AI transforms the Executive Assistant role from tactical execution to strategic system design. By automating repetitive tasks, EAs can focus on higher-leverage activities like building AI agents, culture-reinforcement tools, and scalable feedback systems for the entire organization.

As AI agents take over task execution, the primary role of human knowledge workers evolves. Instead of being the "doers," humans become the "architects" who design, model, and orchestrate the workflows that both human and AI teammates follow. This places a premium on systems thinking and process design skills.

According to Sierra AI CEO Brett Taylor, companies are seeing a new role emerge from AI implementation. Traditional contact center managers are evolving into "AI Architects," responsible for designing, managing, and optimizing the entire system of human and AI agents, marking a shift from operational to strategic work.

As AI agents proliferate across departments, a new role is emerging to manage them holistically. This person must understand the entire organization to ensure agents communicate effectively and workflows are cohesive, preventing the creation of new digital silos.

Top-performing engineering teams are evolving from hands-on coding to a managerial role. Their primary job is to define tasks, kick off multiple AI agents in parallel, review plans, and approve the final output, rather than implementing the details themselves.

Companies aren't using AI to cut staff but to handle routine tasks, allowing agents to manage complex, emotional issues. This transforms the agent's role from transactional support to high-value relationship management, requiring more empathy and problem-solving skills, not less.

The adoption of powerful AI agents will fundamentally shift knowledge work. Instead of executing tasks, humans will be responsible for directing agents, providing crucial context, managing escalations, and coordinating between different AI systems. The primary job will evolve from 'doing' to 'managing and guiding'.

Instead of focusing on foundational models, software engineers should target the creation of AI "agents." These are automated workflows designed to handle specific, repetitive business chores within departments like customer support, sales, or HR. This is where companies see immediate value and are willing to invest.

As businesses deploy multiple AI agents across various platforms, a new operations role will become necessary. This "Agent Manager" will be responsible for ensuring the AI workforce functions correctly—preventing hallucinations, validating data sources, and maintaining agent performance and integration.