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It’s the end of knowledge work; long live wisdom work

Long Live Wisdom Work | Edgar Allan | Blog

Let’s start with the bad news: the specific applications of new AI technologies are in a state of constant flux. As Open AI continues to make rapid advancements that outpace whole swaths of startups, we can’t always know exactly what shape new AI-powered workstreams will take. 

The good news, however, is that nearly everyone agrees that there’s a deeper upheaval in motion and that its broad outline is becoming clearer by the day.

As the information age draws to a close, how can organizations best prepare for the dawn of the wisdom age? They can start by understanding the core difference between knowledge and wisdom work and how value is delivered in this emerging framework.

What is knowledge work?

Knowledge work sits on top of knowledge tools, which are so ubiquitous that it might be faster to name what’s not a knowledge tool. As an example, there are all kinds of tools that facilitate visual design. But to get an actual design created, you need someone who has absorbed a large amount of knowledge about design, mastered the craft, and knows how to use those tools. 

In knowledge work, we see the intersection of two core pieces of our present economy: 

  1. Companies that make and manage knowledge tools 
  2. Companies that sell their expertise with those tools as a service to others

What is wisdom work?

AI applications promise to upend these two intersecting items because the AI can both make and operate tools to create an end product … sort of. This is where wisdom work comes into play. AI apps are only as good as the info they consume and their prompts, which means a human needs to add the right strategic insight to guide what to build and how to optimize it.

What does this mean for those of us working in the information age? 

From this vantage point, what AI effectively eliminates is the repetitive, repeatable aspects of current knowledge work. What remains is a strong need for strategic intervention and continuous improvement. Rather than toil away at creating one end product, service and product companies can facilitate rapid innovation for clients in hyper-cycles of iteration.

Collectively, our basic objective remains unchanged: to help solve business challenges for clients. However, the technology that informs the tools we use to accomplish that will be changing at a much faster pace, meaning you will need to move even faster while vertically integrating your organization at the same time.

In other words, prepare to build and rebuild products as you continually guide clients on how best to use them in the present moment. 

Another thing that hasn’t changed but will be pulled into stark focus in our world: Rather than pure consulting or products for their own sake, the only real item for sale is solutions to problems. For us, as an example, we’ve built (and continue to evolve) an AI-augmented Javascript layer for Webflow, which we also help our clients manage to their advantage. 

The possibility is just incredible. And things are moving so much faster than before. What used to take years to develop now takes months or even weeks. And we at EA are focused on the intersection of marketing sales and products, so we’re here to help you navigate this brand new space as we continue to navigate it ourselves. 

Interested in partnering with Edgar Allan to create a branded large language model, on how to use AI in your agency, or on a web design, brand, or content design project? Get in contact with us today.

Did you enjoy this article? Read more like it on the Edgar Allan blog.

More articles from Edgar Allan on AI:

AI: Friend or foe?

Introduction to branded large language models

How to prep your marketing org for branded large language models

Asteroid or dinosaur - pick one (exploring the implications of AI to agencies)

Driving growth with programmatic no-code

Creating digital artwork using custom code and AI with Slater 

Slater early-release: An open letter to the community

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