Enterprise automation platform Make used its recent Waves 2026 conference in Prague to outline a comprehensive vision for shifting artificial intelligence operations out of opaque environments and into a transparent framework. During the opening keynote, Chief Executive Officer Fabian Veit addressed the persistent gap between widespread individual AI adoption and deep organizational transformation, arguing that while personal productivity tools have achieved mass acceptance, core business processes remain largely unchanged due to a fundamental lack of operational trust.
Overcoming the Black Box Dilemma
According to executive leadership, organizations have successfully deployed conversational tools and basic assistants for day-to-day tasks, but wider transformation continues to stall. The core hurdle is not fear of rogue technology, but rather the operational uncertainty of probabilistic systems operating at scale. Without visibility into how autonomous agents interact with critical business systems, leaders remain hesitant to delegate high-stakes workflows.
To counter this opacity, Make is championing a glass-box approach designed to make agentic operations transparent, governable, and understandable at every level. Rather than overwhelming users with raw, unmanaged data streams, the strategy relies on refraction—using meaningful visual abstractions to help human operators maintain leverage and oversight as autonomous activity accelerates across the enterprise.
Evolving Development and Governance Models
The company also detailed how its platform will support the entire lifecycle of AI integration, spanning creation, runtime management, and discovery:
- Natural language is expected to increasingly drive system creation, with AI assistants translating human intent directly into functional workflows.
- Visual models will remain critical for reviewing and approving proposed changes, ensuring human oversight keeps pace with automated development.
- Integrated governance tools will restrict agent permissions, utilizing private workspaces and scoped toolboxes to enforce strict operational boundaries.
Executives emphasized that thousands of individually legible automation assets do not automatically equate to a coherent enterprise operating model. Moving forward, the focus must shift toward understanding the complex relationships and workflows connecting these components across the broader technological landscape to ensure reliable execution.