For decades, return on investment (ROI) has been a clear-cut, metric-driven framework for evaluating business success. Whether optimizing supply chains, expanding market share, or improving customer satisfaction, the pursuit of ROI has shaped how enterprises invest, operate, and scale. But in today’s data-saturated, speed-driven world, traditional ROI models are increasingly inadequate.
In a whitepaper titled “The Future of Enterprise Intelligence: Integrating GenAI for Competitive Advantage” by Practus and Pathsetter AI, the narrative is clear: Gen AI is no longer just a futuristic tool. It’s a strategic enabler that reshapes how ROI is conceived, measured, and realized.
The ROI Paradox in Traditional Enterprises
Despite increasing investments in Business Intelligence (BI), over 97% of data leaders admit their organizations still struggle to maximize data-driven decision-making. Traditional BI frameworks often fail to provide real-time, actionable intelligence. Reports and dashboards may arrive too late; decision-making lags behind dynamic market conditions. In effect, the value generated is often retrospective and insufficient.
Take, for instance, a retail chain using BI dashboards to analyze Q2 sales. By the time underperformance is flagged, the opportunity for in-quarter course correction is lost. In ROI terms, delayed insights translate to lost revenue, missed promotions, and increased operational inefficiency.
Gen AI: Moving From Hindsight to Foresight
Unlike BI, Gen AI empowers enterprises with predictive, real-time intelligence. It doesn’t just highlight what happened but simulates what could happen next. Whether through automated forecasts, intelligent simulations, or context-aware recommendations, Gen AI transitions the enterprise from hindsight to foresight.
| ROI Dimension | Traditional BI | Gen AI-Enabled EI |
|---|---|---|
| Insight Timing | Retrospective | Real-time & Predictive |
| Decision Speed | Manual, delayed | Automated, accelerated |
| Operational Efficiency | Dashboard-driven | Outcome-driven automation |
| Customer Experience | Segment-level personalization | Hyper-personalization at scale |
| Innovation | Limited to trends analysis | AI-driven ideation & product development |
Case in Point: Klarna & Coca-Cola
The whitepaper details how Klarna used Gen AI to reinvent customer support. Facing an 85% surge in inquiries across 45 markets, Klarna implemented a Gen AI-powered support system. The results?
- 67% of customer queries resolved without human intervention
- 78% reduction in response times
- 54% cost reduction per interaction
- 22% increase in customer satisfaction
Klarna’s ROI was not just operational but cultural with lower agent turnover and the emergence of new roles like AI trainers. Here, Gen AI redefined ROI by improving both tangible metrics and intangible workforce value.
Similarly, Coca-Cola cut content production time by 30% and improved campaign A/B testing capacity by 40%, thanks to a Gen AI platform integrated with brand assets and creative workflows. ROI wasn’t limited to speed and savings; it included scalability, brand coherence, and employee satisfaction.
Introducing Outcomes as a Service (OaaS)
Perhaps the most radical shift outlined is the move from platform implementation to Outcomes as a Service (OaaS). Here, vendors are evaluated not by technical delivery, but by impact on KPIs—from revenue uplift to cost savings.
Example Transformations Under OaaS Model:
- Supply Chain Optimization: From installing automation tools to targeting “15% reduction in inventory carrying cost.”
- Financial Forecasting: From delivering an AI model to ensuring “10% improvement in forecast accuracy.”
- Customer Experience: From deploying a chatbot to achieving “20% reduction in wait times.”
This redefinition requires not only technology but cultural alignment: continuous feedback loops, human-AI collaboration, and clear ownership of outcomes.
Strategic KPIs: A New ROI Lexicon
Traditional ROI focuses on cost reduction and revenue gains. Gen AI demands a broader KPI framework:
| Metric | Target Range | Strategic Value |
|---|---|---|
| Innovation Rate | 25-40% | Accelerated product development |
| Time-to-Decision | 40-60% reduction | Agile strategic execution |
| Forecast Accuracy | 85-95% | Precision in operations and finance |
| Process Automation Rate | 25-40% | Cost and error reduction |
| AI Adoption Rate | 30-70% (yearly) | Workforce transformation |
These metrics move ROI from output measurement to outcome orchestration.
Critique: Challenges in Reframing ROI
While the whitepaper provides a comprehensive roadmap, it assumes enterprises can seamlessly shift from experimentation to execution. The reality is messier.
- Legacy Systems: Integration with outdated IT ecosystems remains a huge hurdle.
- Cultural Resistance: Employees often mistrust AI, seeing it as a replacement, not a tool.
- Data Governance: Privacy and bias remain persistent threats to reliable outcomes.
Moreover, tracking ROI in Gen AI isn’t always immediate. Benefits such as employee satisfaction or brand perception are harder to quantify and need long-term tracking mechanisms.
The ROI of What Matters
In the Gen AI era, ROI is no longer just about efficiency or cost savings. It’s about unlocking human potential, driving sustainable value, and enabling organizations to operate at the speed of thought.
C-suite leaders must recognize that the competitive advantage lies not in adopting Gen AI tools, but in engineering business outcomes with them. That means building internal capability, aligning strategy with execution, and redefining ROI to include what truly matters: adaptability, creativity, and customer-centricity.
The future is not dashboards. It’s direction. Not pilots. But Performance. And the time to act is now.