Generative AI Workforce Transformation: A 3D Framework

I’m fortunate to work with visionary Chief Data Officers at Fortune 500 companies through Workera. Over the last six months, their #1 mandate has been to transform their organization toward embracing Generative AI. My role has been to help them execute their vision specifically through the talent lens: How to expedite the transformation of the workforce?

To distill it down, there are three simple dimensions that consistently emerge across these leading corporations as critical to unlocking Generative AI's full potential: Innovation, Productivity, and Risk & Security.

• Innovation: Through Generative AI, businesses can fast-track their product development, roll out new features, and either cut costs or boost revenue by securing new clientele. For example, Accenture –?quite a visionary company from a talent management perspective – reportedly landed over $100M in Gen AI contracts in only four months. Impressive, right?! This is about building elite technical teams, but most Fortune 500 companies still struggle. They agree that hiring Generative AI talent is not the right strategy, given the small supply and the large demand for this talent. Instead, they invest in developing in-house Generative AI expertise. They pinpoint the gaps within their technical and technical-adjacent teams, establish and harmonize ambitious skills objectives, offer their staff with personalized feedback and upskilling plans to bridge any capability gaps in technical areas like large language models, prompt engineering, and production-grade AI skills.
• Productivity: Generative AI is swiftly augmenting – and in some cases, automating – various job tasks. For enterprises aiming to stay nimble, workforce planning and productivity improvements are key. Imagine the cost benefit of a 1% productivity improvement on 100,000 employees. Internally at Workera, we’ve estimated 20-40% productivity improvements on coding tasks like documenting code, simple debugging, translating between programming languages, basic imports, and simple refactoring. I expect the boost is likely much larger on other tasks like text summarization, document question answering, or basic data cleaning. To increase productivity, enterprises identify the skill gaps in their extensive workforce related to Generative AI usage. They assess in areas like Generative AI foundations, digital literacy, AI literacy, prompt engineering, and in a variety of software tools like ChatGPT.
• Risks and Security: Handing over Gen AI tools to employees isn't without its risks, but these can be substantially mitigated through targeted training and certifications. Workera ensures that before any staff engages with Gen AI technologies, they are not only well-prepared but also certified, setting a baseline of competency and safety for enterprise operations. I suggest an initial certification level in Generative AI comprising two key assessments: one focusing on ChatGPT that includes topics on security risks and ethical considerations, and another centered on the Foundations of Generative AI, which dives into a diverse range of applications, best-use scenarios, and limitations. And, a second-level certification to hone in on optimizing Generative AI usage, featuring assessments on Prompt Engineering and Large Language Models. For those aiming to excel in using AI or Generative AI responsibly, my final recommendation is to complete the third level of certification featuring the popular suite of Responsible AI assessments. Additionally, I recommend rewarding employees upon achieving certification with perks like access to specialized tools.

I’ll try to unpack these key dimensions in greater detail shortly, so stay tuned!