A significant maturity gap in large organizations is that internal platform PMs don't treat their users (e.g., developers, finance) as customers. Applying customer-centric practices like problem framing and journey mapping to these stakeholders can dramatically improve outcomes.

Personio created 'Go-to-Market Engineer' roles within their Revenue Operations team. These individuals have a business background but are also data-driven and tech-focused. This hybrid role is crucial for successfully implementing AI solutions because they understand both business context and technical requirements.

When employees are 'too busy' to learn AI, don't just schedule more training. Instead, identify their most time-consuming task and build a specific AI tool (like a custom GPT) to solve it. This proves AI's value by giving them back time, creating the bandwidth and motivation needed for deeper learning.

Vercel's CTO Malte Ubl suggests a simple method for finding valuable internal automation tasks: ask people, "What do you hate most about your job?" This uncovers tedious work that requires some human judgment, making it a perfect sweet spot for the capabilities of current-generation AI agents.

By building a custom AI assistant integrated into Salesforce, Personio dramatically increased its expansion SDRs' productivity. The tool consolidates customer information from over 10 systems, reducing daily research time from two hours to just 15 minutes and doubling the pipeline generated per employee.

To find valuable AI use cases, start with projects that save time (efficiency gains). Next, focus on improving the quality of existing outputs. Finally, pursue entirely new capabilities that were previously impossible, creating a roadmap from immediate to transformative value.

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.

Instead of asking employees what they do, map your core business processes (e.g., customer acquisition). Then, assign each step to a person. This bottom-up approach reveals who is truly driving value and who is overburdened, leading to more accurate role definitions based on business impact.

In the AI era, shift from silos like 'Demand Gen' to cross-functional pods focused on outcomes like 'Brand Relationship' or 'Product Delight.' This model, inspired by product development, aligns teams to solve specific customer problems and better integrates AI agents directly into core workflows.