The AI Fleet: A New Way of Developing Teams
The AI Fleet: A New Way of Developing Teams
5 min read
If you could build or curate your own fleet of AI team members, where would you start?
Prelude
For the professionals reading this, ask yourself "Am I in a position where I just do the work, or am I continuously thinking about how to leverage AI to get the work done faster, more efficiently, and at a higher level of quality?" The answer will determine your career trajectory. Those who are seeking ways to optimize how work gets done will be the ones that are retained and rewarded. Those who continue doing things the way they have always been done will find themselves competing against colleagues and competitors who have already moved past them.
For the leaders and executives reading this, the question is equally direct. Are you measuring your team's performance by the tasks they complete, or by the systems and automations they are building to multiply their output? If AI expertise is not a competency you are evaluating across every department in your firm, that should concern you. The firms that embed AI capability into every function will outpace those that treat it as a single department's responsibility or an initiative that lives on a roadmap somewhere.
Prelude
For the professionals reading this, ask yourself "Am I in a position where I just do the work, or am I continuously thinking about how to leverage AI to get the work done faster, more efficiently, and at a higher level of quality?" The answer will determine your career trajectory. Those who are seeking ways to optimize how work gets done will be the ones that are retained and rewarded. Those who continue doing things the way they have always been done will find themselves competing against colleagues and competitors who have already moved past them.
For the leaders and executives reading this, the question is equally direct. Are you measuring your team's performance by the tasks they complete, or by the systems and automations they are building to multiply their output? If AI expertise is not a competency you are evaluating across every department in your firm, that should concern you. The firms that embed AI capability into every function will outpace those that treat it as a single department's responsibility or an initiative that lives on a roadmap somewhere.
Invoking Question
I asked my team a simple question this week: If you could build or curate your own fleet of AI team members, where would you start?
Not "what would you automate?" Not "what tasks could AI handle?" Those are fine questions, but they keep people thinking small. They keep people anchored to the backlog sitting in front of them. The fleet question does something different. It forces you to think like a leader, not just a task completer.
What job titles would your AI team members have? What instructions would you give them? How would you measure their performance?
What happened next is what made this exercise so valuable. Every single person immediately had not just one or two ideas, but dozens. They were not just thinking about the next item on their to-do list. They were thinking about things they were not even doing today. Things they knew should be happening but never had the bandwidth to prioritize. That is where business growth takes a new shape, when your team starts thinking bigger, becoming more significant contributors, and attacking the opportunities head on rather than fearing the surmounting list of things that could be done.
The Ideas Came Fast
Marketing needed content creators, design specialists, and editors. They needed the ability to generate professional headshots for new employees without scheduling a photographer. They needed a way to conduct structured interviews with project teams to document retrospectives. They needed a method to clean up and normalize a contact list before importing it into their CRM.
Sales needed a prospecting engine. They needed a way to take meeting recordings and requirements gathered during discovery and translate that into a polished statement of work. They needed visibility into which questions had not yet been answered so they could increase their probability of close. They needed to understand which team members had capacity that could be soft allocated to opportunities nearing signature.
Account Management needed the ability to send customer surveys for gathering satisfaction and loyalty metrics. They needed to identify which projects were nearing go-live so they could proactively generate opportunities for optimization and continuation conversations. They needed a way to send renewal notices for contracts approaching the end of their terms.
Project Management wanted to identify where risks existed, specifically with conflicting task deadlines. They needed to send proactive inquiries around upcoming PTO schedules, capture the responses, and surface any resource coverage gaps.
Professional Services wanted to reconcile meeting recordings, calendar invites, and supporting documentation to reduce the manual burden of entering time. Managers wanted to review those entries and auto-approve them when the necessary criteria were met, including the customer name, meeting attendees, conversation topics, and the value delivered within that duration.
Talent acquisition wanted a faster way to identify candidates, contact them, and progress them through an expedited resume review. The team even discussed how AI could conduct an initial screening to narrow the candidate pool and shorten the days-to-hire timeline without compromising on the total number of candidates evaluated.
The Shift That Matters
The list goes on, but the takeaway is consistent across every department. All of these functions can be optimized by leveraging AI technologies that are available today. The biggest question is not whether it can be done. The biggest question is who is actually going to get it started.
The old way of working was positioning yourself or your team to complete these tasks manually. The new way of working will be defined by how quickly and efficiently you can leverage AI capabilities to do them instead. Every department now requires AI experience and competency to be successful within their roles. It is no longer a differentiator. It is a necessity to optimize the tasks and complete the routines required within a given department.
The capacity constraint has fundamentally changed. It is no longer "How long does it take you to complete a task?" It is now "How long does it take you to curate the automation required to complete the tasks?" Every business in every industry is in a race to answer that question. The firms that answer it fastest will create distance between themselves and their competitors, and the gap becomes increasingly difficult to close.
