The Race for AI ROI: How Enterprise Productivity is Being Transformed
IBM's groundbreaking "The Race for AI" report surveyed over 3,500 senior business leaders across 10 EMEA countries, revealing unprecedented insights into how Artificial Intelligence is transforming enterprise productivity. The findings paint a picture of rapid adoption, measurable returns, and sector-specific disparities that are reshaping the competitive landscape.
AI: The Greatest Productivity Force Multiplier in History
Artificial Intelligence is being hailed as the greatest force multiplier for productivity the world has ever witnessed. This designation isn't hyperbole—governments and businesses are backing this assessment with billions in investment, recognizing AI's potential to fundamentally alter the trajectory of economic growth.
The timing couldn't be more critical. Europe's productivity growth has remained stagnant, hovering below 1% throughout 2024. AI represents not just an incremental improvement, but a transformative opportunity to reverse this troubling trend. The numbers are staggering:
- 3% annual boost in global productivity growth projected by 2030
- $4 trillion in potential value addition to the global economy
- $3.5 billion in measurable productivity gains achieved by IBM itself in just two years
🎯 Key Insight
IBM's own transformation story demonstrates that AI-driven productivity gains aren't theoretical—they're measurable, financially reportable, and achievable within a 2-year timeframe.
The Data: 66% Already Seeing Significant Impact
The research, conducted in partnership with Censuswide in September 2025, delivers compelling evidence of AI's current impact:
- 66% of EMEA senior business leaders report AI has already delivered significant productivity improvements
- Only 2% of respondents indicated they have yet to see or expect any meaningful impact within the next two years
- 60% of organizations anticipate tangible returns on their AI investments in under 12 months
- 92% of EMEA senior leaders are confident that AI agents and tools will deliver measurable ROI within two years
Where ROI Goals Have Already Been Met
Organizations are seeing concrete results across multiple dimensions:
| Metric | Achievement Rate |
|---|---|
| Employee Time Savings | 25% |
| Financial Cost Savings | 20% |
| Increased Revenue | 22% |
| Enhanced Employee Satisfaction | 23% |
| Improved Customer Satisfaction | 21% |
Strategic Priorities: Efficiency First, Then Innovation
When prioritizing AI investments, EMEA senior leaders focus on three key areas:
- Increasing Efficiency (51%) - The primary driver for half of all organizations
- Enhancing Decision-Making Capabilities (42%) - Leveraging AI for strategic insights
- IT Modernization (40%) - Building the foundation for AI-first operations
💡 Beyond Efficiency
For forward-thinking organizations, AI benefits extend far beyond simple efficiency gains. They're enabling businesses to augment human potential and accelerate innovation in ways previously impossible.
AI as a Strategic Enabler of Business Transformation
Operational Benefits
Organizations report tangible improvements across multiple operational dimensions:
- 55% - Increased operational efficiency
- 50% - Improved decision-making and knowledge-sharing
- 48% - Augmented workforce capabilities
Business Model Transformation
The most progressive organizations are moving beyond incremental improvements:
- 24% of leaders who reported significant productivity gains felt AI had fundamentally altered their business models
- 78% of senior leaders are using or planning to use AI to speed up innovation cycles
- 25% of EMEA business leaders seeing improvements identified "developing company strategy" as an area of greatest productivity gains
Strategic AI Applications
Organizations are deploying AI in transformative ways:
- 76% are transitioning from linear value chains to AI-enabled platforms connecting multiple stakeholders
- 79% are evolving from periodic risk assessments to continuous AI-powered monitoring
Sectoral Disparities: Winners and Laggards
While the overall outlook is positive, progress varies dramatically across sectors, revealing a concerning digital divide:
| Sector | Significant Gains | Financial ROI | 2-Year ROI Confidence |
|---|---|---|---|
| Banking & Financial Services | 72% | 26% | 94% |
| Energy & Utilities | 70% | 26% | 94% |
| EMEA Average | 66% | 20% | 92% |
| Public Sector | 55% | 13% | 86% |
Banking & Financial Services: Leading the Charge
The financial sector is setting the pace with clear strategic priorities:
- 52% prioritize increasing operational efficiency
- 41% focus on enhancing risk mitigation and compliance
- 72% already seeing significant productivity gains (vs. 66% EMEA average)
- 26% achieving financial ROI (vs. 20% EMEA average)
Energy & Utilities: Matching Financial Services
Energy companies are keeping pace with strategic AI deployment:
- 55% prioritize operational efficiency
- 51% focus on enhancing decision-making
- 70% reporting significant productivity gains
- 26% achieving financial ROI
🏆 Real-World Success: Nedgia
A generative-AI contact center deployed by Nedgia in the Energy & Utilities sector cut waiting times dramatically by instantly resolving queries, freeing human agents for higher-value support tasks.
