Entrepreneurship, Inequality, and the Impact of Artificial Intelligence
The last few years have marked a lot of excitement, and some fear, about the potential of artificial intelligence. More recently, with the launch of language tools like Chat GPT and Bing AI, entrepreneurs are reconsidering what additional value or impact they might create now that these chatbots have the ability to automate many of their daily tasks. While there is no doubt that businesses of all kinds will be impacted, especially as these tools become increasingly sophisticated and trusted, not all entrepreneurs will be impacted in similar ways.
Businesses founded within an environment of resource scarcity, versus those that have more resources at hand, tend to operate differently. Underserved entrepreneurs often start businesses in which they trade their time directly for compensation to meet their immediate needs. Even as they expand, the same operating model typically prevails–owners’ and employees’ time, in one form or another, is given in exchange for payment. But the most successful businesses find ways to operationalize, automate, and “scale,” to use the language of venture capitalists.
The weight of these differences increases when we consider that there already exists significant digital divide among business owners. While many technologically sophisticated entrepreneurs and their teams—especially those with scalable businesses—stand to benefit from the new opportunities that AI provides, it is less clear what will happen to those whose businesses provide everyday products and services that have lower levels of technological sophistication.
There are at least three perspectives that can help assess the potential impact of AI on equity within business ownership and entrepreneurial success:
AI as a business resource
On the surface, it may seem that the use of AI tools as business resources is low hanging fruit for those who already have scalable operating models. It allows them to automate tasks even further, and even avoid hiring for certain roles to preserve capital. Social media platforms, such as Twitter, have benefited from artificial intelligence and machine learning for years to make product improvements.
However, there are many tasks that entrepreneurs across every sector can potentially automate using AI tools, even if they don’t not have access to Twitter-level deep learning algorithms. For example, realtors are utilizing AI to create property descriptions, and Quickbooks, an accounting software used across businesses of all sizes, now touts its ability to “leverage data and the most advanced AI models to reduce manual work [and] serve up cash flow insights.” This saves entrepreneurs significant time in accounting-related tasks.
All entrepreneurs should have equal access to these types of AI. The key to ensuring its ubiquity is to help entrepreneurs understand how those tools fit their specific operations. Here, those of us who train and support entrepreneurs have a key role to play.
Inevitably, certain tasks of entrepreneurs and their employees are likely to be completely overtaken by AI-enabled resources. However, in other domains where human interactions remain, entrepreneurs investing in the human elements of service excellence can use this to stand out and compete.
AI enabling a new way of learning
Access to knowledge is one of the most persistent gaps between underserved communities and more affluent ones. One’s education has always been thought of as a proxy for their level of knowledge, capabilities, and marketability. However, the internet has already democratized access to knowledge, and highly motivated individuals are able to find and utilize educational resources online at no cost. In all likelihood, access to AI tools will further simplify access to knowledge-based resources.
Even though the current, more nascent versions of AI tools have some limitations in terms of the information they provide, it is only a matter of time before these issues are resolved. In this way, AI has potential to further democratize access to knowledge.
What one needs to know to start a business will become increasingly available to those who seek it online. Aspiring entrepreneurs from all backgrounds will be able to readily access both industry-specific information related to their interest, as well as more generalized material about running a business. They may have to “learn how to learn” in the AI-enabled environment, but access to these learning resources will no longer be limited to those with a formal education.
Innovation capability
Perhaps the most exciting opportunity that novel AI provides comes in the form of enabling new innovations. Currently, most of the excitement surrounds areas such as drug discovery, diagnostics, environmental protection, and education.
But, there is also high potential for AI to further exclude those who have been left out of innovation systems in the past. Using AI for the creation of something truly novel requires complex prior knowledge of systems, applications, and data science. Indeed, it is possible that those who have been excluded from the innovation systems of the past will have an even harder time becoming creators of novel solutions in the increasingly complex systems of the future. Those at the margins of the business ecosystem may benefit from the basic usage and application of AI tools, but their participation in innovation development and technological transformation as creators will likely remain limited.
Ultimately, even if AI tools can simplify information access or task automation for all entrepreneurs, it is unlikely that their development will immediately make it easier for aspiring entrepreneurs from underserved communities to succeed. In fact, many AI tools may replace some jobs and negatively impact small business opportunities in areas that are characterized as repetitive knowledge work.
For those small business entrepreneurs who are able to find and pursue opportunities in this new landscape, AI tools can simplify many tasks, provided that these tools are not prohibitively expensive for them to acquire. At the same time, without structural and systemic changes that purposefully bring diversity of backgrounds to innovation processes, it is hard to see how AI in a vacuum could promote equal access to the cutting edge of innovation.