The adoption of AI tools, infrastructure, co-pilots and agents across the workforce is transforming how we work as individuals and teams at an extraordinary rate. Many employees want to embrace AI to do their jobs more effectively, and they want their workplaces to have the same mindset. This shift requires companies to take a strategic approach to workforce management, whereby understanding and integrating AI capabilities becomes just as important as traditional business functions.
Tech startups will lead the transformational shift
Tech startups are nimble, agile and generally early adopters, and as such, will likely be the first to adopt agentic solutions into their tech stacks and workflows. With limited cash flow, they want tools that can delay hiring, reserve cash and help make current roles more scalable. In this article, we’re going to focus on the tech startup and what the future of its workforce could look like as this internal adoption of AI takes place.
Today, startups are composed of two primary categories of people: the hyper-specialists — those with niche roles in engineering, product, finance, marketing, sales and other specific fields and the ultra-generalists — the early operators that connect the dots, build cohesive strategies, learn and adapt, hire as needed and ensure smooth operations across the company. Currently, hyper-specialists are in the most demand, especially in engineering and product roles, and as such, have the highest compensation.
The ultra-generalist role is crucial for startups. With limited employees and budgets, the first hires need to be professionals who are versatile and can effectively handle a wide range of challenges and decisions. Today, generalists are already using AI tools like ChatGPT and Gemini to help them perform some of the tasks traditionally reserved for specialists, such as writing content and generating code.
Generalists are also more recently incorporating AI copilots into their workflows for specific functions to enhance productivity. For example, an HR AI copilot could analyze data from employee surveys, feedback forms and communication channels to identify trends in employee sentiment and engagement levels and then provide actionable insights, such as identifying departments where morale might be low.
With the rise of AI agents, the hierarchy of roles is set to change drastically
As AI Agents come on the scene, they will go a step further than copilots providing insights and recommendations, and will actually take action. This could be a recruitment AI agent that not only scans resumes and matches candidates with job descriptions but also schedules the interviews, for example (with human oversight, for now).
Consequently, ultra-generalists will need to manage teams composed of both AI agents and human workers. The “jack of all trades” ultra-generalists will be uniquely capable of running these hybrid teams and will thus become increasingly valuable to organizations. Research from the World Economic Forum forecasts that 23% of all jobs will change in the next five years due to technological advancements like AI, elevating the importance of roles that require managing both human and AI resources in the near future.
Salaries will be based on the breadth of the generalist’s skill set — communication, problem-solving, adaptability and ability to build and manage inter-intelligent teams of humans and AIs. The market will undergo a paradigm shift, with generalists starting to earn as much or more than specialists at the same level.
As AI Agents work together, the model of specialized expertise evolves
Let’s explore the following significant and imminent shift, where AI agents operate within a larger multi-agent framework. In this model, multiple agents work together to address challenges too intricate for one agent to solve independently. Each agent brings specialized expertise to the table, works with various digital tools as needed and collaborates with both agents and humans.
AI systems will consist of specialized agents working together with limited human oversight. Just as different parts of the human brain handle various tasks, including processing, analyzing and understanding information and then responding to it, AI systems are being developed to replicate that model. Over time, these AI systems will learn and improve, becoming more self-sufficient.
Consider a basic example in accounts receivable:
One agent could look through accounting data and identify who owes money, another could determine the best collection method, a third could make the call(s) and another could process the payment and close the loop back to the human. These AI agents will continuously learn from their combined experiences and optimize their processes. For example, they could learn that by sending a reminder text a week before they call, they are 5% more likely to collect and continuously find the best method for achieving their goal.
Throughout this process, the ultra-generalist will set goals, provide inputs and monitor the system for errors, safety and privacy. Their role will not be replaced, but instead, they will be able to manage multiple systems at once with even less time and effort, making this role the highest in demand and, therefore, the highest paid.
The future of the unicorn in this new paradigm
In the next 5 to 8 years, we will witness the emergence of unicorn companies with fewer than 50 employees run by small groups of ultra-generalists, quickly generating over $20 million in revenue per employee. With small teams managing such large corporations, the generalist’s ability to align, communicate, retain talent and adapt will be their differentiating factor.
To prepare for this near-term future, companies must:
- Identify potential ultra-generalists within their teams.
- Ensure these individuals are comfortable working with AI today.
- Involve them in business strategy and give them a meaningful seat at the table.
And current generalists must:
- Become familiar with AI, especially agentic AI.
- Expand their knowledge base across various functions within the organization.
- Cultivate adaptability as their most crucial skill.
- Continuously monitor changes in AI and spend time learning to work with the newest AI tools.
By taking these steps, startups and ultra-generalists can position themselves for success in a rapidly changing market driven by the synergy of human and AI collaboration.
Opinions expressed by SmartBrief contributors are their own.
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