- Should they deploy a AI chatbot now or wait?
- What should they consider as they make that decision?
Statement
PulsePoint should start integrating generative AI capabilities towards bottom level tasks, and slowly building up from there as they further test generative AI’s compatibility with their platform. This decision allows for greater control of its spread, with more time to observe before fully committing to an AI solution. This is important, as it gives time to react to a variety of elements that arise when pivoting your technological solutions, as customers are sure to react as well as the rising potential of generative AI.
While it is a more passive solution, it is well backed. Multiple sources and technological authorities are backing up the capabilities of generative AI, so they should not blatantly ignore it. However, fully committing to generative AI is risky, as models are arguably not consistent. Until they reach a consistency that people are satisfied with, the rollout of generative AI should be slow and controlled.
The experts that weigh on the matter are correct; it is important to approach generative AI with a balance of innovation and caution. By starting with low-risk bottom-level applications, PulsePoint can use AI’s potential while mitigating risks such as data privacy concerns, model inaccuracies, and client pushback. This phased approach ensures smoother integration into existing workflows and allows the company to gather valuable insights to refine its AI strategy before scaling up.
One of the suggestions was to focus on augmenting rather than replacing human efforts. This will foster trust among employees and clients alike. This method respects the traditional relationships PulsePoint has built with its clients while demonstrating the company’s commitment to innovation. With careful planning, transparent communication, and a focus on both immediate gains and long-term adaptability, PulsePoint can effectively position itself as a leader in the generative AI space without jeopardizing its core values or operational stability.
Considerations
The largest considerations that they should consider is that generative AI is a glass cannon, in that while it can significantly boost productivity, it does not handle edge cases and practice thorough review. Usage of generative AI must be investigated carefully for quality. There is a growing idea that generative AI is unreliable (Google AI search, hallucinations in LLMs) that it is important to slowly phase these things in to ensure that any damage done is controllable.
In the pursuit of the new, it is important to make informed decisions. The CEO’s vision of generative AI is focused on what it can bring to the table, which does not consider the vulnerabilities it has. She is focused on generative AI being the next new thing, and has no backing otherwise that they should fully commit to generative AI. Her partnering companies, CTO, and board all are wary of using generative AI to its fullest of capabilities. As CEO, she must be a good listener and consider the words of others.