The Practical Framework Reality
The fleet concept is not a theoretical exercise. It is a practical framework for getting your team to think beyond their current workload and into the operational leverage that AI provides. Start the conversation. Ask your team where they would build their fleet. You will be surprised at how quickly the ideas surface and how many of them are entirely within reach.
The race is on. The question is whether you are building or watching.
About the Author
Cassius Kellogg is a leader in the consulting and professional services industry, focused on helping organizations build the kind of clarity, discipline, and structure that produces lasting outcomes. He believes that relationships are at the center of every successful business, that the best leaders make everyone around them better, and that the most valuable work is the work that creates engines capable of running without their creator.
If this piece resonated with you, I would welcome a conversation. The ideas in this paper are the result of years of trial, error, and iteration — and they continue to evolve every time I work with a new client, a new team, or a new problem. I am always interested in hearing how others apply these principles in their own context, and I am always looking to learn from people who think carefully about how to make complex things simple.
Invoking Question
I asked my team a simple question this week: If you could build or curate your own fleet of AI team members, where would you start?
Not "what would you automate?" Not "what tasks could AI handle?" Those are fine questions, but they keep people thinking small. They keep people anchored to the backlog sitting in front of them. The fleet question does something different. It forces you to think like a leader, not just a task completer.
What job titles would your AI team members have? What instructions would you give them? How would you measure their performance?
What happened next is what made this exercise so valuable. Every single person immediately had not just one or two ideas, but dozens. They were not just thinking about the next item on their to-do list. They were thinking about things they were not even doing today. Things they knew should be happening but never had the bandwidth to prioritize. That is where business growth takes a new shape, when your team starts thinking bigger, becoming more significant contributors, and attacking the opportunities head on rather than fearing the surmounting list of things that could be done.
The Ideas Came Fast
Marketing needed content creators, design specialists, and editors. They needed the ability to generate professional headshots for new employees without scheduling a photographer. They needed a way to conduct structured interviews with project teams to document retrospectives. They needed a method to clean up and normalize a contact list before importing it into their CRM.
Sales needed a prospecting engine. They needed a way to take meeting recordings and requirements gathered during discovery and translate that into a polished statement of work. They needed visibility into which questions had not yet been answered so they could increase their probability of close. They needed to understand which team members had capacity that could be soft allocated to opportunities nearing signature.
Account Management needed the ability to send customer surveys for gathering satisfaction and loyalty metrics. They needed to identify which projects were nearing go-live so they could proactively generate opportunities for optimization and continuation conversations. They needed a way to send renewal notices for contracts approaching the end of their terms.
Project Management wanted to identify where risks existed, specifically with conflicting task deadlines. They needed to send proactive inquiries around upcoming PTO schedules, capture the responses, and surface any resource coverage gaps.
Professional Services wanted to reconcile meeting recordings, calendar invites, and supporting documentation to reduce the manual burden of entering time. Managers wanted to review those entries and auto-approve them when the necessary criteria were met, including the customer name, meeting attendees, conversation topics, and the value delivered within that duration.
Talent acquisition wanted a faster way to identify candidates, contact them, and progress them through an expedited resume review. The team even discussed how AI could conduct an initial screening to narrow the candidate pool and shorten the days-to-hire timeline without compromising on the total number of candidates evaluated.
The Shift That Matters
The list goes on, but the takeaway is consistent across every department. All of these functions can be optimized by leveraging AI technologies that are available today. The biggest question is not whether it can be done. The biggest question is who is actually going to get it started.
The old way of working was positioning yourself or your team to complete these tasks manually. The new way of working will be defined by how quickly and efficiently you can leverage AI capabilities to do them instead. Every department now requires AI experience and competency to be successful within their roles. It is no longer a differentiator. It is a necessity to optimize the tasks and complete the routines required within a given department.
The capacity constraint has fundamentally changed. It is no longer "How long does it take you to complete a task?" It is now "How long does it take you to curate the automation required to complete the tasks?" Every business in every industry is in a race to answer that question. The firms that answer it fastest will create distance between themselves and their competitors, and the gap becomes increasingly difficult to close.
The Practical Framework Reality
The fleet concept is not a theoretical exercise. It is a practical framework for getting your team to think beyond their current workload and into the operational leverage that AI provides. Start the conversation. Ask your team where they would build their fleet. You will be surprised at how quickly the ideas surface and how many of them are entirely within reach.
The race is on. The question is whether you are building or watching.
About the Author
Cassius Kellogg is a leader in the consulting and professional services industry, focused on helping organizations build the kind of clarity, discipline, and structure that produces lasting outcomes. He believes that relationships are at the center of every successful business, that the best leaders make everyone around them better, and that the most valuable work is the work that creates engines capable of running without their creator.
If this piece resonated with you, I would welcome a conversation. The ideas in this paper are the result of years of trial, error, and iteration — and they continue to evolve every time I work with a new client, a new team, or a new problem. I am always interested in hearing how others apply these principles in their own context, and I am always looking to learn from people who think carefully about how to make complex things simple.