Roland Berger IT Study 2024: AI Trends, Challenges and Business Implications

Strategic IT Trends Overview

Roland Berger’s comprehensive 2024 IT Study reveals six strategic trends that are fundamentally reshaping the information technology landscape. Based on front-line project experience and expert interviews, this annual analysis provides critical insights for IT professionals navigating an increasingly complex technological environment.

The study identifies a clear hierarchy of challenges and opportunities, with artificial intelligence emerging as the dominant disruptive force across all industries. However, the analysis reveals that IT leaders must simultaneously address multiple interconnected trends, from environmental sustainability to cybersecurity resilience, while managing cost pressures and skills gaps.

What distinguishes this year’s findings is the evolution of certain trends from optional considerations to business-critical imperatives. Enterprise digital transformation strategies can no longer treat sustainability, security, or AI readiness as separate initiatives—they must be integrated into comprehensive technological and business strategies.

AI Readiness and Generative AI Adoption

Artificial intelligence, particularly generative AI, represents the most significant technological disruption identified in Roland Berger’s 2024 study. The research reveals a sobering reality: while AI promises transformative business impact, most organizations are unprepared for successful implementation and integration.

Through in-depth interviews with top management and IT executives worldwide, the study found that more than two-thirds of respondents rated their companies as “moderately prepared” to adopt Generative AI at best, with some acknowledging complete unpreparedness. This readiness gap represents both a significant risk and an opportunity for competitive differentiation.

The AI readiness challenge extends beyond technical implementation to encompass organizational culture, skill development, and strategic alignment. Companies that simply allocate budget to AI initiatives without comprehensive preparation face significant risks of failed implementations, wasted investments, and missed opportunities for competitive advantage.

Roland Berger’s research emphasizes that AI readiness requires a nuanced understanding of what organizations want to achieve, assessment of technology maturity levels, and honest evaluation of existing capabilities. The most successful AI implementations result from strategic approaches that align technological capabilities with specific business objectives and organizational readiness.

Cybersecurity and Cyber-Resilience

The cybersecurity landscape in 2024 is characterized by an escalating arms race between increasingly sophisticated attack vectors and organizational defense capabilities. Roland Berger’s study identifies cyber-resilience as a fundamental business requirement, not merely a technical consideration, due to the alarming trail of financial and reputational damage left by rising cybercrime.

The evolution from cybersecurity to cyber-resilience reflects a strategic shift in how organizations approach digital risk management. Rather than focusing solely on prevention, cyber-resilience encompasses the ability to detect, respond to, recover from, and learn from security incidents while maintaining business continuity.

Modern cyber threats target not just technical infrastructure but business processes, supply chains, and stakeholder trust. The study reveals that organizations with robust cyber-resilience strategies demonstrate better business performance, stakeholder confidence, and competitive positioning compared to those treating security as a purely technical function.

Enterprise cybersecurity frameworks must now integrate with broader business risk management, regulatory compliance, and operational resilience strategies. The most effective approaches combine advanced technical defenses with organizational capabilities for rapid incident response and business continuity maintenance.

Green IT and Environmental Sustainability

Environmental sustainability has undergone a fundamental transformation from optional corporate responsibility initiative to essential business asset. Roland Berger’s 2024 study identifies green IT as a strategic imperative driven by both environmental impact concerns and the recognition that ESG criteria represent lucrative business opportunities.

The transition to green IT encompasses multiple dimensions including energy efficiency optimization, sustainable technology procurement, circular economy principles in IT asset management, and carbon footprint reduction across digital operations. Organizations are discovering that environmental responsibility often aligns with operational efficiency and cost optimization.

Companies are implementing comprehensive sustainability strategies that extend beyond regulatory compliance to competitive differentiation. Green IT initiatives are generating measurable business value through reduced operational costs, enhanced stakeholder relationships, improved regulatory positioning, and access to sustainability-focused investment and partnership opportunities.

The study reveals that organizations treating sustainability as a core business driver rather than a compliance burden achieve better outcomes across multiple performance dimensions. This includes improved operational efficiency, stronger stakeholder relationships, and enhanced long-term competitive positioning in increasingly environmentally conscious markets.

Cloud Services and Cost Management

The ubiquity of cloud services has created a new category of management challenges that extend beyond technical implementation to encompass cost transparency, skills development, and strategic optimization. Roland Berger’s study identifies cloud cost management as a critical capability that many organizations lack despite extensive cloud adoption.

The cloud cost transparency challenge stems from the complexity of modern cloud service models, where traditional IT budgeting and cost allocation methods prove inadequate for dynamic, usage-based pricing models. Organizations struggle to predict, monitor, and optimize cloud expenses across diverse service categories and usage patterns.

