Unlocking continuous growth "Data & AI-native" business process transformation
Article | 2026-06-26
8 minute read
Reimagining how work gets done has always been at the heart of business innovation. For decades, companies turned to Business Process Re-engineering (BPR) to sharpen their competitive edge and ensure long-term growth in the face of constant change. Each wave of BPR has been shaped by the technologies of its time. From the widespread implementation of ERP (Enterprise Resource Planning) systems in the 2000s to the rapid adoption of digital technologies in the 2010s.
Now, with the rise of data-driven thinking and rapid advancements in Artificial Intelligence (AI), businesses are entering a new phase of transformation. Traditional processes, built on the assumption that humans handle every task, are giving way to models where humans and AI work together, each contributing their unique strengths. In this new era, where AI, including generative AI, is delivering unprecedented capabilities, the objective is clear: to achieve a truly "Data & AI-native" business process transformation.
Turning this vision into reality requires three foundational transformations to happen.
First, Data. Data is typically siloed optimized for individual business applications across the entire enterprise. It is essential to reintegrate data across the entire enterprise. Thereby creating an environment where AI can access the full breadth of information it needs across business applications to make comprehensive, cross-functional decisions.
Second, IT Architecture: To fully unlock the potential of data and AI, requires that IT infrastructure is restructured. Shifting from systems designed primarily for human operation to architectures that enable and optimize AI-driven processes.
Third, Security: As AI agents increasingly operate autonomously on behalf of humans and exchange data with one another, building a robust, granular security framework across business processes and IT systems becomes critical. This security foundation not only protects the enterprise but also serves as a key driver of trust and long-term growth.
Business process transformation is essential for successful AI implementation. To support these new processes, IT architecture must also evolve. In turn, security transformation underpins both business process and IT architecture changes, ensuring a secure foundation for this new environment. By transforming data, IT architecture, and security in a unified, integrated way, businesses can build truly Data & AI-native processes. Strengthening their competitive edge and driving sustained growth.
Uvance Wayfinders see technology as the core enabler of business transformation, providing the foundation that supports change across all aspects of the enterprise. Today, data and AI are fundamentally reshaping how businesses operate and create value. We hope this article offers helpful insights to support your organization’s ongoing growth.
1. What is a Data & AI-native Business Process?
With the rapid advance and adoption of data and AI technologies, many companies are beginning to incorporate them into their operations. However, AI-driven BPR does not mean automating or streamlining existing processes. Introducing AI into current processes without rethinking and fundamentally redesigning them will not unlock AI’s full potential to enhance business performance and corporate value.
To fully realize the value of data and AI, we must reimagine business processes that were originally designed around human execution and transform them into “Data & AI-native” processes where humans and AI work together. This requires capturing data across all business activities and gradually expanding the scope of AI use. The ultimate goal is to achieve digital twin transformation, enabling comprehensive, real-time optimization of the entire organization.
For example, think about the time spent searching for emails or files needed for daily work. While each search may only take a few minutes, the cumulative time spent on these routine tasks, before any real thinking or decision-making begins, can be significant. By creating an environment where AI has access to all relevant data and can instantly retrieve the necessary information upon request, productivity can be greatly improved.
In customer service, it's not just about automating interactions with chatbots. AI can help deliver personalized experiences that truly meet customer needs. In finance operations, rather than manually consolidating information in spreadsheets, AI can analyze real-time data, predict future outcomes, and proactively recommend actions based on those predictions.
Ultimately, business processes need to be redesigned from a new perspective: How can AI complement human capabilities, and what should humans focus on that only they can do?
However, simply forcing AI onto existing operations is misguided. While AI has advanced significantly and can handle a wide variety of tasks, it is not a magic solution. Like any tool, AI has distinct strengths and weaknesses relative to human capabilities. To unlock its true potential, organizations must redesign processes to allow AI to do what it does best, while preserving and strengthening the human elements that drive competitive advantage. Not every task should be handed over to AI. Thoughtful integration is key.
As AI continues to evolve at an extraordinary pace, clinging to established norms and legacy processes will leave organizations unable to adapt to emerging technologies and business models, potentially even risking a “Kodak moment”. Past successes can easily become future liabilities. Misapplication or underutilization of data and AI will ultimately undermine business performance. Building truly Data & AI-native business processes is essential to embed the agility, adaptability, and resilience required to compete and grow in a rapidly changing world.
2. How AI drives business process improvement and contributes to business
What is the relationship between AI adoption and business process transformation? According to the 2025 Process Optimization Report published by Celonis in February 2025 (*1), 58% of the 1,620 business leaders surveyed across the US, Japan, Europe, and other regions indicated that inefficiencies in their internal processes are limiting the effectiveness of AI.
Also, 79% of respondents agreed that “a deeper understanding of process mechanisms is urgently needed to identify improvement opportunities and unlock greater value” through AI. These findings underscore the critical role that business processes play in enabling AI to generate actionable insights and drive productivity gains.
In addition, 64% of business leaders believe that "AI will deliver significant improvements to ROI." Transitioning to Data & AI-native business processes creates a virtuous cycle in which AI continuously generates value, driving stronger business contributions and reinforcing growth. Many global business leaders are already witnessing these benefits firsthand.
As Alex Rinke, Co-founder and Co-CEO of Celonis, explains in the report: “AI agents need to recognize processes, just as GPS needs a map.” By positioning Data & AI-native business processes as strategic assets, organizations can lay the foundation for continuous value creation and innovation through AI. Ultimately enabling long-term, sustainable growth.
