So where were our respondents along the maturity spectrum? We received a balanced mix of responses: - Some gen AI applications in pilot phase (not production) - Some gen AI applications in production - Mostly in the planning stage, no apps in production or pilot - Mostly waiting and seeing before investing resources All in, about two-thirds of our respondents are either in production (in some capacity) or operating pilots today. This about 10% better than McKinsey’s numbers back in August, demonstrating that more and more companies are starting to lean in on AI adoption (or perhaps that this cohort is just a little more engaged). But taking the next steps will require a more strategic approach: – Based on the aforementioned areas of assessment, gaps must be identified and addressed – There should be a 3–5-year strategy in place outlining the organizations AI/ML goals and objectives – In both robust and scalable AI/ML infrastructure as well as in personnel – a dedicated team of professionals will be necessary – Once the roadmap is underway, it’s important to establish clear protocols around governance (policies and best practices) + culture (data-driven decision making) – As AI/ML is integrated into the org’s business processes and product development lifecycle, impact should be closely measured and monitored via robust KPIs