Global Data and AI strategy: building a unified approach for an international IT Services company
Advisory
IT services
Europe
Wiktor Zdzienicki
Co-Founder at Innsyte
Author’s historical experience before founding Innsyte
This case study explores the creation of a comprehensive data and AI strategy for a major international IT services company. The initiative aimed to build a cohesive global framework for developing, delivering, and selling data and AI solutions. Despite existing regional capabilities, the lack of a unified approach hindered the company from maximising its potential in data and AI. The project, driven by the Innsyte co-founders, focused on establishing global standards and practices to enhance both internal efficiency and customer service quality.
Consultants: 300+
GTM continents: 3
CSPs covered: 3
Job profiles: 9
Problem: lack of unified AI strategy hindered global efficiency
The company, a global leader in IT services, faced a complex challenge: how to consolidate its data and AI capabilities spread across various regions into a cohesive global strategy. Although there were robust local and regional operations, each unit operated somewhat independently. This resulted in inconsistent approaches to data and AI project delivery and sales. As the world increasingly embraced data-driven decision-making and AI solutions, it became crucial for the company to standardize its operations.
The need was twofold. Internally, the company needed to ensure that its data assets were being leveraged effectively across all its entities. Externally, it needed to provide consistent, high-quality services to its international clients, who expected uniformity in service delivery regardless of their location. The company had begun to build its data and AI capabilities at the regional level, but there was no overarching framework to guide these efforts. Without a global strategy, there was a risk of duplicated efforts, missed opportunities, and a lack of coherence in customer engagements.
Before engaging with the team, the company had already developed regional data and AI capabilities but lacked global alignment. They had recognized the potential for scaling their efforts but needed a structured, centralised approach that would enable them to leverage their capabilities more effectively. This included the development of global structures, standardized project delivery models, and a unified approach to building and selling data and AI solutions.
Solution: building a comprehensive AI operating model for global alignment
To address these challenges, a specialised team was assembled to create a comprehensive global data and AI strategy. The process began with a thorough analysis of the current state of affairs, including an assessment of existing capabilities, customer needs, project types, and technology stacks. This phase involved extensive research and stakeholder engagement through workshops, interviews, and surveys. Key participants included regional leaders, technical experts, business stakeholders, and sales teams. The team’s approach focused on several core areas:
- Capability assessment – evaluating existing regional strengths and identifying gaps in skills, tools, and processes. This involved cataloging the current technology stacks used, the types of projects being delivered, and the specific competencies of regional teams.
- Stakeholder engagement – conducting interactive workshops and interviews to gather insights from various levels of the organization. This included understanding the unique needs and challenges of each region, as well as aligning these with the company’s broader strategic goals.
- Strategy development – creating a detailed strategy that encompassed all aspects of data and AI operations. This included defining a global operating model, standardizing tools and technologies, developing a global delivery framework, and establishing clear guidelines for sales and project execution. The strategy also addressed key questions such as whether to prioritize AI or data solutions, the balance between advisory and implementation services, and the degree of autonomy to be given to regional teams.
- Implementation roadmap – developing a phased plan for rolling out the new strategy across all regions. This included the establishment of regional champions to drive local adoption of global standards, the creation of training programs to up-skill teams, and the development of a centralised knowledge-sharing platform to facilitate collaboration and information exchange.
The strategy was designed to be flexible, allowing for regional customisation while ensuring overall alignment with global objectives. It also included a robust framework for ongoing evaluation and refinement, enabling the company to adapt its approach as needed based on evolving market conditions and technological advancements.
Impact: improved efficiency and project delivery through a standardized AI strategy
The implementation of the global data and AI strategy had a significant impact on both internal operations and customer engagements. Key outcomes included:
- Enhanced global coordination – the establishment of a global framework for data and AI enabled better coordination and information sharing across regions. This led to more cohesive project delivery and a consistent customer experience, regardless of the client’s location.
- Increased project volume and quality – the standardized approach resulted in a notable increase in the number of data and AI projects delivered, particularly in Europe. This was driven by improved sales materials, clearer service offerings, and enhanced internal capabilities.
- Improved customer satisfaction – clients benefited from a more predictable and uniform service delivery model. The company’s ability to provide consistent quality and meet diverse client needs more effectively boosted overall customer satisfaction.
- Stronger cooperation with external partners – the strategy facilitated better alignment between the company and its multinational partners, enabling the delivery of integrated solutions that leveraged the company’s global expertise and resources.
The shift from a regional to a global approach was not without its challenges, including the need to balance regional autonomy with global consistency, the complexities of knowledge transfer, and managing technological debt. However, the assignment of regional champions and the establishment of clear communication channels helped address these issues, enabling the company to make steady progress toward its strategic goals.
Designing a global data and AI strategy is a challenging endeavor that involves navigating numerous daily obstacles. However, it is the only sensible approach for a global IT services company to ensure consistent, high-quality service and customer care across all regions.
Wiktor Zdzienicki, Co-Founder at Innsyte
Lessons learnt: balancing global AI strategy with regional flexibility
The implementation of a global AI strategy and unified AI operating model transformed the company’s ability to deliver consistent, high-quality data and AI solutions across regions. By standardising processes and enhancing cross-regional collaboration, the company not only improved operational efficiency but also elevated customer satisfaction and strengthened its global partnerships. This strategic shift has positioned the company as a leading provider of scalable AI solutions, ready to meet the evolving demands of its international clientele.
Balance global and regional needs
it’s crucial to maintain a balance between global alignment and regional creativity. Localisation and regional autonomy are key to fostering innovation and responsiveness
Empower regional champions
Assigning regional champions is essential for effective implementation. They act as a bridge between global strategy and local execution, ensuring that initiatives are adopted and adapted as needed.
Understand customer needs in context
Global strategies must be informed by an in-depth understanding of regional customer needs. Top-down approaches should be balanced with insights from the ground to remain relevant and effective
Align internal and external stakeholders
Success in global initiatives requires the alignment of interests among all stakeholders, including internal teams and external partners. Clear communication and shared objectives are critical to managing these complex relationships.
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