Chapter 7 Knowledgeability: Is AI about to make knowledge really cheap? (from the Surfing AI book)

From Duignan, P. (2026). Surfing AI: 30 New Concepts for Getting Your Head Around AI Shock.

One of AI’s effects is reducing the scarcity value of knowledge. We can call this AI knowledgeability, knowledge de-scarcification, or knowledge commodification. Traditionally, the scarcity of knowledge has made its discovery, acquisition, communication, and application valuable. As a result, those who could obtain and apply knowledge have benefited from its scarcity. AI knowledgeability is likely to cause wide-ranging disruption in multiple knowledge-related sectors. At the same time, it is opening up an interesting range of opportunities.

Until now, people’s access to knowledge has been limited by a number of barriers. AI is reducing the effect of each of these barriers in several ways. AI is reducing the cost of discovering knowledge. Discovering knowledge through the scientific process has always been expensive and time-consuming. But now AI is helping scientists make scientific breakthroughs on problems they have struggled with for years. These scientific advances will accelerate as AI becomes more intelligent and is applied to solving more scientific problems.

In addition to scientific breakthroughs, access to information and ideas within the economy is another source of value related to knowledge. A well-functioning market can be seen as an ‘information processor.’ Markets can summarize and communicate a great deal of information about traded goods and services. Specifically, markets can quickly signal the difficulty of producing certain goods and services and the current demand for them. In a well-functioning market, such price information increases the resources allocated to producing goods and services in demand or incentivises developing cheaper substitutes for more expensive items.

It is hard to know the exact longer-term effects of AI’s ability to cheaply collect and analyze vast amounts of information and how this will impact how markets function. How will large numbers of people potentially having more detailed information and predictions about where prices are heading impact markets? As AI systems provide more informational certainty at scale, will it make speculation, for instance, a less attractive proposition in the case of something like commodity futures?

Another key economic issue is the value of proprietary knowledge and innovative ideas. The widespread use of non-disclosure agreements and non-competition clauses in contracts and the effort put into industrial espionage show how much people value protecting knowledge and ideas. AI is now impacting this in interesting and uncertain ways.

If AI can create what are currently seen as proprietary ideas, presumably this will reduce the competitive advantage provided by being able to think up such ideas. It is not clear how things will pan out, but this may lead to people creating AI systems that they will want to keep private because they themselves want to be able to exploit the novel ideas they generate. This could lead to a race to create innovative ideas between private AI systems and those accessible to the public.

Therefore, the value of any knowledge base that remains protected from public access will likely increase. Corporates will take increased steps to protect valuable IP. Indigenous and cultural groups have been focusing on who has access to their cultural knowledge and who can use it for what purposes. The development of AI has shone a spotlight on who owns what intellectual property and how cultural knowledge can be protected.

Research has shown that chatbots can score in the top one per cent on creativity tests. Now that this has translated into AI creating novel ideas for entrepreneurs, it is reducing the value of human-sourced innovative ideas within the entrepreneurial ecosystem.

Another area of AI’s impact on knowledge is the time individuals take to acquire knowledge. Until now, developing expertise in an area has required a long period of study. With AI, it is now much easier for people to acquire knowledge. Equally importantly, the current transmission of knowledge, mainly in the form of text-based material, has not been the most useful learning mode for many people. AI’s capability to tailor education to the optimal format for each student, called CustomEdu in this book, is greatly explaning learning opportunities and widening access to education.

The long time needed to acquire professional knowledge has led to the rise of credentialism. It seems that certain types of credentialism are rapidly becoming less important as AI systems become the authoritative source of knowledge in many domains. The comparative advantage of those with higher degrees may be reduced. A McKinsey report has argued that the value of multi-year credentials may diminish due to AI. This may flow into reducing the wage premium that highly skilled knowledge workers can demand.

Another issue regarding knowledge has been the need for expertise to apply knowledge to particular problems. When given enough detail about a specific situation, AI is adept at providing information on how knowledge can be applied in that instance. We can think of a knowledge pipeline. This consists of knowledge creation, transmission, its learning by experts and the assessment of what such experts know. It also includes the application of knowledge to particular situations through a professional customizing and adapting the knowledge to a particular task.

AI is making each step in the knowledge pipeline more efficient. It increases the production of new knowledge, makes its transmission more efficient, and, lastly, helps to customize and adapt knowledge quickly to any particular situation. Until now, a choke point in the knowledge pipeline has been having enough professionals or experts to customize and apply knowledge. As AI improves at adapting and applying knowledge, this will overcome the chokepoint created by a limited number of highly trained and expensive experts. In a sense, AI is heading towards providing a fully scalable and much more affordable way of replicating scarce human expertise in a wide variety of situations. These will likely include areas such as medicine, law, and engineering.

Another limitation concerning the application of knowledge is that it has, in the past, been siloed into different disciplines. One of the significant advantages of some types of AI is their ability to access and integrate knowledge from across a wide range of different areas. Such systems can look across large tracts of human knowledge and take a multidisciplinary approach when applying knowledge in a particular context.

Language barriers have also been a significant problem in creating, transmitting, and applying knowledge. AI is dissolving language barriers. Until now, the Global North has enjoyed a considerable advantage over the Global South regarding its access to commercially relevant knowledge. This advantage has been amplified in the English-speaking Global North because so much knowledge has been discovered, stored, and communicated in English. For hundreds of millions of knowledge workers in the Global South, AI has now opened up access to vast amounts of knowledge. Equally importantly, because of AI’s ability to translate English and improve the standard of people’s written English, AI will enable people in the Global South to compete on a much more even playing field with knowledge workers in the Global North. This is likely to reduce the comparative advantage of Global North knowledge workers for any knowledge work that can be transacted across the internet in English.

A final aspect of AI’s knowledgeability is how AI’s vast range of knowledge will affect us as humans at the psychological level. Sometimes, when in the presence of a very knowledgeable person, you can feel that there is little point in your talking because they will know more than you about any topic that comes up. Is this same effect about to be created by highly intelligent AI? Will AI have a chilling effect on what humans think they are competent to talk about when in its presence? Will a point come soon where it seems somewhat pointless to discuss anything because AI can have a more sophisticated take on it?

As can be seen, AI is about to disrupt many aspects of knowledge and knowledge work at many levels. AI knowledgeability will reinvent how knowledge is created, stored, transmitted, learned, and applied.