At AWS re:Invent, I sat down with Ben Schreiner, Head of AI and Modern Data Strategy at AWS, for a wide-ranging conversation about what it really takes for enterprises to succeed with AI.
While new tools and platforms continue to dominate headlines, Schreiner emphasized that the hardest part of AI transformation is not technology, but people: culture, change management, and trust. The discussion explored how empathy-driven leadership, strong data foundations, and thoughtful governance are becoming essential as companies move toward a future defined by agentic AI—where humans and autonomous agents work side by side.
Looking ahead, Schreiner painted a picture of a workplace where AI amplifies human creativity, elevates uniquely human skills, and fundamentally reshapes how work gets done.
Core Takeaways
Empathy Is Central to AI Change Management
Schreiner stressed that AI adoption is a leadership moment, requiring empathy for employees who may feel uncertainty or fear. Successful change management means acknowledging those concerns, investing in training, and clearly explaining why AI transformation matters and how it benefits individuals as well as the organization.
Trust Is the Critical Barrier for Agentic AI
As autonomous agents begin taking actions inside enterprises, trust becomes essential. Schreiner highlighted AWS’s focus on guardrails, agent policies, evaluations, and monitoring to ensure humans define what agents can and cannot do—and can intervene when behavior drifts from intent.
Data Strategy and AI Strategy Are Inseparable
AI success depends entirely on data quality and architecture. Schreiner argued that organizations must treat data as a product, work backward from business problems, and ensure the right data is accessible before expecting AI initiatives to scale beyond proof-of-concept.
The Future of Work Elevates Human Skills
Looking ahead two to three years, Schreiner predicted that managers will oversee both humans and AI agents, while uniquely human skills—critical thinking, creativity, communication, and curiosity—become more valuable as automation handles repetitive tasks.
Key Quotes
AI Transformation Is a Leadership Moment
“For the leaders out there, I think having a lot of empathy is required. This is a leadership moment and we need to bring our people along this journey. We need to set a course, have a north star, but the empathy for people who are afraid is critical. We need to acknowledge that and put things in place like training and exposure, so people understand why this transformation is happening and what’s in it for them.”
Humans Must Define the Boundaries for AI Agents
“I believe that the human beings need to define what AI can and can’t do on their behalf. That is our responsibility as the humans deploying these agents. Guardrails, agent policies, and evaluations are all about governance and control—putting boundaries around what is possible so organizations can trust these systems.”
AI Strategy and Data Strategy are Intertwined
“I think they’re one and the same. If you have an AI strategy without a data strategy, you’re going to have bumps in the road. We see companies succeed in proofs of concept with clean, finite data, and then struggle when they try to scale because the enterprise data isn’t in the same state. That realization often comes too late.”
AI Liberates Humans to Do More Meaningful Work
“These bots and agents working on our behalf free us up to do things we enjoy and that pique our intellect. On my own team, we built an agent to handle time-consuming data entry, saving about a day a month per person. Now they spend that time talking to customers. The quality of life improved—and that’s the kind of impact this technology can have.”
