Ada Lovelace Was a Marketing Genius, Too

The world’s first computer programmer could also be described as a pioneer in B2B technology marketing. Her wisdom and discerning insights into the potential of technology not only advanced science but also serve as a guiding light today for those of us tasked with articulating to others tech’s potential. Lovelace was an aristocrat, fortunate to study mathematics in the early 19th Century. Her mother, also a mathematician, believed what we might call a STEM education could prevent Ada from following in the footsteps of her father, the sensual Romantic poet Lord Byron. Lovelace began studying Charles Babbage’s prototype digital computers in the 1830s. And don’t get thrown off to that reference to digital. Today “digital” suggests electrons moving around. But here digital means reducing the world to ones and zeroes to better compute what’s going on in it, rather than figuring things out via analogs. Read Walter Isaacson’s The Innovators, for an excellent history of the people who advanced computing for the details. Here’s where the marketing comes in What cemented Lovelace’s place in history in 1843 was her translation and ridiculously extensive annotation of an Italian mathematician’s article on Babbage’s Analytical Engine. Despite her mother’s efforts, Lovelace inherited her father’s gifts with the pen. Her science was like verse. “The Analytical Engine weaves algebraic patterns just as the Jacquard loom weaves flowers and leaves,” she wrote in one of her notes in the article. The substance of her thoughts was even more powerful. Her annotations envisioned applications of the Analytical Engine that went beyond basic calculations, creating the first known computer program with an algorithm that produced Bernoulli numbers. Her contributions remind us of the importance of an often-overlooked tool in tech: human perspective. Rather than focusing solely on the nuts and bolts of a remarkable innovation, she considered its applications. She perceived new worlds where the benefits of technology could be brought to fruition. These insights are extremely important for the future of enterprise AI. Advancements in AI, machine learning, and other technologies have promised ambitious but too-often-unrealized advancements for organizations in many industries. Many of those advancements have yet to be achieved not because AI is incapable of performing them. Rather, too few companies have created AI-enabled applications that busy professionals can integrate into their workflows without significant training, teams of data scientists or other accommodations. Until the hype cycle around generative AI achieved liftoff, selling AI in a general sense wasn’t really moving the industry forward. In other words. business solutions that AI makes possible was the name of the game. Generative AI has changed that game, but its utility will still be expressed most tangibly through business solutions. And it will be what business solutions can and can’t do that will ground the conversation. You might accuse me of sidestepping consumer applications, and you would be right. But let me save that for a future piece. First tech white paper? Lovelace foresaw the distinction. When she wrote her groundbreaking notes, Babbage and his colleagues were hoping that the British government or others would finance the completion of his complicated machines. Unfortunately, they never received it, though researchers have been seeking to replicate and finalize his inventions in the 150 years since Babbage died thanks in part to Lovelace’s notes. And today marketers might call those notes a white paper, or a document that aims to both inform readers – usually prospective customers or partners – about a complicated technical subject and persuade them of its utility in solving problems. It’s a translation and explanation of a solution, one might say. While Babbage and his team were concentrated on the nuts and bolts of their engines, she was busy showcasing their work to the rest of the world and describing its material benefits to potential users. She was on the frontlines. That’s where B2B marketers in enterprise AI need to devote their attention today. When the sugar high of generative AI fades, it will still be delivering understated but significant value in business operations in a wide variety of industries today, from clinical trials for pharmaceutical development, to consumer lending, to manufacturing. Much of that value will originate in incremental advances with AI that don’t garner headlines because it may be more on the user interface side. The momentum is clear, however. AI is at the center of the digital transformations changing the global economy today. B2B marketers should take a page from Lovelace and clarify just how big it can be, and what stands in the way.