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It seems like just a year ago, access to mass-market, commercially available, genuinely helpful AI tools seemed like a far-off wish.
After all, enterprise software vendors have been extolling the virtues of “advanced machine learning” and “AI engine” tools for years. Lots of promises had been made regarding AI adoption, yet the problems those solutions were ostensibly designed to address remain stubbornly present.
HR executives know that recruiting and applicant tracking systems still deliver lackluster candidate experiences.
Learning & Development pros know that even the most sophisticated “Netflix-like” recommendation algorithms are still missing the mark.
Then ChatGPT hit the scene, and suddenly the AI revolution didn’t seem that far off.
OpenAI released ChatGPT at the end of November 2022, and in short order, we began seeing just how powerful it was. Developers began using it to write code. Ryan Reynolds used it to write a script for a Mint Mobile ad. And in record time, it was everywhere.
Shortly thereafter, “the AI revolution” media blitz began. Stories ran the usual click-bait gamut from dystopian to utopian, but no matter where you turned, one truth became inescapably clear: the AI era was upon us.
There’s no doubt that generative AI is going to have a disruptive impact on the employment landscape, but whether AI adoption is positive or negative is largely up to those tasked with introducing AI into the flow of work.
Department heads and team leaders will certainly play a role in defining how AI will be integrated at a functional level, but Human Resources, Learning & Development, and Digital Transformation pros will be on point for the cultural assimilation… and that’s arguably the most crucial point of impact. Here’s why:
Change fatigue is real.
From sociopolitical upheaval to radical shifts in the way individuals define and experience work, the past several years have been marked by constant change for many, if not most, employees. New policies and procedures have been rolled out, and although many organizations were already on a digital transformation journey pre-pandemic, the rapid shift to remote work added rocket fuel to those plans.
Now we’re asking workers to embrace yet another change, and it could be more daunting than ever.
Tech without context or personal connection is just another app. Even something as powerful and as game-changing as Generative AI can become just something else to learn. Yet another tool the boss is throwing at me to make me work better/harder/faster.
Therein lies the rub.
You can’t put your head in the sand and pretend that AI isn’t going to create tectonic shifts in the workplace, but you also can’t treat technology with such far-reaching implications as “just another app.” AI is fundamentally different.
It may seem counterintuitive, but in the rush to integrate AI into every nook and cranny of our everyday lives, it’s critically important to remember the people behind the tech. To that end, AI training can’t be handled by an old school “watch a video, take a quiz, print a certificate” LMS approach. To make it stick, you have to nail the fundamentals:
- Learn from people, not pixels
Old school “watch this video, take this quiz, print this certificate” video-based training (like you find in most traditional LMS platforms) may be great for compliance purposes or to gain a basic understanding of a topic, but they don’t lead to skills mastery. By contrast, human-led instruction – complete with coaching and mentoring – keeps students engaged, and particularly with a topic like AI, is vital to ensuring employees know the “why” behind the “what.” (In other words, you’ll have an opportunity to ensure they view AI in the right context and regard it as an ally, not a potential job-stealer.) - Learn as a team
One of the fastest ways to ensure any AI implementation delivers sub-par performance is to have “lumpiness” within a team. When one motivated team member acquires Jedi-like skills while the rest lag behind, you’ll have poor execution and poor results. If you train as a team, however, you’ll establish greater consistency across the organization, and – more importantly – the team will have a “lingua franca” surrounding all things AI. This will also unlock the creativity of the team, together discovering new ways to implement AI and use it to extend their own capabilities. - Learn by doing
Nothing drives home the power and potential of AI in the workplace like getting practical, hands-on time with the tools and working on real-world projects. From simple prompt engineering to more complex process automation processes, when employees get a chance to roll up their sleeves and actively solve problems together, the lessons and the learning will stick. When you add mentors to the mix – individuals with “been there, done that” expertise – the return is amplified.
At the end of the day, AI just isn’t about new tech and tools. It’s about people. Whether your employees regard it as the monster under the bed waiting to steal their jobs or as a time-saving and performance-improving resource is largely how it is introduced and embraced… and that ultimately comes down to how they’re trained.
Since you’re here…
Springboard for Business grows businesses by empowering leaders and their teams with the critical thinking, data, and technology skills central to the future of work. Companies like Amazon, Walmart, HP, JPMorgan Chase, and Visa have partnered with Springboard for Business to upskill and reskill employees around the world. Click here to learn more.
