AI's rise in business: opportunities and challenges

As AI adoption grows in importance, businesses face challenges but aim for balanced, trustworthy integration.

AI adoption is continuing to advance, with many business leaders recognising its growing importance. Cisco’s latest study indicates that 65% of CEOs are now concerned about underinvesting in this transformative technology, up from 53% last year. Today, 69% of respondents view AI adoption as important for achieving contemporary business success.

Despite this confidence, businesses face challenges in developing the required infrastructure, data frameworks, and security measures to support safe, consistent, and scalable AI implementations. Now in its second year, Cisco’s survey captures insights from 2,500 CEOs across 23 countries, exploring their views on AI, expectations for its future, and the barriers affecting wider adoption.

European CEOs place particular emphasis on trust and ethical alignment when approaching AI adoption. They highlight the importance of careful implementation while maintaining transparency, accountability, and responsible practices.

Looking ahead, CEOs generally expect AI to become increasingly integrated into the workplace by 2030, while continuing to operate under human oversight. This perspective, shared by 72% of CEOs, reflects a focus on maintaining security, productivity, and ethical decision-making as AI capabilities expand.

Although CEOs’ understanding of AI has improved significantly—with the proportion reporting limited understanding decreasing from 74% to 47%—achieving comprehensive AI integration remains challenging. Key barriers include infrastructure limitations, security considerations, and fragmented data environments.

Infrastructure readiness remains a priority, with 53% of CEOs identifying limitations in current systems. Addressing these gaps through upgrades to support AI workloads is among the key areas of focus for 2026, alongside developing team capabilities to support AI-ready processes.

Data fragmentation is another significant challenge. CEOs identify data quality and accessibility as major barriers to AI adoption, more frequently than any other issue. Fragmented data environments continue to affect AI progress, creating a need for organisations to improve data consolidation and accessibility to support effective AI use.

These concerns align with findings from Cisco’s 2026 AI Readiness Index, which highlights global trends identified among more than 8,000 IT leaders. The report indicates that only a minority of organisations believe their networks are fully prepared for AI workloads or that their data ecosystems are sufficiently aligned for large-scale AI deployment.

Ultimately, organisations that address these challenges and establish the necessary foundations for AI adoption will be better positioned to develop and scale AI-enabled capabilities, while those that delay preparation may face increasing difficulty keeping pace with evolving business requirements.

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