Issues / #94
is nimsforest adressing all these - plan for it 25 questi...
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question
Project: nimsforest2
Reporter: anonymous
29 Apr 2026 21:12
Description
is nimsforest adressing all these - plan for it 25 questions every exec should ask as they transform their business with AI:
1) How can I tell the difference between AI activity and AI productivity?
2) Which of our current competitive advantages get eroded or amplified by AI becoming more widely used?
3) How do we have a cohesive AI strategy vs. a bunch of experiments with no clear process or rigor?
4) What is our responsibility for AI upskilling vs what is our employees?
5) How do we make sure we're not just adding AI to existing products/processes but starting from scratch and using first principles to reimagine them?
6) How do we message our AI strategy in a way that is honest and empathetic to employees?
7) What does "transforming your business with AI" actually mean? What is the menu of opportunity?
8) If a task drops from $100 to $1, what’s worth doing that wasn't worth it before?
9) What is our risk framework for making go/no decisions on AI tooling & systems?
10) How do we create a culture of experimentation and exploration for employees while mitigating unpalatable security risk?
11) How do we bubble up AI use cases and opportunities through employees and prioritize and productionize those opportunities from the top?
12) How does leadership get their hands dirty and walk the walk with AI proficiency and building to effectively lead by example?
13) How do we have a data strategy that gets us progressively AI ready, but also doesn't hold us back from beginning our transformation today?
14) Where do we start?
15) How do we build AI systems and solutions that have harnesses that are model agnostic, so we're well positioned for a dynamic and volatile market?
16) How do we test for AI curiosity, literacy, and interest during our hiring process?
17) How do we make “the bad guys” (IT, legal, compliance) partners and heroes in our AI transformation story?
18) How true is the "we can redeploy people to do higher value tasks" narrative?
19) How do you transform a company culture to start embracing/experimenting with AI when most employees are apathetic or fearful of AI replacing them?
20) Should AI transformation be owned by a central team/steerco or embedded in every function?
21) What are the risks of doing this and not doing this?
22) How do we find the AI A players and make what they do the "gold standard" across our org?
23) What other businesses have transformed successfully using AI? What businesses have failed? How can we apply lessons learned from both?
24) If a competitor launched tomorrow, AI-native from day one, what would they do differently, and why aren't we?
25) If we become dependent on external AI vendors, what happens if the cost of LLMs skyrockets?
1) How can I tell the difference between AI activity and AI productivity?
2) Which of our current competitive advantages get eroded or amplified by AI becoming more widely used?
3) How do we have a cohesive AI strategy vs. a bunch of experiments with no clear process or rigor?
4) What is our responsibility for AI upskilling vs what is our employees?
5) How do we make sure we're not just adding AI to existing products/processes but starting from scratch and using first principles to reimagine them?
6) How do we message our AI strategy in a way that is honest and empathetic to employees?
7) What does "transforming your business with AI" actually mean? What is the menu of opportunity?
8) If a task drops from $100 to $1, what’s worth doing that wasn't worth it before?
9) What is our risk framework for making go/no decisions on AI tooling & systems?
10) How do we create a culture of experimentation and exploration for employees while mitigating unpalatable security risk?
11) How do we bubble up AI use cases and opportunities through employees and prioritize and productionize those opportunities from the top?
12) How does leadership get their hands dirty and walk the walk with AI proficiency and building to effectively lead by example?
13) How do we have a data strategy that gets us progressively AI ready, but also doesn't hold us back from beginning our transformation today?
14) Where do we start?
15) How do we build AI systems and solutions that have harnesses that are model agnostic, so we're well positioned for a dynamic and volatile market?
16) How do we test for AI curiosity, literacy, and interest during our hiring process?
17) How do we make “the bad guys” (IT, legal, compliance) partners and heroes in our AI transformation story?
18) How true is the "we can redeploy people to do higher value tasks" narrative?
19) How do you transform a company culture to start embracing/experimenting with AI when most employees are apathetic or fearful of AI replacing them?
20) Should AI transformation be owned by a central team/steerco or embedded in every function?
21) What are the risks of doing this and not doing this?
22) How do we find the AI A players and make what they do the "gold standard" across our org?
23) What other businesses have transformed successfully using AI? What businesses have failed? How can we apply lessons learned from both?
24) If a competitor launched tomorrow, AI-native from day one, what would they do differently, and why aren't we?
25) If we become dependent on external AI vendors, what happens if the cost of LLMs skyrockets?