IT leaders looking for a blueprint for staving off the disruptive threat of generative AI might benefit from a tip from LexisNexis EVP and CTO Jeff Reihl: Be a fast mover in adopting the technology to get ahead of potential disruptors.
Since its origins in the early 1970s, LexisNexis and its portfolio of legal and business data and analytics services have faced competitive threats heralded by the rise of the Internet, Google Search, and open source software — and now perhaps its most formidable adversary yet: generative AI, Reihl notes.
Reihl concedes that generative AI is evolving much faster than anything he has seen in his career, which spans nearly four decades in IT leadership roles. To address this new reality, his company’s C-suite convened to strategize after the debut of OpenAI’s GPT-4 last March. The meeting consensus? To rewrite and reprioritize all the company’s annual goals to address the new innovations head on.
“We were all-hands-on-deck,” Reihl says. “We did a major pivot because this was a game changer in terms of its interactive abilities, as well as the comprehensiveness of its answers and its data generation capabilities. It was just staggering in terms of its capabilities.”
Given LexisNexis’ core business, gathering and providing information and analytics to legal, insurance, and financial firms, as well as government and law enforcement agencies, the threat of generative AI is real. But Reihl is confident that LexisNexis can tackle generative AI’s advances due to imperfections in today’s general-purpose large language models (LLMs), as well as the proprietary data and unique tools LexisNexis has honed to enhance and customize the LLMs it uses for its services, including Anthropic’s Claude AI assistant and GPT-4 on Microsoft Azure.
LexisNexis’ 2,000-plus technologists and around 200 data scientists have been working feverishly to incorporate unique features that exploit generative AI and add more value for the company’s global customer base. But the foray isn’t entirely new. LexisNexis has been playing with BERT, a family of natural language processing (NLP) models, since Google introduced it in 2018, as well as Chat GPT since its inception. But now the company supports all major LLMs, Reihl says.
