Using AI For Enterprise Skills Enablement

Reena Tiwari, the former Chief Information Officer at LexisNexis, views artificial intelligence as both a set of practical capabilities deployed across products and a foundational skill every employee should understand and leverage. In her view, AI isn’t just a technical tool; it’s a democratizing force that can improve productivity, shape how teams work, and expand what legal professionals are capable of doing each day.

LexisNexis, a global leader in legal research and analytics with more than 10,000 employees in over 160 countries, has been applying AI technologies for years. Tiwari described not only how LexisNexis uses AI in today’s legal environment but also how she is empowering teams to build skills, challenge legacy processes, and approach AI adoption thoughtfully and strategically.

AI Isn’t New, But Context Matters

Tiwari points out that AI, in forms like natural language processing, machine learning, and deep learning, has been part of LexisNexis’s products and solutions for over a decade. These technologies power capabilities that many users take for granted, such as advanced search, document analysis, and legal insights delivered at scale.

Yet, she also recognizes that the AI conversation today, especially around generative AI, feels different because it touches every individual. As she explained, the latest wave of AI is not just enterprise software: “ChatGPT, for example, because of them enabling every single user or every single individual … that’s why I feel the hype is really, really high…” and it’s accessible in a way previous technologies were not.

This accessibility creates both opportunity and challenge for technology leaders. The hype can obscure real value unless organizations ground their thinking in the actual problems they want AI to solve. Tiwari’s approach for her team is to start by educating themselves first, understanding what generative AI is, how it differs from earlier analytics or predictive models, and where it can play a meaningful role in business processes.

Real AI Impact in Legal Technology

In a legal context, the risks of undisciplined AI use are real. Tiwari shared a cautionary example where a lawyer used a generic AI tool to draft a case summary, only to discover that the case didn’t exist. These kinds of “hallucinations” are a known limitation of many public generative models that lack access to verified, authoritative data sources.

That’s where LexisNexis’s approach differs: the company blends cutting-edge models with real, structured legal data that users trust. As Tiwari explained: “…they don’t have real data behind them… because it’s gleaned from websites and they can’t name the source of the information. That’s where we bring value. We use the latest and greatest technology … and use that data we have … to create [Lexis+ AI] … the solution we provide … is real and it helps them in improving their productivity and efficiency.”

Lexis+ AI, a generative AI-enhanced suite of capabilities, includes features like conversational search, document drafting, summarization, and document upload analysis. These tools help legal professionals quickly produce contract clauses, draft arguments, or extract insights from complex documents, significantly reducing manual effort and accelerating outcomes.

Democratizing AI for the Everyday Worker

A central theme in Tiwari’s leadership is democratization, ensuring AI isn’t confined to a small group of specialists or siloed teams. She made this plain: “It shouldn’t be this one person sitting in the ivory tower on top … No, everybody should be using those kinds of tools and technologies to improve their day to day lives.”

This philosophy drives her emphasis on skills enablement. Rather than waiting for formal “AI teams” to build everything centrally, she encourages people to understand AI, ask “how could this change the way we do our work?”, and experiment with new tools and techniques.

As she coaches her team: start with education to understand what generative AI is and how it differs from traditional analytics, and then question existing processes: how do you write code, how do you document, how do you perform QA, how do you deduplicate data? At each step, ask: is there a better way to do this with AI?

This bottom-up approach helps align AI experimentation with real business problems, reducing the risk of chasing shiny technologies without measurable impact.

Enterprise Opportunities Beyond Legal Research

While Lexis+ AI drives real impact in the core legal domain, Tiwari also sees broader enterprise opportunities with AI — particularly in areas like sales, marketing, and customer support automation. She highlighted the potential for AI to:

• automate routine tasks in sales and marketing, freeing teams for higher-value engagement;
• improve conversational experiences for customers using intelligent interfaces;
• surface actionable insights from reporting and operational data in real time.
  

Tiwari painted a picture of future enterprise tools where leaders don’t have to sift through dashboards and static reports. Instead, AI could deliver real-time, predictive insights in accessible formats, like a constantly updating “ticker” that informs decisions on the go.

Building an AI-Ready Workforce

Tiwari sees AI skills development as a continuum, not just for IT professionals, but for every employee, regardless of role. She argued that technical literacy, including programming and AI fluency, should be as fundamental as subjects like math and English.

Within her organization, this translates into encouraging training, tracking metrics about who’s learning new technologies, and rewarding those who bring innovative ideas forward. These practices help create a culture where innovation isn’t siloed but becomes part of everyday work.

She also emphasized balancing demands: while running the business (keeping the lights on), enhancing existing systems, and undertaking major transformation work, organizations must protect space for innovation so that it doesn’t vanish amidst operational demands. Disciplined focus on AI and emerging technologies ensures that innovation continues even as business processes evolve.

Lessons Learned

Across her conversation, Reena Tiwari shared clear insights for leaders navigating AI at scale:

• Ground AI adoption in real problems. Start with education and use case identification before chasing technologies.
• Democratize tools and skills. Don’t reserve AI for a privileged few, equip everyone with the knowledge to use AI to improve their work.
• Leverage trusted data. AI outputs are only as valuable as the data they’re built on; in legal domains, source attribution and accuracy are paramount.
• Think beyond product to process. AI can reshape internal operations, from sales to reporting, not just external customer interfaces.
• Cultivate continuous learning. Track training, reward innovation, and keep space for experimentation even during transformation.

Reena’s vision for AI at LexisNexis is both practical and aspirational. She embraces pragmatic experimentation with AI while insisting on responsible use, grounded in real data and tied to measurable outcomes. By empowering teams, not just specialists, with the skills to leverage AI meaningfully, she is helping shape a future where technology amplifies human judgment, accelerates productivity, and transforms how enterprise work gets done.