Brad Reynolds, Senior Vice President – Artificial Intelligence at Expedient speaks with Robert Lutton, VP, Sandhill Consultants, and Editorial Board Vice Chair, CDO Magazine, in a video interview about, the use of generative AI in enterprises, showing quick results with AI, strategies to couple AI with private data, and controlling shadow AI.
Expedient helps companies transform their IT operations through cloud solutions and managed services including disaster recovery, security and compliance, and more.
Shedding light on the use of generative AI in enterprises, Reynolds draws a picture where everyone, from the CEO to individual contributors, can see the output of generative AI systems. The organizational objective, he says, is to marry the private data with generative AI capability responsibly.
Adding on, Reynolds mentions unlocking the organizational memory through the data as he believes that answers exist inside the company. The extraction part is challenging, he adds, which involves asking the right questions to the subject matter experts.
He elaborates that the organization is looking at taking baby steps by coupling generative AI with data responsibly and is in the planning and early execution phase
In continuation, he mentions that in the early phase, the organization is also looking at enabling AI in existing vendor applications, instead of building applications in-house. This is being done to educate the company via actually using AI.
When asked about showing quick results with AI, Reynolds mentions implementing enterprise chat solutions as the “lowest hanging fruit.”
According to Reynolds, it will take some time for people to realize the value of the conversation which also involves data. He refers to the prompting guide released by OpenAI and discusses the remedial effects and things that influenced his interaction with it.
Moving forward, Reynolds believes that all the interesting use cases will come from subject matter experts and not necessarily from the smartest technical person in the room. Therefore, it is critical to give power in their hands that enables flexibility and risk-taking.
After having that acumen inside the organization, the next step should be assessing how to apply AI to the private data, says Reynolds. To do it responsibly, one must access the knowledge bases around customer support, interaction, and experience and improve that internal data.
Another side to look into is the sales and marketing, says Reynolds. Sharing his experience, he reiterates the importance of client conversations. To develop the knowledge base, Reynolds mentions having systems like Salesforce, email, ticketing, and chat systems, that have developed the knowledge corpus about clients.
Understanding where the client is, and taking them to the next step takes the business forward, asserts Reynolds. While knowledge base and customer support are efficiencies to be gained, he maintains that the sales opportunity decides how the next decade will be for the company.
When asked about bringing shadow AI to light, Reynolds affirms that the organization in the earliest stage should bring in an enterprise chat solution. Otherwise, he continues, the in-house users will keep signing up for ChatGPT at US$ 20 a month, which may not necessarily be in the corporate governance domain.
Therefore, it is fundamental to get people experienced with using AI tools so that they can assess the power of generative AI. Furthermore, it should be done keeping privacy and security in mind.
In conclusion, Reynolds states that various capabilities build enterprise chat systems, including demonstration, integrating single sign-on active directory, assessing login access, PII redaction, and filtering. This builds control around shadow AI and gets the enterprise people experienced with generative AI.
CDO Magazine appreciates Brad Reynolds for sharing his invaluable data insights with our global community.