How startups can use generative AI from ideation to implementation

The day ChatGPT debuted, this transformational technology captured the imaginations of business leaders and changed decision-making forever. Today’s C-suite sees incredible upside opportunities with generative AI. Set to drive a $7 trillion increase in GDP and boost global productivity by 1.5%, generative AI and its tangible economic consequences have reimagined business priorities for decades — and potentially generations — to come.

ChatGPT and other generative AI technologies have opened the door to breakthrough thinking across all industries. Some technology and business leaders are thinking about unintended consequences — in particular, the “hallucination” problem. Sometimes, ChatGPT’s hallucinations are innocuous and easily corrected by improving training data or adding a human into the loop. As the world races to adopt this technology, we have to continue to work on improving the error rates and decreasing the hallucinations.

Above all else, financial decision-making and compliance are predicated on data accuracy and confidence in the information. So, while it’s annoying to have ChatGPT generate a wrong answer for noncritical prompts, data errors across an investment portfolio could translate to lost revenue, missed regulatory filings and a complete distrust of the technology.

Fortunately, technologists can take a step back and ask the following questions to unlock the potential power of generative AI.

Do we have a phased approach?

Generative AI will have far-reaching consequences across a business’s workflow and the products it brings to its customers. R&D and go-to-market teams should follow a playbook so every part of the organization can innovate responsibly and efficiently. To start, tech teams must take a “square one” approach and examine their use cases, infrastructure needs, goals, and next steps.