We've had over 200+ conversations with 70+ companies ranging in scale from ($100M in to Billions in revenue) about Generative A.I..
One of the trends I've seen is the formation of A.I. Councils or A.I. Steering Committees. These types of groups can be really in helpful in understanding how a technology might impact your organization. They can pull together thoughts and perspectives across departments, and build a very strong and cohesive strategy around how you go to market with new tech. That said there's two pitfalls that I've started seeing more and more with these committees:
- Don't let it be a solution in search of a problem. For good reason there are executives or board members telling companies to make use of A.I. That A.I. will be a transformative technology that they need to employ or be left behind in the dust. That's great in creating urgency, but don't forget that you need a real business case to make use of the technology. You need to make sure you're focused on the large pain points that exist within a department or across departments first. Figured out what the most pressing problems are first, and then see where GenAI can help. I'm confident that there's broad applicability with GenAI, but you will get much better impact and adoption if you start with the problems first.
- Don't let F.U.D. (fear, uncertainty, doubt) get in the way accelerating your adoption. Yes, this is very new tech (built on decades of work, for sure). Yes, A.I. is non-deterministic and introduces new risks unlike other tech. And yes, there's a slew of questions about how invest in the right platforms for the long-haul. But you can't afford to let that slow you down. The companies that were the fastest in adopting SaaS and cloud technology were the companies that grew the fastest in the last decade. Decision by committee usually means you're getting to a decision more slowly and with less risk. But, this is one area you can't afford to be slow in. This is one of the main reasons we're creating elvex. We want to accelerate your adoption of A.I., while hopefully taking most of the risk and complexity off the table.
For those in enterprise or those working with enterprise what are you seeing? Agree or disagree. The more we share, the more confident we'll all get about how to best use A.I.