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22 results for “enterprise ai”
Topic3 mentions across episodes
enterprise AI
Topic3 mentions across episodes
enterprise
what you've really got is a a a huge likelihood of a stranded asset out there, natural gas plants that are no longer useful for powering these things that they were built for. The thing about AI for business, it may not automatically fit the way your
34:26 / 35:32
from transcript34:26 – 35:32
The thing about AI for business, it may not automatically fit the way your business works. At IBM, we've seen this firsthand. But by embedding AI across HR, IT, and procurement processes, we've reduced cost by millions, slashed repetitive tasks, and
33:11 / 34:01
from transcript33:11 – 34:01
to the liability management transactions we talked about. Mhmm. So perhaps folks are thinking that that will precipitate. Perhaps it's a reaction to some of the maturity walls that folks understand. Or perhaps it's some of what I was saying in the op
33:44 / 34:50
from transcript33:44 – 34:50
That's shopify.com/built. Every business right now is asking the same question. How do we actually make AI work for us? Because the possibilities are huge, but guessing is risky. And sitting on the sidelines, that's not really an option because chanc
29:13 / 30:16
from transcript29:13 – 30:16
to get started. That's pipedrive.com/simplecrm. So there's a lot of noise about AI, but time's too tight for more promises. So let's talk about results. At IBM, we work with our employees to integrate technology right into the systems they need. Now
16:27 / 17:31
from transcript16:27 – 17:31
30% off. Framer.com/built. Rules and restrictions may apply. Every business right now is asking the same question. How do we actually make AI work for us? Because the possibilities are huge. But guessing is risky. And sitting on the sidelines, that's
42:43 / 43:47
from transcript42:43 – 43:47
and simply handing the industry over to a highly centralized, highly concentrated beef packing and retailing industry. The thing about AI for business, it may not automatically fit the way your business works. At IBM, we've seen this firsthand. But b
34:25 / 35:31
from transcript34:25 – 35:31
Every business right now is asking the same question. How do we actually make AI work for us? Because the possibilities are huge, but guessing is risky. And sitting on the sidelines, that's not really an option because chances are, your already makin
37:31 / 38:33
from transcript37:31 – 38:33
...one AI cloud enterprise resource planning software or ERP, and it's already trusted by over 43,000 businesses. NetSuite is a unified workspace that brings together every piece of your data into one single easy to use interface, and it's the connectin
11:14 / 12:32
from transcript11:14 – 12:32
Sign up for your $1 per month trial today at shopify.com/built. Go to shopify.com/built. That's shopify.com/built. Every business right now is asking the same question. How do we actually make AI work for us? Because the possibilities are huge. But g
39:40 / 40:48
from transcript39:40 – 40:48
So let's talk about results. At IBM, we work with our employees to integrate technology right into the systems they need. Now a global workforce of 300,000 can use AI to fill their HR questions, resolving 94% of common questions. Not noise, proof of
32:59 / 34:02
from transcript32:59 – 34:02
The thing about AI for business, it may not automatically fit the way your business works. At IBM, we've seen this firsthand. But by embedding AI across HR, IT, and procurement processes, we've reduced cost by millions, slashed repetitive tasks, and
36:14 / 37:09
from transcript36:14 – 37:09
How do we actually make AI work for us? Because the possibilities are huge, but guessing is risky. And sitting on the sidelines, that's not really an option because chances are your competitors are already making their move. That's where NetSuite by
59:12 / 1:00:15
from transcript59:12 – 1:00:15
Every business right now is asking the same question. How do we actually make AI work for us? Because the possibilities are huge, but guessing is risky. And sitting on the sidelines, that's not really an option because chances are your competitors ar
33:46 / 34:48
from transcript33:46 – 34:48
That's shopify.com/built. Every business right now is asking the same question. How do we actually make AI work for us? Because the possibilities are huge. But guessing is risky. And sitting on the sidelines, that's not really an option because chanc
28:27 / 29:30
from transcript28:27 – 29:30
Sign up for your $1 per month trial today at shopify.com/built. Go to shopify.com/built. That's shopify.com/built. Every business right now is asking the same question. How do we actually make AI work for us? Because the possibilities are huge, but g
33:45 / 34:45
from transcript33:45 – 34:45
Every business right now is asking the same question. How do we actually make AI work for us? Because the possibilities are huge, but guessing is risky. And sitting on the sidelines, that's not really an option because chances are your competitors ar
22:27 / 23:30
from transcript22:27 – 23:30
So there's a lot of noise about AI, but time's too tight for more promises. So let's talk about results. At IBM, we work with our employees to integrate technology right into the systems they need. Now a global workforce of 300,000 can use AI to fill
28:32 / 29:32
from transcript28:32 – 29:32
So there's a lot of noise about AI, but time's too tight for more promises. So let's talk about results. At IBM, we work with our employees to integrate technology right into the systems they need. Now a global workforce of 300,000 can use AI to fill
27:54 / 28:50
from transcript27:54 – 28:50
The thing about AI for business, it may not automatically fit the way your business works. At IBM, we've seen this firsthand. But by embedding AI across HR, IT, and procurement processes, we've reduced cost by millions, slashed repetitive tasks, and
30:08 / 31:08
from transcript30:08 – 31:08
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