Generative AI: now is the time to ‘learn by doing’

By Bryan Kirschner, Vice President, Strategy at DataStax

Today, we’re all living in a world in which “humans with machines will replace humans without machines”—for the second time. The first time around, smartphone apps became ubiquitous and indispensable machines that just about everyone uses to get things done. This time, generative AI applications will become ubiquitous and indispensable machines that just about everyone uses to do things on their behalf.

Mobile’s destiny as a “front door to the business” and a mainstage for delightful customer experiences wasn’t obvious to everyone in its early days. It took former Microsoft CEO Steve Ballmer, for example, nearly a decade to publicly express regret for his famously dismissive opinion of the iPhone at its launch.

But the jury is already in on generative AI.

ChatGPT has been proven to deliver double-digit gains in speed and quality for knowledge workers (even when just used “off the rack.”) Generative AI can already outperform medical doctors head to head on high-quality and empathic answers to patient questions.

And the technology and tooling will only get better.

In short order, every new employee will show up with apps like ChatGPT on the phone in their pocket. Every customer will know generative AI from the productivity apps or the browser they use at school or work (and from support chats with just about every company they interact with).

We can also count on some generative AI new entrants that are equivalent to the Instagrams, Ubers, and Spotifys of the mobile transition to reshape expectations in surprising (and, frankly, for most of us as consumers, delightful) ways.

The only question at hand is whether any given organization, yours included, stands out as being particularly good or bad by comparison.

The good news: Your people are likely to be ready, willing, and able to embrace generative AI and figure out ingenious ways to better do their jobs and service your customers. In a survey of 500 IT leaders and practitioners released today, only 2% of respondents consider it a threat to their careers. By contrast, 61% said they believe that AI will “greatly enhance” their careers or create new opportunities.  And your technical leaders and hands-on practitioners—rightly, in our view, as I wrote about previously—aren’t intimidated by generative AI applications: More than half are “very” or “extremely” confident that they have the skill set to build generative AI applications.

And CIOs are already playing a vital role in putting enthusiasm and talent to work: 43% said that AI strategy is led by IT.

But there’s a critical misunderstanding to watch out for that surfaced in another recent survey. BCG found that 52 percent of CEOs agreed with the statement: “We do not fully understand GenAI and actively discourage its use across our organization.”

Here’s the rub: Today, no one fully understands generative AI. The pattern for success at learning how to create value safely and responsibly is a mindful culture of experimentation and thoughtful “learning by doing.”

Organizations that hold back on coming to an understanding of how to apply it, in their context, will earn the worst of both worlds: You still won’t understand it, and your proactive competitors will steal a march.

Pick some enabling metaphors and guardrails (such as the “eager intern” or “autonomous agent”). Appoint some champions for governance through “policing, coaching, and refereeing.” And get people going with collaboration, openness, and curiosity. No one today wishes they’d taken mobile less seriously or moved more slowly. In the very near future, the same will be true for generative AI.

Download The State of AI Innovation report to learn how 500 IT leaders and practitioners rely on AI for productivity, the challenges they face, and the tools they trust to drive innovation.

About Bryan Kirschner:

Bryan is Vice President, Strategy at DataStax. For more than 20 years he has helped large organizations build and execute strategy when they are seeking new ways forward and a future materially different from their past. He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing.

Artificial Intelligence, Machine Learning