Companies with messy data should focus on generative AI tasks like content creation for immediate value. Predictive AI projects, such as churn forecasting, require extensive data cleaning and expertise, making them slow and complex. Generative tools offer quick efficiency gains with minimal setup, providing a faster path to ROI.
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Most companies are not Vanguard tech firms. Rather than pursuing speculative, high-failure-rate AI projects, small and medium-sized businesses will see a faster and more reliable ROI by using existing AI tools to automate tedious, routine internal processes.
Many leaders mistakenly halt AI adoption while waiting for perfect data governance. This is a strategic error. Organizations should immediately identify and implement the hundreds of high-value generative AI use cases that require no access to proprietary data, creating immediate wins while larger data initiatives continue.
To find valuable AI use cases, start with projects that save time (efficiency gains). Next, focus on improving the quality of existing outputs. Finally, pursue entirely new capabilities that were previously impossible, creating a roadmap from immediate to transformative value.
Pega's CTO advises using the powerful reasoning of LLMs to design processes and marketing offers. However, at runtime, switch to faster, cheaper, and more consistent predictive models. This avoids the unpredictability, cost, and risk of calling expensive LLMs for every live customer interaction.
Leverage AI to analyze your year's worth of data to quickly identify top-performing content. AI can then go a step further by summarizing these top pieces or extracting key takeaways, creating new derivative content from your existing assets with minimal manual effort.
