With the explosion of advancements in Artificial Intelligence (AI), the demand for AI-literate knowledge workers is rising. Achieving and maintaining AI literacy requires continuous learning and consistent use of AI technologies.
Artificial Intelligence and Knowledge Workers
The pervasiveness of AI in our lives – both personally and professionally – raises concerns that machines are taking over our jobs. A look back at the effect assembly lines had on productivity and the economy more than a hundred years ago may help to dispel those fears. Today, AI brings that level of revolutionary innovation to knowledge work.
Just like a manufacturing assembly line relies on planning, training, and specialized skills to function optimally, so does AI. Knowledge workers – people who use their knowledge to solve problems of varying complexity – will work alongside AI. The knowledge worker’s optimal use of AI will depend first on understanding its capabilities. Then, the knowledge worker can discern the best way to collaborate with AI by leveraging its efficiency and its specialized applications.
The challenge in creating a balance between AI’s capabilities and the skills of the knowledge worker is the pace of advancement. AI is on a trajectory to advance exponentially. The knowledge worker who stands a chance of keeping up will be the knowledge worker who commits to continuous learning.
Build AI Literacy
Building AI literacy can be compared to attaining language literacy. You start with general awareness, gain practical experience within a familiar and safe environment, and increase your confidence to explore and experiment.
The knowledge worker’s general awareness of AI happens automatically due to the pervasiveness of intelligent automation and the AI-infused software they use every day. It’s like a child hearing the alphabet song and then being able to sing it before they even know how important it is to know their ABCs.
Refining awareness happens through practical use. A best practice for practitioners and business teams is to pilot AI with an isolated use case. This structured approach provides purpose and a familiar context where awareness of AI can naturally evolve into an understanding of AI.
This systematic approach results in consistent hands-on experience. It inherently focuses efforts on a specific set of AI solutions and innovations, effectively mitigating the problem of sorting through the proliferation of AI solutions and innovations.
Piloting AI within an existing workflow is like using vocabulary words to build meaningful sentences. The practical application of AI to a real process or a real problem refines the foundational awareness of AI. It leads to understanding how AI is used, and how to use it.
Continuous learning will build AI literacy, from comprehension to competency to mastery.
Learn from Reliable Resources
As ubiquitous as AI is, so too are resources for learning about AI. The sheer amount of advice and information about AI is overwhelming. Choosing the most relevant and reliable resources is a personal journey.
You do not have to read everything about AI that comes across your feed. Once you find a resource that appeals to you, use that resource for a period of time. Use it consistently. Asses its value and the degree to which it provides consistent, accurate, and current information. Does it provide actionable advice and opportunities to engage? Is it formatted to be both flexible and focused? Does it purport a philosophy that is aligned with yours?
Formulate a learning plan you’ll be able to commit to and establish criteria for your personal learning objectives. For example, limit yourself for a period of time to learning about AI that is relevant to a specific use case, as mentioned above. Or you might study AI solutions related to your area of expertise, such as marketing, customer service, project management, or content creation.
The objective is to find a few reliable resources that you deem worthy. These might come in the form of influencers on LinkedIn, or established experts who publish regular blog posts, podcasts, videos, and newsletters.
As you build and maintain AI literacy, you may outgrow some of your resources. That’s a good sign. You may go from learning from reliable resources to being a reliable resource!
Maintain Momentum
Maintaining your momentum in building AI literacy requires continual exploration and experimentation. You are no longer at the stage of having a tool and looking for a place to use it. You now have experience using AI tools for specific use cases and to some degree, you understand their capabilities (and limitations). You recognize the potential impact of AI on traditional workflows.
The key now is to keep using AI. Continue identifying the best resources for building your AI literacy. Look for more use cases within your area of influence. Involve others in your organization who could learn from your experience. If you’re not already part of your organization’s AI council, consider how you might contribute to their initiatives.
As long as you continue to use AI, you will continue to build your AI literacy. You will be exposed to advancements in existing AI solutions, and you’ll seek opportunities to use AI to complement your knowledge and expertise.
By using AI – by collaborating with AI – you are training AI to be the best it can be, while it is enabling you to be the best you can be.