A.I. and the Fundamental Force of Business

Humanity has been characterized by periods of large societal leaps, powered by revolutions that have fundamentally changed our societal structures and the way businesses operate. From the Industrial Revolution that brought mass replication of products to the forefront to the expansive universe of communication unlocked by Web 1.0 and 2.0, we have continually broken barriers and forged pathways to uncharted territories. Now, we find ourselves on the cusp of an A.I. Revolution—a seismic shift that ventures into realms previously exclusive to humans. Despite the efforts of many to do so, the effects of this shift cannot be easily overstated. A.I. and automation are often mentioned in the same breath, but the transformative change from A.I. goes far beyond automation cuts deeper and into the underlying fundamental force of business–agency, or the ability to make decisions and take action, which can now be replicated at scale in increasingly profound ways. You might think that I’m being melodramatic by comparing people and machines doing some stuff to the fundamental forces of gravity, electromagnetism, and the nuclear forces (yes, I just watched Oppenheimer), but I disagree. Those physical forces are constant, whereas by replicating the concept of agency we have the potential to manipulate and amplify this powerful force to a seemingly unlimited extent. 

The Evolution of Agency in Business

Agency is at the core of any functioning entity. It entails making decisions and taking requisite actions, steering the trajectory of businesses toward success and innovation. Traditionally in the business world, agency was merely an obvious–and therefore often unspoken–function of humans, honed through experience and skill. The concept of agency as a fundamental force in business has been taken for granted to such an extent that people still debate, for example, the most important factor for the success of a startup, as if the founders and the overall team weren’t clearly the most important factor. After all, of the many things that need to go right for a new business to succeed, nearly every one of them originates with the decisions and actions of people–or at least as far as we’ve seen to date. However, the advent of artificial intelligence has irreversibly altered this landscape, imbuing machines with a level of agency that places us incredibly close to an inflection point in an exponential curve where products, and even companies themselves, are increasingly guided by “decisions” made by computers at a runaway pace.

From Mass Production to Mass Agency

Historically, each transformative era introduced scale — the Industrial Revolution championed mass production, Web 1.0 facilitated mass communication, and Web 2.0 initiated mass interaction. (Sorry, Web3, but I need to see more from you.) Today, the A.I. Revolution heralds the age of mass agency, where machines can not only replicate human actions but also simulate human decision-making, engendering a reality where business operations are exponentially scalable, efficient, and precise. Essentially, if agency is the fundamental force of business, then a human can be thought of as an indivisible building block of business just as the atom was once thought of as the fundamental building block of matter. However, just as we have learned about quarks and have theorized things like quantum fields (which I don’t understand in the slightest), computer scientists have made significant strides in the fields of data science, computer vision, and natural language processing, which are breaking down agency to its constituents at an unnervingly breakneck pace. We’re still not there yet, and many leading A.I. experts like Meta’s Yann LeCun like to point out the many limitations of A.I. as it now exists (especially when it comes to large language models, or LLMs, like ChatGPT), but no one really knows where we stand on the exponential curve. So, while the timing and nature of that inflection are still unknown, the fact that it is coming soon from an historical time frame seems almost certain. 

A.I. in Action: Decoding Decision-Making and Agency

Understanding the implications of the A.I. revolution requires us to delve into the mechanics of how artificial intelligence is reshaping decision-making and agency. Let’s explore a couple domains, factory operations and human resources, where A.I. is already translating data into insightful actions, and at a scale previously unimaginable:

Factory Operations

The integration of A.I. technologies has allowed factories to become more efficient, flexible, and autonomous, ushering in the era of smart manufacturing or Industry 4.0. Below are several ways in which AI has transformed factory operations in areas like predictive maintenance, quality control, energy management, robotics, and more. An interesting case study I’ve come across is that of Pepsico partnering with Microsoft to build machine learning capabilities into its Cheetos extruder machines, enabling real-time adjustments to optimize the meticulously fine-tuned attributes that make Cheetos such a consistently tasty snack. Rather than stopping the machines to check a batch that you may have to throw out, the machines adjust themselves and save significant amounts of both time and material in the process. Another machine learning-driven technology referred to as digital twins, allows companies to create virtual copies of entire factories to simulate production runs to make adjustments in advance or in real time. While these technologies still augment and don’t entirely replace human work and oversight, they certainly expand on the level of harnessable agency that was typically available to industrial companies.

Human Resources

In human resources (because despite all this talk, we as humans don’t plan on going anywhere), machines can parse resume data and scan a variety of work products to infer employee skills and provide companies with deep insights about both internal and external talent pools. This type of skill sensing requires natural language processing to interpret work as it’s described in different contexts, and in both foreseen and unforeseen ways (see Supervised vs. Unsupervised Learning). A.I. can also be used to interpret more subjective measures like an employee’s soft skills and team dynamics (see Teaming). When you put the hard skills, soft skills, and team dynamics together, you have the makings of an efficient internal mobility platform that works as an intelligent talent marketplace that empowers employees to seek projects, job roles, mentorship, and learning opportunities tailored to their abilities and aspirations. Traditionally, this level of insight was nowhere near accessible to HR departments. However, now A.I.-based technology has shown promise to supercharge HR’s analytical and operational capacity, which has spurred a lot of investment from large tech companies and VC to build the next generation of intelligent HR platforms. 

A non-exhaustive list of companies using A.I. for next-generation HR systems like the ones described above: 

• ServiceNow
• Gloat
• Phenom
• Fuel50

Conclusion

The A.I. revolution marks a transformational shift, altering the fundamental forces of business in a more profound manner than any previous revolution. By harnessing the unprecedented capabilities of A.I., we venture into a realm where machines hold the power to make decisions and take actions at a scale that will soon move beyond our wildest imaginations. As we stand at the threshold of this new era of both boundless opportunities and formidable challenges, let’s not mourn the coming of our intellectual rivals, but instead celebrate the fact that their success comes from their ability to be more like us–or at least when we’re at our best–if for no other reason because it’s perhaps the best way to understand viable career paths still available to us as biological agents.