The availability of real-time data in ad tech allows for a "daily rigor" management style. Instead of long feedback loops, leaders can steer the business daily in "war room" meetings, tracking deals and numbers to maintain intensity and react quickly to performance.

As AI takes over campaign execution, the marketer's job shifts from micro-management to macro-strategy. They define the business rules—such as discount ranges, offer types, and creative assets—and the AI then makes millions of optimized micro-decisions for individual customers within those human-set boundaries.

Effective enterprise AI deployment involves running human and AI workflows in parallel. When the AI fails, it generates a data point for fine-tuning. When the human fails, it becomes a training moment for the employee. This "tandem system" creates a continuous feedback loop for both the model and the workforce.

Instead of fully automating conversations and risking sounding robotic, use AI to provide real-time suggestions and prompts to a human sales rep. This scales expertise and consistency without sacrificing the human touch needed to close deals.

Implement AI effectively by allocating 10% of your time to human-led strategy (ideation), delegating 80% to AI for repetitive execution (research, list building), and reserving the final 10% for human review and integration. This framework ensures human taste and vision remain central to the process.

The next frontier in e-commerce is inter-company AI collaboration. A brand's AI will detect an opportunity, like a needed digital shelf update, and generate a recommendation. After human approval, the request is sent directly to the retailer's AI agent for automatic execution.

Rather than fully replacing humans, the optimal AI model acts as a teammate. It handles data crunching and generates recommendations, freeing teams from analysis to focus on strategic decision-making and approving AI's proposed actions, like halting ad spend on out-of-stock items.

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.

Sales leaders are growing skeptical of 'black box' AI that gives directives without context. The most effective AI serves as a coach, augmenting human skills by handling informational tasks. It cannot, however, replace the emotional intelligence and human judgment required for true sales transformation.