A recent article entitled Generate Value From GenAI With ‘Small t’ Transformations by Melissa Webster and George Westerman caught my attention. The authors posited that business leaders get real value from large language models by working their way up the risk slope and building the foundation for larger future transformations. However, they came up with an interesting strategy to test their question. They wrote, “As business strategists, we wanted to see what generative AI could add to our work. We explored this question through experiments on different aspects of the strategy creation process. In each experiment, we put a realistic strategy question to ChatGPT, followed by a lengthy back-and-forth to refine the initial responses. The intention was to understand how the tool can support ideation, experimentation, evaluation, and the building of stories—and where it falls.”
Basically, they used ChatGPT and generative AI (GenAI) to create and refine the strategy. I found this approach very interesting for the compliance professional. From this approach, they learned lessons in three uses applicable to the compliance professional.
- GenAI in Tasks That Are Common to Individuals in Many Roles
- Specialized GenAI for Compliance Professionals
- Enhancing the UX
Common Tasks. Compliance professionals can use large language models (LLMs) in ways that are useful to many compliance roles, such as writing, synthesizing information, generating imagery, and documenting meetings. GenAI’s near-ubiquitous nature can have a real impact on your compliance function. You can buy or create integrated tool sets that link generative AI to other functions that compliance professionals typically perform. Benefits vary by use and user, with individual initiative-taking and prompting skills influencing the value they derive.
Consider adding compliance-specific intelligence by training models on terminology and information that are proprietary to the company. For example, the authors point to the “Global consulting firm McKinsey built Lilli, [which built] a platform that links generative AI to its intellectual property from over 40 internal sources. The effort involved significant technical hurdles; for example, the tool needed to be changed to read PowerPoint slides, one of the company’s main ways of communicating project information, but the platform is providing value. For instance, if a consultant has a question about green energy business models in less-developed economies, Lilli can quickly find and synthesize information from projects that have already studied the problem somewhere in the world. McKinsey has reported that the platform’s capabilities and robust employee education led to about 75% of employees actively using Lilli in less than a year, time savings of up to 30%, and substantially improved quality.”
McKinsey is not alone in developing these specialized models for the general workforce. The same approach would work for a compliance function.
Specialized GenAI for Compliance. In this category, the authors say that “companies working their way up the risk slope are developing generative AI capabilities to improve productivity and quality in specific job roles or business processes. There is less tolerance for unacceptable output here.” These GenAI resolutions “typically maintain a human in the loop, where employees interact with the tools and review the outputs rather than allowing the GenAI tools to make decisions or produce outputs automatically.” Moreover, such outputs would seem directly suited for the compliance function.
In the space adjacent to compliance, the world of corporate finance, the authors found that “finance teams are relatively late adopters of new technologies, with CFOs citing technology gaps, data concerns, and competing priorities as reasons for that lag.” What does that sound like? Many legally trained corporate compliance officers.
The authors cited, “One international energy company we studied created a tool using a mix of GenAI, traditional AI, and other algorithms to suggest mitigations or help rewrite an audit report. Other companies use generative AI to assist in drafting reports for audits or regulatory compliance. At Amazon, the finance function uses rules-based AI, machine learning, and LLMs to address tasks in fraud detection, contract review, financial forecasting, personal productivity, interpretation of rules and regulations, and tax-related work.” Such a tool could move compliance professionals from repetitive tasks to focus more on work involving critical thinking.
Enhancing the UX. The next step for GenAI in compliance is with its customers, i.e., corporate employees. Just as GenAI is transforming traditional customer service and retail engagement, it can do so for interactions by compliance and employees. Unlike traditional phone menus or robotic process automation (RPA) chatbots, GenAI enables dynamic, multilingual responses, enhancing customer experience while optimizing operational efficiency. Take the example of John Hancock, which has implemented AI-driven chatbots to manage routine inquiries, allowing human agents to focus on more complex customer needs. This shift improves response times, reduces costs, and increases employee efficiency. Now, apply that strategy to your employees.
Beyond text-based interactions, GenAI is expanding into voice-based customer engagement. Companies like Starbucks, Domino’s, CVS, and major banks are integrating AI-driven voice assistants with future applications that will likely include video-based interactions. Compliance can also use all of these strategies.
By pursuing small-t transformation, often with a human in the loop, as they build capabilities, your compliance team can enable the development of applications with higher value and risk. The authors list several actions a Chief Compliance Officer (CC) can take to generate transformation with generative AI.
- Identify key pioneers in your organization and develop your messaging. With generative AI, innovation often comes from “cyborgs”—early adopters who integrate the technology into their work and are motivated to use it to solve a problem for themselves or their customers. Use them to communicate your innovation vision.
- Assess your company’s current position on the risk slope. What are you already doing, and what would be the next level of complexity and reward? Look at opportunities in individual productivity, role-specific enhancements, and innovations in product or customer engagement.
- Consider scalability. The authors noted, “According to the head of AI at a large bank we spoke with, “the more stuff you do, the more stuff you find to do.”
- Secure management buy-in. Small-t innovations can help to make the value story real and make the case for investments that can reduce the perceived risk of larger opportunities.
- Investigate foundational investments. Some of the boldest use cases will require extensive investment in data cleansing, model training, and integration before they can be ready for a real-world test.
- Maintain a long-term perspective. “The transformative cases take longer to build the business case, test the models, change behaviors, etc.,” said Chris Bedi, chief customer officer at software company ServiceNow. “The challenge is not only technical but also leaders taking time to reimagine their future with big ideas.”
The bottom line is that while productivity gains are the expected and common benefits of applying GenAI to specialized roles and tasks in compliance, the technology’s true impact extends further. GenAI is fundamentally transforming what compliance professionals can achieve. GenAI is enabling innovations and reshaping traditional compliance processes by enhancing efficiency and expanding the realm of possibilities within various functions.
