How Do You Invest in AI If You Cannot Initially Quantify AI Outcomes?

Enterprise technology executives face a dilemma when deploying generative artificial intelligence: unless there is measurable return on investment (either predicted or realized), the investment will not be made, or continue. 

But Gen AI is quite new, so few entities will have at least a year’s worth of experience to make such outcome assessments. 

So many projects essentially require some leap of faith or willingness to experiment. 

source: Deloitte

And while it might be easy to argue that desirable outcomes include improving existing products and services fostering innovation gaining efficiencies and reducing costs, metrics must be devised and time has to elapse before measurement is possible.

Use Case	Metrics	Tracking Method
Content Creation (e.g., marketing copy, product descriptions)	Content creation speed  Content quality  Customer engagement with content	Track time spent creating content  Compare human-generated vs. AI-generated content quality through A/B testing  Monitor website traffic, conversion rates, and customer feedback
Product Design and Development	Number of design iterations required  Time to market for new products  Customer satisfaction with product design	Track design cycle times  Monitor time spent on prototyping and development  Conduct customer surveys to gauge satisfaction with product design and functionality
Data Augmentation (e.g., training machine learning models)	Accuracy of machine learning models  Training time for machine learning models  Cost of data acquisition	Track model performance metrics (e.g., precision, recall)  Compare training times with and without AI-generated data  Monitor costs associated with data collection and labeling
Personalized User Experiences (e.g., product recommendations, chatbots)	Customer satisfaction with personalization  Conversion rates on recommended products  Number of customer interactions handled by chatbots	Conduct customer satisfaction surveys  Track website click-through rates and conversion rates for recommendations  Monitor chatbot performance metrics (e.g., resolution rates, customer satisfaction scores)