Impact of AI on organizations

Will everyone become a manager?

I’ve long believed that people, process, and technology are all intricately linked. Usually the technology is referring to what the teams are building but in fact it can also refer to the technology that the people are using. Assembly lines and the machines that people used on them is an example of a technology that impacted organizational structures. Henry Ford's assembly lines which borrowed inspiration from meatpacking facilities, led to new organizational innovations in three ways. First, tasks were meticulously broken down and allocated to unskilled or semiskilled laborers, with the majority of the required skill being integrated into the machinery. Next, the expansion of manufacturing enterprises led to the establishment of a layered structure of supervisors and managers. Lastly, the escalating intricacy of business processes prompted the recruitment of managerial personnel with expertise in specific domains such as accounting, engineering, research and development, etc. 

The reason we have organization charts today can be traced back to the New York and Erie Railroad of 1855. The challenges faced in organizing work across vast distances, led to the creation of the first organizational chart by telegraph executive Daniel McCallum. The first organizational chart was lost and rediscovered by Caitlin Rosenthal. It was designed to resemble a tree with its branches and leaves, illustrating both the geography and the organizational hierarchy, with each position detailed, all the way to individual engine operators. This historical perspective shows how technological advancements can influence organizational structures​​.

The same is true of process improvements. In tech companies we now have cross-functional product engineering squads because of agile development processes. Before the agile revolution, engineers were organized and worked solely in engineering organizations. Product managers worked alongside other PMs writing product requirements documents that were passed along to engineers to work on as a separate and distinct phase. The agile process fundamentally changed the software development organization.

We are rapidly approaching a world in which every job a human performs will be aided by artificial intelligence. Most people can see this path clearly for knowledge workers like accountants, software developers, and lawyers but it might be a stretch to see this happening in the trades e.g. plumbing, electricians, and carpenters. However, it’s absolutely happening. AI is helping optimize job scheduling, recruiting, and even training/supervision. AI software like Fracta is helping predict which water mains need to be replaced before they break. In software engineering, we’re using AI in almost every phase from creating user personas to generating hypotheses to coding. One small example of this comes from a company like SparkBeyond that has developed a Hypothesis Engine that can generate millions of ideas and hypotheses autonomously and test and rank them based on the data. How is all of this AI on our teams going to impact the organization?

In order to answer that we need to take a quick detour to differentiate between leadership and management. Leadership and management are intricately linked but also distinct and different. There are many great ways of identifying the differences including:

Management is doing things right; leadership is doing the right things. – Peter Drucker

Managers light a fire under people; leaders light a fire in people. – Kathy Austin

Management is efficiency in operations, but leadership is efficiency in people. – Tim Cook

One of my personal favorites is from John Kotter, a Harvard Business School professor: 

Management is about coping with complexity while leadership is about coping with change. 

However, for this discussion another way to view this distinction between management and leadership is from Grace Hopper, a computer scientist and U.S. Navy rear admiral:

You Manage Things; You Lead People.

Another way that I think about this is that you manage tasks and you lead people. 

In today’s typical product development teams the managers manage the tasks. They are the ones who divide tasks into smaller sub-tasks and assign people to accomplish them. Not surprising, management is typically left to be handled by the managers. But they aren’t the only ones who lead. Senior engineers, designers, analysts, everyone on the team can and should display leadership. How might this change with the introduction of more AI into teams?

One possible scenario is that individual engineers will have a group of AI-bots working for them on small tasks. The engineer will design the feature, while bots develop small parts of it. If this becomes reality, the work of management (managing tasks) will become the work of individual engineers. Individual engineers will need to divide tasks and manage the work of their team of bots. Today the individual engineers are expected to lead but not manage. In the future it’s possible that everyone on the team is expected to not only lead but to also manage. 

It's evident that the incorporation of AI in team dynamics is poised to revolutionize traditional roles and responsibilities. With engineers potentially overseeing groups of AI-bots, the distinction between management and leadership becomes more nuanced. In this future landscape, engineers won't just be tasked with leading; they'll also assume managerial responsibilities, dividing tasks and overseeing the execution by their AI counterparts. This shift suggests a fundamental redefinition of job roles where individual contributors are not only expected to exhibit leadership qualities but also to manage complex tasks effectively.

The implications of this shift are profound. It could democratize management functions, traditionally reserved for specific roles, by embedding these skills into every team member's role. Such a change would necessitate a reevaluation of skill sets required for all roles, with an increased emphasis on management capabilities alongside technical proficiency and leadership. Moreover, this decentralization of management tasks could enhance agility and responsiveness within teams, as decision-making becomes more distributed and less hierarchical.

Furthermore, the offloading of routine tasks to AI can significantly amplify the creative and strategic capacity of team members. Freed from mundane responsibilities, individuals can focus more on innovation and problem-solving, driving forward the core objectives of their projects with greater efficiency and effectiveness. This change can foster a more dynamic and innovative work environment, where the focus shifts from simply executing tasks to pioneering new solutions and approaches.

Reflecting on the historical impact of technological advancements on organizational structures, such as the transformative effect of railroads, it's clear that we are on the cusp of another significant shift with the integration of AI into product teams. This change heralds a redefinition of roles, particularly in management. In a future where AI handles routine tasks, team members, especially in technical roles like engineering, might find themselves not only leading but also managing—tasks that involve oversight of AI systems and bots. This shift signifies a move towards a more integrated role, where management is democratized and distributed among various team members, not just confined to designated managers.