Brands will struggle to capitalize on agentic AI if they treat it as a side project for existing teams. Mastering complex AI systems is a full-time job, necessitating the creation of specialized roles like "AI e-commerce manager" to focus exclusively on optimizing these new technologies.
As AI evolves from single-task tools to autonomous agents, the human role transforms. Instead of simply using AI, professionals will need to manage and oversee multiple AI agents, ensuring their actions are safe, ethical, and aligned with business goals, acting as a critical control layer.
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.
Shifting the mindset from viewing AI as a simple tool to a 'digital worker' allows businesses to extract significantly more value. This involves onboarding, training, and managing the AI like a new hire, leading to deeper integration, better performance, and higher ROI.
As AI agents automate day-to-day e-commerce optimization, the primary role for humans evolves. Core competencies will shift from data analysis and execution to high-level decision-making and managing the complex, collaborative joint business planning process with retail partners.
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.
The next frontier of leadership involves managing an organizational structure composed of both humans and AI agents. This requires a completely new skill set focused on orchestration, risk management, and envisioning new workflows, for which no traditional business school training exists.
Companies mistakenly try to hire one person for both applying AI in products and building the underlying AI infrastructure. These are two distinct roles requiring different skill sets. A VP of Engineering leverages existing AI for efficiency, while a Head of AI builds the core platforms for the company.
You can't delegate AI tool implementation to your sales team or a generalist RevOps person. Success requires a dedicated, technical owner in-house—a 'GTM engineer' or 'AI nerd.' This person must be capable of building complex campaigns and working closely with the vendor's team to train and deploy the agent effectively.
Instead of traditional IT roles focused on software, an AI Ops person focuses on identifying and automating workflows. They work with teams to eliminate busy work and return hundreds of hours, shifting employees from performing tasks to directing AI.
Rather than simply eliminating jobs, the rise of AI agents is creating a need for new, specialized roles. Positions like "Go-to-Market Engineer" and "AI Marketing Ops Specialist" are emerging to oversee, coach, and orchestrate these agents, signaling a transformation—not a reduction—of the GTM workforce.