How are you approaching generative AI adoption in your organizations? Are you focusing first on quick-win use cases (like chatbots/automation) or deeper integrations into core platforms?

We have a 2-pronged approach. We definitely are exploring AI solutions to fit use cases from the business, but at the same time we have identified core capabilities that we either need now or will need and are exploring how to develop / implement those capabilities. We have a color-coded AI roadmap that shows the plans for both efforts - use-case-based exploration / development vs. capabilities. I suppose a third prong would be the low- and no-code solutions that we are encouraging our staff to explore, so that they can create their own low-complexity solutions and prompts.

We began with standalone, high visibility use cases where results could be clearly demonstrated, which helped build early momentum. Notably, leveraging LLMs with GraphRAG yielded faster and more effective outcomes, leading to quick buy-in from the leadership team. As we move toward deeper platform integrations, we recognize the need for a more robust and well-vetted architecture.

We began with a set of small use cases that utilized Copilot to enhance individual efficiencies. We are now moving to include more complex and integrated AI solutions that would result in medium to large-scale transformation.

AI Adoption can be viewed from two perspectives, firstly employee personal efficiency by using AI tools like copilot, and secondly more collective and company based efficiency and process improvement. For both its important that the business is aware of the risk and security concerns, so whether your going for quick-wins or larger transformational initiatives this should be your number one priority. I'm sure your key stakeholder would also want to know if there is ROI for any adoption, as this is important.

We started with quick-win use cases to drive adoption and learning about AI at the company. Shortly after, platform teams started investigating AI solutions on virtually all software that we manage and we're investigating capabilities that we can utilize for deeper integrations.