Public Sector: Struggling to Keep Pace
The public sector faces significant headwinds, with only 55% reporting productivity gains compared to 66% EMEA average. Key barriers include:
- 70% - Inadequate data infrastructure or data fragmentation
- 68% - Budget limitations
- 66% - Talent or expertise shortage
Top Priority Areas for Public Sector:
- Increasing operational efficiency (55%)
- Enhancing risk mitigation and compliance (42%)
- Enhancing decision-making (41%)
⚠️ Growing Digital Divide
The 17-percentage-point gap between Banking/Energy (70-72%) and Public Sector (55%) in productivity gains represents a concerning disparity that could widen without targeted intervention.
Transforming the Workplace: Employee and Customer Impact
Augmenting the Workforce
AI and automation are fundamentally reshaping how employees spend their time, freeing them from routine tasks to focus on higher-value activities:
- 39% - Driving innovation and new ideas
- 36% - Strategic planning
- 33% - Creative work
Importantly, over one in four (28%) respondents reported that AI is driving job creation, contradicting fears of widespread job displacement.
Enhancing Customer Experience
AI is transforming how organizations engage with customers:
- 39% - Using virtual assistants
- 38% - Fraud detection and prevention
- 38% - Behavior prediction and analysis
Requirements for Scaling AI Successfully
Scaling AI across the enterprise demands more than great technology—it requires a comprehensive approach to governance, ethics, and operational flexibility.
Critical Success Factors
Enterprise leaders emphasize five key requirements:
- 87% - Maintaining control over AI systems and data
- 86% - Ability to govern AI systems for regulatory compliance
- 85% - Flexibility to choose and adapt AI solutions as needs evolve
- 85% - Ensuring technology operates ethically and responsibly
🔑 The Right-Sized AI Approach
Enterprises need efficient, cost-effective AI tailored for specific use cases, rather than generic, trillion-parameter models. Choice and interoperability matter more than raw model size.
Five Key Priorities to Accelerate AI ROI
1. Establish an Effective Operating Model for AI
Create a common, universally understood approach for AI transformation across the organization. This includes:
- Clear roles and responsibilities
- Standardized processes for AI development and deployment
- Integration with existing business operations
2. Cultivate AI Literacy and a Culture of Innovation
Remove fear and build understanding of what AI is and is not. This ensures:
- Tools add value when applied to the right areas
- Employees can identify productive AI use cases
- Innovation becomes embedded in organizational culture
3. Get Comfortable with Uncertainty and Rapid Change
Develop a culture that embraces constant change as AI becomes embedded in every interaction layer:
- Iterative development approaches
- Continuous learning and adaptation
- Flexibility in strategic planning
4. Understand and Mitigate AI Deployment Risks
Apply AI governance tooling to monitor and mitigate risks such as:
- Unwanted bias in decision-making
- Data privacy violations
- Regulatory non-compliance
- Security vulnerabilities
5. Establish a Cross-Company "AI Board"
Create oversight mechanisms to ensure responsible AI deployment:
- Define ethical principles
- Review higher-risk AI use cases before implementation
- Ensure alignment with organizational values
- Monitor ongoing AI performance and impact
Key Takeaways for Business Leaders
📊 The Bottom Line
- AI ROI is Real and Rapid: 60% of organizations expect tangible returns within 12 months
- Sectoral Disparities Matter: Banking and Energy are outpacing other sectors by 15+ percentage points
- Beyond Efficiency: 24% of high-performers report AI fundamentally altering business models
- Choice Matters: 85-87% of leaders prioritize control, flexibility, and ethical governance
- Job Creation, Not Destruction: 28% report AI is driving job creation
The Path Forward
The IBM EMEA Report makes clear that AI isn't a future possibility—it's a present reality delivering measurable value today. Organizations that establish the right governance frameworks, cultivate AI literacy, and maintain flexibility in their approach are positioning themselves to capture the full potential of this transformative technology.
The race for AI ROI is on, and the early leaders are already seeing returns. The question for every organization isn't whether to adopt AI, but how quickly and strategically they can scale it across their operations.
📚 Learn More
This article is based on IBM's "The Race for AI" EMEA Report, surveying over 3,500 senior business leaders across 10 countries in September 2025. For organizations looking to accelerate their AI journey, the report provides a roadmap grounded in real-world success stories and data-driven insights.