Summary: As AI and automation reshape enterprise operations, organizations face a critical challenge: moving beyond siloed optimizations to see and steer the business as a whole. Digital Twins of the Organization (DTOs) meet this need by providing a dynamic, real-time model of enterprise operations — connecting data, processes, and strategy. Highlighted in Gartner’s Hype Cycle for Enterprise Process Automation, DTOs enable scenario simulation, predictive decision-making, and alignment of AI investments with true business value. This article explores why DTOs are becoming essential for digital transformation, operational excellence, and enterprise resilience in the age of AI.
In an era where AI and automation are reshaping enterprise operations, organizations need more than just data — they need a living, dynamic model of how their business truly runs. Enter the Digital Twin of the Organization (DTO): an emerging yet critical capability that creates a real-time, data-driven mirror of operations. As outlined in Gartner’s latest Hype Cycle for Enterprise Process Automation, DTOs are foundational for orchestrating complex decisions, aligning AI investments, and avoiding the costly trap of local optimization.
Why Now: The Strategic Importance of Digital Twins of the Organization
AI is transforming enterprise operations — from predictive analytics in supply chains to generative assistants in customer service. Yet most organizations apply these technologies in narrow, siloed use cases. The outcome? Local optimizations that overlook the bigger picture and sometimes create new inefficiencies.
Unlike traditional dashboards or static models, a DTO provides a dynamic, real-time model of how an enterprise functions across processes, systems, and business units. It doesn’t just report what is happening — it connects operational context to strategic intent.
According to Gartner’s 2025 Hype Cycle for Enterprise Process Automation, DTOs are not just another tool - they are a transformational capability. Organizations can use them to align operations with strategy, simulate scenarios before implementing changes, and anticipate downstream impacts of decisions — all essential in an environment defined by rising complexity and accelerating change.
Digital Twins of the Organization are not just another tool - they are a transformational capability.
This capability becomes particularly urgent in the age of AI. A recent MIT Sloan study (NANDA) found that only 5% of AI projects deliver sustained success. Why? Because most lack a broader operational and strategic context. DTOs fill this gap by showing where AI can generate systemic value - not just incremental automation.
For leaders navigating transformation, DTOs function as a strategic “navigation system” enabling smarter decisions, faster adaptation, and a clearer visibility into how digital investments drive business value.
The Power of Seeing the Whole: Avoiding the Local Optimization Trap
AI has become synonymous with automation, efficiency, and innovation — but its true power lies in orchestration. Many organizations chase quick AI wins in isolated processes. But without visibility into the broader system, these efforts rarely scale — and often create new bottlenecks and contradictions.
The DTO solves this. By offering a unified, real-time representation of how processes, people, data, and systems interact, leaders can step out of silos and ask bigger questions: Where are we creating value? Where are we losing it? What trade-offs are we making without realizing it?
This systems-level view is essential in AI-driven environments, where one change in a local workflow can cascade unpredictably through supply chains, customer experience, or compliance operations. DTOs make these ripple effects visible — and testable — before they occur.
With scenario analysis built in, executives can explore strategies, test alternatives, and predict outcomes before committing resources. This makes the DTO not just a diagnostic tool, but a strategic asset.
Most importantly, DTOs drive a shift from reactive decision-making to proactive orchestration — moving organizations from chasing efficiency in parts to designing effectiveness across the whole.
Beyond Visibility: Bridging the Past, Future, and Action
Observing how your business operates is only the start. Defining how it should operate — and mapping the path to reach it — is what truly drives transformation. This is where the synergy between Object-Centric Process Mining (OCPM), Digital Twins of the Organization (DTO), and Enterprise Architecture (EA) comes into play.
Each plays a distinct role:
Object-Centric Process Mining (OCPM) provides retrospective insight. It reveals how processes truly run across systems — not how they were designed — offering a necessary reality check. For organizations still relying on assumptions or outdated models, OCPM is often a necessary reality check.
Digital Twins of the Organization (DTO) shift the focus to the future. They offer simulation and scenario analysis capabilities, allowing leaders to explore the impact of proposed changes, forecast performance under different conditions, and align investments with strategic objectives.
Enterprise Architecture (EA) translates insights into execution. It ensures organizations can act on DTO insights with the right systems, governance, and capabilities.
Together, these three layers form a continuum: from how the business has worked, to how it could work, to how it will be built. This dynamic alignment is essential for any enterprise undergoing transformation, particularly those investing heavily in AI and automation.
The message is clear: visibility alone isn’t enough. Organizations need an integrated approach that connects insight, foresight, and execution into a single strategy.
The Path Forward: From Insight to Execution
While the value of DTOs is compelling, adoption requires more than technology. It demands a mindset shift in how organizations think about operations, architecture, and change.
Gartner’s advises a pragmatic approach: start small, scale deliberately, and align with business priorities. This means identifying high-impact use cases where DTOs can immediately support strategic decision-making — such as operational resilience, supply chain coordination, or customer experience improvement. These focused wins build momentum and surface organizational learning, paving the way for broader adoption.
While the value of DTOs is compelling, adoption requires more than technology. It demands a mindset shift in how organizations think about operations, architecture, and change.
But DTOs don’t operate in isolation. They are most effective when integrated with business orchestration platforms, automation capabilities, and enterprise architecture practices. Tools like BOAT (Business Orchestration and Automation Technologies) act as a connective tissue — orchestrating processes across systems, enabling low-code development, and coordinating AI agents.
Governance is critical. Without shared standards — for KPIs, modeling, data governance, and scenario protocols — DTO initiatives risk fragmentation and complexity.
Finally, culture matters as much as capability. DTOs thrive when organizations embrace cross-functional collaboration, data transparency, and continuous adaptation. Establishing a center of excellence or operations competency hub can accelerate maturity.
In short, DTOs are not a plug-and-play solution. They are a strategic discipline — enabling organizations to evolve from static planning to living, learning enterprises.
By Pavel Azaletskiy
Editor Viktoryia Karalionak