“In summary, here are a few pieces of advice when building a generative AI competency:
- Don’t boil the ocean by chasing 100 use cases in parallel. Be laser-focused and try things, but focus on taking three proof of concepts into production with a proven financial payback and not just metrics around ‘time saved’.
- Don’t use generative AI as a hammer for every nail in the many situations where predictive AI will deliver the same result and is already out there and proven.
- Don’t go recruiting skills. Whenever possible, upskill your people. It is a terrific way to recognize your talent. Look for people who are interested in learning. Make room for them to upskill. Focus on prompt design skills and prompt action/workflow skills for those outside IT and data skills for people inside IT.
- Focus on the flow of work. Generative AI is most impactful in the flow of a sales process, a customer support process, a marketing process, an ecommerce process, and a field service process.
- Beware of copilot proliferation. One copilot per application that needs to be maintained and supported — imagine 1,000 apps with 1,000 copilots.
- Unless you’re a mega bank or tech company, focus your model-tuning efforts on two or three industry-specific use cases and use out-of-the-box tech from your existing suppliers for the rest.
- Most importantly, focus on data quality, access, and governance. These are the fuel that AI needs, so it requires investment — and likely more investment than the AI investment itself.
- Write to us. We love fielding questions and sharing what we know: mmaoz@salesforce.com for Michael and ed.thompson@salesforce.com for Ed”