At the EDA Summit 2024, Conor Twomey, co-founder of AI One, delivered a compelling talk that resonated deeply with those eager to understand how enterprise AI is evolving. In an era where businesses are under immense pressure to adopt artificial intelligence swiftly and effectively, Twomey's insights provided clarity amidst the noise.
He framed today’s AI movement not merely as another phase in digital transformation but as a critical business opportunity. The urgency for companies to implement robust AI strategies stems from demands by boards, investors, employees, and customers alike. Yet many enterprises falter because they perceive AI primarily as a technological challenge rather than a pathway to growth and innovation.
Twomey introduced his 'crawl, walk, run' framework—a practical approach he has observed across over 650 executive conversations aimed at unlocking ROI through innovation:
Crawl: Start small by enhancing search capabilities. Many organizations begin their journey into generative AI by improving semantic understanding of unstructured data—think of it like creating an internal Google tailored for your company’s needs. This initial step fosters momentum and cultivates a culture open to experimentation through initiatives like hackathons.
Walk: Integrate AI into existing workflows without discarding legacy systems. Companies can enhance data science processes using generative tools that reveal hidden signals or streamline operations—like incorporating real-time social media trends into client outreach efforts for better personalization.
Run: At this stage, forward-thinking organizations reinvent themselves entirely around an ‘AI-first’ mindset. They ask provocative questions about what they would do differently if starting anew—leading them toward unique offerings that set them apart from competitors.
To illustrate these principles in action, Twomey shared two notable case studies:
- Morgan Stanley's Wealth Management Division: By deploying generative AI solutions capable of transcribing client meetings and summarizing discussions automatically, advisors could redirect their focus towards nurturing relationships instead of getting bogged down in paperwork. While seemingly straightforward technology initially seemed unremarkable; its impact was profound—increased efficiency led directly to higher client satisfaction rates and revenue growth.
- BNY Mellon’s Predictive Solutions: Tackling settlement failures within the $22 trillion U.S Treasury market might sound mundane compared to flashy tech innovations—but BNY Mellon's proactive use of predictive analytics saved millions while reinforcing trust among market participants by passing savings back rather than monetizing insights solely for profit.
These examples highlight how even modest applications can yield significant value when aligned with strategic goals centered on customer experience and operational excellence.