3. Three transformations supporting Data & AI-native
Realizing Data & AI-native business processes requires three fundamental transformations: Data, IT Architecture, and Security must all be adapted for the AI era. Addressing any one of these areas in isolation will limit impact. The true value emerges when all three are transformed in a unified, integrated, and consistent manner, to create a foundation where AI can operate effectively and drive meaningful business outcomes.
Data
To fully leverage AI’s capabilities, organizations must establish an environment where data is seamlessly aggregated and accessible across all business functions. With business processes based on the premise that humans do everything, the data for operating the business is not digitized. In many cases, critical data gaps are bridged through human experience, intuition, and judgment. While strategic decision-making should remain a human prerogative, numerous operational tasks within end-to-end processes are prime candidates for AI augmentation.
For example, take KPI management. It is neither efficient nor strategic for leaders to manually define KPIs and monitor dashboards and passively report “the numbers are as expected.” Instead, humans should focus on interpreting insights and determining strategic actions to drive performance improvements. KPIs offer only a snapshot, but AI can go beyond these limitations. Analyzing data in depth, providing richer evaluations, and delivering recommendations that help optimize future outcomes.
Achieving this requires breaking down data silos across functions, organizations, and regions to build a connected data foundation. Visualizing integrated data enables AI to more easily identify issues, generate insights, and perform sophisticated analyses. At the same time, implementing strong data governance improves data quality and collection, while change management supports continuous business transformation. Transformation driven by these integrated efforts is key to unlocking the full potential of AI.
IT Architecture
To fully leverage AI across business functions, organizations must rethink their IT architecture. Not only making data more accessible to AI, but also enabling AI to orchestrate and optimize business processes. Traditionally, IT architecture has been structured around two distinct axes: core systems and information systems. Core systems manage essential business operations such as sales, production, and inventory, often requiring human input for data entry, verification, and approvals. Information systems, in turn, have typically extracted data from core systems for analysis and reporting, with people interpreting the data and taking action accordingly.
As we move into an era where agent-based AI takes on a more active operational role, this dynamic shifts fundamentally. AI will not only analyze data but also initiate and execute actions based on human-defined policies and objectives. This evolution demands a new kind of IT architecture, one where core and information systems are seamlessly integrated through a unified data and AI infrastructure.
Without such an integrated foundation, the adoption of advanced technologies like AI will face a high hurdle. A Data & AI-native IT architecture dramatically increases the agility and flexibility of the enterprise. Rather than being constrained by static cloud or on-premise deployments, AI can dynamically orchestrate workloads and resources based on real-time business needs, continuously optimizing the execution environment. Furthermore, AI-driven development can shorten system development lifecycles, enhance quality, and accelerate time to value.
What’s required is more than simply modernizing legacy systems. It is about redefining the IT architecture to align with the realities of AI-enabled business. Carefully evaluating emerging technologies, assessing their true business impact, and balancing immediate wins with long-term transformation goals. This dual-track approach requires discipline: avoiding hype-driven decisions, staying laser-focused on solving the organization’s most pressing challenges, and designing for both agility and resilience as the business evolves.
Security
In the AI agent era, security must be embedded across all business processes and the IT architecture that supports them. Cyber threats are growing in both scale and sophistication. Organizations not only need to defend against increasingly complex external attacks, but also prepare for potential unintended actions triggered by their own AI systems.
Security can no longer be relegated to the IT department. It must be elevated to a core management priority, a foundational pillar that enables organizations to confidently build and scale Data & AI-native business models. Addressing only the attack surface is no longer enough; true resilience requires a far more holistic approach.
This means embedding security at multiple levels. At the IT architecture level, where every component includes built-in security controls. Across business processes, where security is integrated into every operational step. And through ongoing oversight, with continuous monitoring, objective measurement, and systematic improvement of the organization's overall security posture.
Investments in security do not produce immediately visible results. However, once damage is incurred, it can be fatal. Resting on existing security will quickly reveal vulnerabilities. Fundamental transformation that leverages a sense of crisis is now required.
4. Conclusion
Transformation only demonstrates its true value when addressed continuously. The most important thing for continuous transformation is not just "doing it and ending it," but a mindset of "constantly capturing changes and responding immediately." The era in which transformation becomes a normal part of daily operations is just around the corner. At such times, AI and cutting-edge technologies will support daily transformation. In other words, companies that neglect to prepare will not be able to make the necessary transformations and will continue to lose their competitive advantage in the market. Now is the time to implement Data & AI-native business processes and begin transformations to overcome uncertainty.
Responding to complex issues, uncertainty in the business environment, and quick decision-making are required in real management. Ultimately, what is needed is "judgment based on facts, while making use of tradition and intuition." This can be said to be an important perspective that leads to transformation for establishing Data & AI-native business processes that fully utilize data and AI and lead companies to growth.
Uvance Wayfinders exists to guide organizations on this journey. Our global team of cross-disciplinary experts partner closely with clients to embed AI deeply into their operations. Not simply as a tool, but as a foundational capability that drives continuous transformation. We offer a new consulting model: one that begins with technology, progresses step-by-step through the necessary business transformations, and stays committed as a long-term partner in our clients' success.
We hope this report provides valuable perspectives to help you navigate the challenges and opportunities ahead.
Satoshi Mihara
Head of Global Technology Practice, Managing Partner, Uvance Wayfinders
Satoshi Mihara has a wealth of experience in the financial and distribution sectors, specializing in data strategy development, architectural design for data environments, and post-implementation organizational transformation and improvement. After positions at domestic system integrators and other firms, he joined Accenture in 2007, where he spearheaded data-driven consulting initiatives. In June 2024, he joined Fujitsu to drive the global expansion and transformation of technology consulting under Uvance Wayfinders.
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