Generative AI Boosts Productivity, ROI and Engagement
With enterprises increasingly adopting AI, their metrics for measuring success for generative and predictive (non-generative) AI differ according to use cases tracked in Omdia’s latest AI Business Performance Metrics Database. Compared to traditional predictive AI adoption, enterprises deploying generative AI (GenAI) are more focused on enhancing productivity, ROI, and customer engagement, as revealed by the database of AI deployment case studies. Generative AI productivity ROI
Since late 2022, GenAI solutions have entered the market. As enough time has elapsed since their adoption, vendors are increasingly releasing GenAI “customer success” studies featuring measured results (metrics or KPIs) for market promotion. In the latest update of the AI Business Performance Metrics Database, Omdia focused on compiling GenAI case studies, constituting 9% of the 700 records. Of the 67 new case studies, 52 focus on GenAI. This offers an initial insight into how enterprises are evaluating the success of their generative and predictive (non-generative) AI deployments.
What Sets Generative AI Apart?
Generative AI is not just a buzzword; it’s a game-changer. By automating tasks like code development and offering virtual assistance, GenAI solutions are redefining productivity. Let’s dive deeper into how GenAI is revolutionizing enterprise metrics.
Comparing generative versus predictive AI within each metric, productivity stands out as the most relatively favored metric for generative deployments, accounting for 17%, nearly double the 9% share of predictive case studies. Top productivity applications include automated code development and virtual assistants. ROI is also more valued in GenAI studies (9% vs 6% of cases), particularly for writing assistants. Engagement is another relatively favored metric, cited in 22% of generative cases, compared to 17% of predictive cases, with key use cases including virtual assistants and digital experience marketing.
Productivity: The GenAI Advantage
Boosting Productivity with Automation
Generative AI excels at automating repetitive tasks, freeing up valuable time for employees to focus on more strategic initiatives. This is evident in:
- Automated Code Development: Speeds up the software development process.
- Virtual Assistants: Enhance efficiency in customer support and administrative tasks.
The Numbers Speak
According to Omdia, productivity is the most favored metric for GenAI, accounting for 17% of generative deployments compared to just 9% for predictive AI. This significant gap underscores the transformative potential of GenAI in boosting productivity.
ROI: Making Every Euro Count
Generative AI’s Impact on ROI
Enterprises are always on the lookout for technologies that deliver high ROI. GenAI has proven to be a worthy investment, especially in applications like writing assistants that streamline content creation and reduce costs.
Case Studies Highlight ROI Success
In the latest update, 9% of GenAI case studies focused on ROI, compared to 6% for predictive AI. This illustrates how GenAI not only enhances productivity but also ensures that every dollar spent yields tangible returns.
“Recent case studies confirm that enterprises are indeed adopting GenAI and keeping a sharp eye on measuring how the technology is affecting their business outcomes,” said Neil Dunay, Omdia Principal Forecaster. “With significant investments being made in the technology, vendors and enterprises are eager to prove to customers and investors that GenAI is delivering on promised results. That may mean cases studies of GenAI failures could go unreported.”
Customer Engagement: The New Frontier
Enhancing Customer Experience
Customer engagement is crucial in today’s competitive market. GenAI is helping enterprises connect with customers in more meaningful ways through:
- Virtual Assistants: Provide personalized customer interactions.
- Digital Experience Marketing: Tailor marketing efforts to individual preferences.
Engagement Metrics Tell the Story
Engagement is cited in 22% of generative AI case studies, compared to 17% for predictive AI. This indicates that enterprises deploying GenAI are seeing a more significant impact on customer engagement.
The Role of Predictive AI
Where Predictive AI Shines
While GenAI is taking the spotlight, predictive AI still plays a vital role in areas like revenue improvement, accuracy, and cost reduction. It’s important to recognize that both types of AI have their strengths and can complement each other in various applications.
Metrics Favoring Predictive AI
Predictive AI is particularly favored for metrics such as:
- Revenue Improvement: Driving sales through accurate forecasting.
- Accuracy: Enhancing decision-making processes.
- Cost Reduction: Streamlining operations to save money.
The Evolution of AI Metrics
Tracking Success Over Time
Omdia’s AI Business Performance Metrics Database, updated twice a year, tracks case studies from AI vendors and end users. This resource provides valuable insights into how metrics for measuring AI success have evolved and how they differ across industries and applications.
Insights from the Database
The database reveals that since GenAI’s market entry, there’s been a growing emphasis on quantifiable outcomes. Enterprises are keen to demonstrate the real-world impact of their AI investments, with a focus on specific numerical metrics.
Conclusion: The GenAI Revolution
In summary, generative AI is reshaping how enterprises measure success. GenAI is proving to be a powerful tool for driving business outcomes by focusing on productivity, ROI, and customer engagement. Omdia’s research provides valuable insights into the impact of GenAI and highlights the importance of tracking AI metrics. As we move forward, staying ahead of AI trends will be key to leveraging its full potential.
Who is Omdia? Generative AI productivity ROI
Omdia, part of Informa Tech, is a technology research and advisory group known for its deep knowledge of tech markets and actionable insights. Their work empowers organizations to make informed growth decisions.