Skills gaps compound the cost management challenge, as cloud optimization requires specialized expertise that many organizations lack internally. The study reveals significant gaps between cloud adoption rates and the development of cloud management capabilities, creating ongoing operational and financial risks.

Successful cloud strategies integrate technical architecture decisions with financial management, skills development, and governance frameworks. Cloud cost optimization strategies that combine automated monitoring, usage governance, and capability development demonstrate superior business outcomes compared to reactive cost management approaches.

IT Governance and Budget Control

Rising IT costs and increasing regulatory complexity are driving organizations toward more sophisticated IT governance frameworks that balance compliance requirements with budget discipline. Roland Berger’s study identifies IT governance as a critical capability for managing the intersection of technological advancement and financial constraints.

Modern IT governance extends beyond traditional project management and compliance oversight to encompass strategic alignment, value optimization, and risk management. Organizations require governance frameworks that can adapt to rapid technological change while maintaining financial discipline and regulatory compliance.

The governance challenge is compounded by the need to balance innovation and agility with control and compliance. Companies must develop governance approaches that enable rapid technology adoption and deployment while ensuring appropriate oversight, risk management, and budget control.

Effective IT governance integrates strategic planning, financial management, risk assessment, and performance measurement into comprehensive frameworks that support both operational efficiency and strategic innovation. The most successful organizations treat governance as an enabler of technological capabilities rather than a constraint on innovation.

Technology Standardization for Agility

The tension between technological standardization and organizational agility represents one of the most complex challenges identified in Roland Berger’s study. Large organizations must balance the efficiency and integration benefits of standardized technology platforms with the flexibility required for rapid adaptation to changing business requirements.

Traditional standardization approaches often created rigidity that hindered organizational responsiveness and innovation. Modern standardization strategies focus on platform standardization that enables agility rather than constraining it, creating consistent foundations for diverse application and service development.

The standardization imperative is driven by the need to integrate rapidly advancing technologies while maintaining operational consistency and efficiency. Organizations require standardized approaches that can accommodate diverse technological requirements while ensuring interoperability, security, and maintainability.

Successful standardization strategies emphasize modular architectures, API-driven integration, and platform-based development approaches that combine consistency with flexibility. These approaches enable organizations to maintain technological coherence while supporting diverse business requirements and rapid adaptation to changing market conditions.

The rAIse Framework for AI Implementation

Roland Berger’s rAIse framework provides a structured approach to AI readiness assessment and implementation planning, addressing the significant preparation gaps identified in the study’s survey findings. The framework emphasizes strategic clarity, capability assessment, and systematic implementation rather than technology-first approaches.

The framework guides organizations through critical assessment questions: What exactly does your company want to achieve with AI? This question ensures that AI initiatives align with specific business objectives rather than pursuing technology for its own sake. Clear objective definition prevents the common mistake of implementing AI solutions in search of problems to solve.

How mature is the technology itself? The framework emphasizes realistic assessment of AI technology capabilities and limitations relative to specific use case requirements. This prevents organizations from attempting implementations that exceed current technological capabilities or choosing inappropriate AI approaches for their specific needs.

Do you have the right skills on board? The capability assessment component evaluates existing organizational capabilities and identifies specific skill development requirements. This includes technical skills, change management capabilities, and the organizational culture attributes necessary for successful AI integration.

Future Implications and Strategic Recommendations

Roland Berger’s 2024 IT Study reveals that successful organizations must develop integrated approaches to managing multiple simultaneous technological and business challenges. The convergence of AI disruption, sustainability imperatives, security requirements, and cost pressures creates a complex strategic environment that demands sophisticated management capabilities.

The study’s findings suggest that organizations should avoid treating the six identified trends as separate initiatives. Instead, successful strategies integrate AI readiness, sustainability goals, security requirements, cloud optimization, governance frameworks, and standardization approaches into comprehensive technological and business strategies.

Strategic recommendations emphasize the importance of capability-driven approaches rather than technology-first implementations. Organizations should begin with clear assessment of desired business outcomes, honest evaluation of current capabilities, and systematic development of the skills and processes required for successful technology integration.

The research indicates that competitive advantage will increasingly accrue to organizations that can successfully navigate the complexity of simultaneous technological trends while maintaining operational efficiency and strategic focus. This requires sophisticated management capabilities, integrated strategic planning, and continuous adaptation to rapidly changing technological and business environments.

Future success will depend on developing organizational capabilities for continuous learning, adaptation, and innovation rather than mastering specific technologies or solutions. Digital transformation roadmaps must emphasize capability development, cultural change, and strategic alignment alongside technological implementation to achieve sustainable competitive advantages in the AI-driven economy.