A new study from IBM reveals that enterprises across Europe, the Middle East and Africa (EMEA) are already reporting significant productivity gains from using AI, with many expecting returns on their investments (ROI) within the next year.
However, the findings suggest small to medium sized enterprises (SME) and public sector organisations are falling behind larger, private sector firms in boosting productivity with AI.
“The Race for ROI”, a new IBM report produced in partnership with Censuswide, surveyed 3 500 senior executives across ten countries, and reveals 66% of respondents said their organizations have achieved significant operational productivity improvements using AI.
In addition, approximately one in five respondents said their organisation has already realised ROI goals from AI-driven productivity initiatives, with a further 42% on average expecting to achieve ROI within 12 months across cost reduction (41%); time savings (45%); increased revenue (37%); employee satisfaction (42%) and increased Net Promoter Score (43%).
Further productivity benefits are expected from the introduction of AI Agents, with 92% of leaders expecting that agentic AI will deliver measurable ROI within two years.
According to the study, business areas achieving the biggest AI-driven productivity gains are software development and IT (32%), customer service (32%), and procurement (27%). At the same time, executives reported the top three benefits of enhanced productivity as greater operational efficiency (55%), enhanced decision-making (50%), and augmented workforce capabilities such as automating repetitive tasks (48%).
However, the gains are not evenly distributed across all types of organizations. While 72% of large enterprises surveyed reported productivity gains from AI, only 55% of SMEs say the same. The research also indicates that public sector organisations are in the earlier stages of realizing AI’s full potential, with only 55% reporting significant productivity improvements to date.
AI transforming business models
Across EMEA, the data shows that leaders are increasingly using AI to enable strategic business transformation. Of the 66% of respondents who reported significant productivity gains, nearly a quarter (24%) credit AI with fundamentally changing their business models.
Strikingly, around a third of respondents are already using AI to change their operations in ways such as accelerating innovation timelines (36%); shifting to continuous AI-driven decision-making instead of periodic planning cycles (32%); and redesigning value streams around AI rather than automating existing steps (32%, and around 2 in 5 intend to do so across all these areas.
Nearly half of all senior leaders surveyed (48%) said that AI is augmenting workforce capabilities. For example, with the time saved from greater productivity, executives said employees are spending more time on tasks such as developing new ideas (38%), strategic decision-making and planning (36%), and engaging in creative work (33%), the report finds.
Ana Paula Assis, senior vice-president and chair of IBM EMEA and growth markets, says: “The true value of AI for business goes far beyond individual productivity – it’s about strategic transformation. Our research suggests that, while we are still in the foothills of AI adoption, enterprises in EMEA are seeing meaningful productivity gains from infusing AI into their operations, with many redesigning their business models.
“On the question of technology autonomy, the response was emphatic: enterprises want to use technology on their terms, with transparency, choice and flexibility baked in.”
Prioritising open systems, interoperability and choice
The study found that openness, interoperability, and choice are critical priorities for all types of organisations adopting AI. 85% of respondents emphasised the importance of transparency in AI systems and models, ensuring that the technology operates ethically and responsibly.
Similarly, 84% stressed the need for interoperability, enabling seamless integration of AI tools into IT systems to maximise efficiency and adaptability.
A further 85% said they valued having the flexibility to choose and adapt AI solutions or providers as needs evolve, underscoring strong demand for autonomy.
Overcoming risk and complexity
While the findings suggest companies are progressing towards greater ROI on AI, it also identified concerns about security, privacy and ethics – including the risk of data breaches and the trustworthiness of AI – as the top barrier to scaling successful AI pilots, cited by 68% of respondents.
Similarly, IT complexity challenges, such as integrating AI with legacy systems, was cited by 68% of senior leaders surveyed.
To accelerate ROI from AI, the report outlines five priorities for enterprise leaders:
- Establish an effective operating model for AI: Establishing a common and universally understood approach for AI transformation across the organization, such as a federated or hub-and-spoke model, along with clear ownership, is crucial for delivering return on investment.
- Cultivate AI literacy and a culture of innovation, from the board to entry-level: In the coming years, AI tools will become increasingly embedded in every interaction. Knowledge of how and why to use these tools across teams and functions will help the organisation to adapt and thrive as AI capabilities and the opportunities they create continue to evolve.
- Get comfortable with uncertainty and rapid change: The world is moving into an era of AI everywhere. AI tools will be embedded and procured into every interaction layer we have – whether it is search engines, the device people interact with or the companies they engage with. Success in this era means developing a culture that embraces change and uncertainty, and enables rapid, purposeful innovation.
- Understand the risks around AI deployment: As with any technology, AI must be applied with caution and a detailed understanding of regulatory, reputational and operational risks. Enterprises should apply AI governance tooling to monitor and mitigate potential risks, such as unauthorised data sharing and unwanted bias.
- Establish a cross company “AI board” to mitigate risk: The AI board’s role is to define ethical principles and risk appetite and review higher risk AI use cases before they are implemented. This, combined with increased AI literacy, will give business units a high level of autonomy to implement AI use cases with confidence.