM beating Chess legend Garry Kasparov in 1997.

“We were very comfortable entering this thing as long as the technology wasn't going to fall completely on its face nor crush the humans in like the first two minutes,” said Iwata.

Still, choosing "Jeopardy!" felt like a bit of a risk, said Iwata, as game shows felt like lighthearted entertainment platforms that couldn’t challenge the computer the way chess did. When weighing the value of every marketing decision, he said considering the long-term brand impact was key.

“The IBM brand was the touchstone to all of our decisions,” he said. “We may not be the fastest technology company in the world, but there is one thing the brand is built on, and that is trusted innovation.”

Bringing relevant storytelling to B2B

The documentary presents the pushback, risks, and aftermath that involved presenting its product on the "Jeopardy!" stage in a modern context.

“Nostalgia is fun, but it’s not very important in business,” said Iwata, who emphasized lessons he learned on B2B marketing and AI that hold up today.

The documentary was grounded in testimonials from former IBM staff, and more B2B players are building narratives around expert commentary. B2B marketers say thought leaders and industry analysts are the most effective influencer types (28%), according to an April Linkedin and Ipsos survey.

AI pushback is a hot topic, and so is creating more entertaining B2B content.

• The biggest concern among leveraging AI tools among adults worldwide is the loss of human jobs, according to a May Kantar survey.
• The primary goal for video marketing is brand awareness (35%), according to an April Linkedin and Ipsos survey.

In an era where AI is perceived as “abstract or intimidating,” this documentary attempts to humanize it while embracing the narrative style that makes B2B brands stand out, said Reid.

Controlling customer expectations

The aftermath of Watson’s "Jeopardy!" was high demand, but IBM positioned it as a research technology instead of a product, which means the sales team wasn’t fully prepared to answer client requests.

“It did catch us by surprise, and it shouldn't have,” said Iwata. “When a bank or airline said, ‘Hey, tell me more about this. We're really interested,’ We could have enabled that team to be ready to have those conversations and capitalize on the interest.”

Since "Jeopardy!" in 2011, IBM Watson hasn’t remained the flashiest player in AI innovation, instead opting to quietly advance in the background. IBM’s latest iteration of Watson is watsonx, a model that is focused on business productivity, and the company is focused on an “ethical framework” that is prioritizing maintaining transparency and mitigating bias in machine learning.

As organizations push for the AI innovation that appeases their consumers, speed can compromise sustainable relevance, said Iwata.

“Trust slows you down, and innovation says go fast and first, even if you fail spectacularly,” said Iwata. “Putting those two things together is not easy.”