Why Generative AI is the Dishwasher of B2B Tech

My mother in law visited us earlier this year. She is the biggest fan of our dishwasher. She loves how the dishes come out hot, sanitized, and smelling like nothing. The dishwasher had mastered removing every trace of our aromatic Indian cooking.

15 years ago, though, she didn’t share the same enthusiasm. Back then, the idea that a machine could clean dishes as well as she did by hand just didn’t sit right with her.

When dishwashers first hit the market decades ago, people loved the idea of saving time and effort on a mundane but necessary task. But when it came time to actually buy one, skepticism kicked in. People were accustomed to scrubbing dishes by hand, often considering the tactile and physical act of scrubbing as essential for proper cleanliness. Could a machine really clean as well as human hands? Would it damage the dishes? The enthusiasm they expressed wasn’t enough to translate into purchases—trust was the real driver of adoption.

Fast forward to today, and we’re seeing the same skepticism play out with Generative AI in the world of technology. In customer feedback sessions and surveys, buyers are captivated by the idea of automating tasks, generating content, and boosting productivity. But when it’s time to buy, hesitation takes over. Skepticism about effectiveness, security, and privacy clouds their enthusiasm.

So, how did we move past the initial skepticism with dishwashers? Two things made the difference: better engineering and better marketing.

Better Engineering

With dishwashers, technology improved over time. Machines became more efficient, detergents more effective, and people slowly began to trust that the dishwasher could clean just as well as they could—maybe even better. Generative AI is following a similar path. Right now, the technology isn’t perfect. We still see issues like biased content or material scraped from copyrighted sources. But as engineering continues to improve accuracy, security, and reliability, skepticism will fade.

Better Marketing

But even the best technology won’t sell itself. Dishwashers didn’t just get better—they were marketed better. Campaigns showed people how much time they could save without sacrificing cleanliness. Generative AI requires the same approach. Any technology that changes how we work or live doesn’t achieve mass adoption overnight. It takes enormous time and effort in customer education and guiding early adoption.

Recognize that people will approach the use of AI with different mindsets, characteristics, beliefs, and levels of willingness to use it, particularly in work versus personal life. Plan for this when releasing AI-enabled products or features.

Until the legal and privacy risks are fully addressed, engineering and marketing must work together to mitigate risks for buyers. For instance, product teams can ensure AI recommendations aren’t applied automatically—allowing real human oversight before any AI-generated output is used. At Betterworks, when we infused generative AI into performance reviews, we never positioned it as “let AI take over your performance reviews.” Instead, our message was about "revitalizing your performance reviews with AI as a co-pilot for managers, helping them express expectations clearly and professionally while offering actionable insights to employees."

Just as my mother-in-law eventually embraced the dishwasher, businesses will come to trust AI—driven by persistent efforts from both engineers and marketers. The future is exciting!

Ending this post with a wonderful chart from McKinsey: