雪泥鴻爪--IT技術者の随筆

1

Not utilizing AI at all

⚫︎ "Generative AI is full of lies and completely unreliable."
⚫︎ "Our company is analog, so we have no connection to generative AI yet."

⚫︎ "No matter how great generative AI is, it has nothing to do with our company."

2

Initial usage, but entirely left to frontline employees

⚫︎ "I'm interested in generative AI, but it's too early to invest."
⚫︎ "Anyone who wants to try it can do so."

⚫︎ Employees independently sign up and start using AI tools.
⚫︎ Due to a lack of executive support, usage remains at an experimental level and does not contribute much to actual business operations.

3

Executives start investing, but leave the implementation to employees

⚫︎ "We expect significant productivity gains from generative AI and have invested in tools and infrastructure."
⚫︎ "However, the company has no unified implementation strategy, leaving it to individual teams."
⚫︎ "If we introduce famous AI tools, productivity should naturally improve."
⚫︎ "We've invested in expensive generative AI tools, but results are slow to appear, making us skeptical of the frontline teams."
⚫︎ "If we hire data scientists, generative AI adoption will go smoothly." (misconception)

⚫︎ Employees have access to generative AI tools but need to restructure business processes, which takes time before benefits become visible.
⚫︎ Executives tend to view generative AI as magic, leading to unrealistic expectations that are hard to meet.
⚫︎ Some LLM experts exist in the company, but they realize that model expertise alone does not solve real business problems.

4

Executives invest while simultaneously establishing a company-wide implementation process, with clear departmental business improvement KPIs.

⚫︎ Understands that generative AI is not magic.
⚫︎ Instructs all departments to redesign business processes with generative AI in mind.
⚫︎ Tracks each department's productivity improvement rate as a key KPI.
⚫︎ Recognizes the necessity of engineering for AI adoption and strengthens investment in development and IT teams.

⚫︎ Centralizes and manages internal knowledge to make it usable for generative AI.
⚫︎ Redesigns business processes from scratch based on generative AI capabilities.
⚫︎ Visualizes productivity improvement metrics and reflects them in departmental and individual goals.
⚫︎ Accumulates internal experience in utilizing generative AI.