Focusing exclusively on GenAI is a guarantee to fail. To unlock the full potential of AI, adopt a holistic approach that integrates GenAI with alternative AI techniques, ensuring that investments are aligned with real business needs and not limited by the hype cycle of any single technology.

In particular, avoid using GenAI for:

• Prediction and forecasting: GenAI models are not well-suited for tasks that require numerical predictive modeling. They lack the explicit optimization and planning capabilities necessary for valuable forecasting tasks. Alternative AI techniques, such as traditional machine learning models, are more reliable for these use cases.

• Critical decision intelligence: The models may produce inaccurate or misleading outputs that inform poor decisions. Use alternative AI techniques that provide more robust and interpretable results for decision-making processes. 

• Handling sensitive data: When dealing with proprietary, sensitive or confidential information, using GenAI — especially public instances — can introduce risks related to data privacy and security. 

• Complex problem domains: GenAI may struggle where there is limited training data or where the relationships between data points are not well understood. In such cases, simpler AI techniques or rule-based systems may yield better results.

GenAI technologies hold the potential for substantial ROI, but to get the full benefits, organizations must adopt a comprehensive approach to measurement that includes both traditional and alternative metrics, invest in change management, and carefully track total costs fully.

The total cost of ownership (TCO) for GenAI initiatives can often exceed initial expectations due to hidden costs such as compliance reviews, model retraining and internal overheads. Maintain a tracker to monitor these expenses and ensure that you are capturing the full financial picture of GenAI investments.

Traditional ROI metrics, such as productivity and cost savings, may not fully capture the value of GenAI implementations. Consider alternative metrics like Return on Employee (ROE) and Return on Future (ROF), which focus on employee experience and long-term strategic benefits, respectively. 

Effective change management is crucial for realizing the benefits of GenAI. Organizations that invest in training and upskilling employees to effectively use GenAI tools are more likely to see positive ROI. This includes creating tailored training programs that match employees' AI maturity levels and addressing the specific needs of different roles within the organization.

Finally, the ROI from GenAI can vary widely depending on the specific use cases. For example, in healthcare, GenAI can streamline administrative processes like prior authorization and claim adjudication, leading to significant efficiencies and cost savings. However, the success of these implementations often hinges on the quality of data and the effectiveness of governance frameworks in place.