Shannon Cross: Okay. Interesting. Yes. Arvind, can you talk a bit about AI and how it runs through your business? There’s obviously so much discussion right now about OpenAI and Microsoft making investments? And I guess I’m trying to think about how we should think about IBM monetizing it, capitalizing on it, how you think about your competitive position relative to others. I don’t know if there are examples you can give where you’re utilizing it. But I’m just — I’m wondering, as AI gets more and more of a — becomes more and more of a discussion point apparently for 2023 and you have such a long history with it, how we should think about where you are now and where you’re going to take it? Thank you.
Arvind Krishna: Thanks Shannon. So, first, let me acknowledge AI has become a big topic of conversation this year. I was in Davos last week, and it probably came up at almost every single discussion around technology, what’s happening with AI as well as what’s happening with OpenAI. If I think about it over the last decade, I think there were three moments you can talk about, and then I’ll begin to translate those into a business impact. One, when IBM won Jeopardy! with Watson, I think it was a big moment, and AI came on to everyone’s roadmap. Second, when deep mind from Google or Alphabet started winning competitions around, for example, GO, and that became another big moment along with the protein folding that they did and now with OpenAI and ChatGPT.
But if I step back just a moment, all of this latest version is based on what is called large language models as the underlying science. Universities do it, Google does it, IBM does it as does OpenAI. To just get to why it’s so exciting. For example, for us, it allows us to do 13 language models when we are looking at understanding different natural languages in the same cost as originally one. That is what is so exciting about these technologies because if you can get an order of magnitude improvement in cost and speed and the resource consumed, both in terms of hardware and people, that is incredibly exciting. Now, let me translate this into how do we monetize this. So, our monetization of AI is very much focused on that $16 trillion of productivity that I’ve talked about that we’re going to get over the decade.
The vast majority of that comes from enterprise automation, and when I say enterprise, I include governments into it. Some examples, if you can automate the drive-through and order taking for quick-serve restaurants, that’s an example of what can happen. If we can get deflection rates of 40%, 50%, 60% at everyone’s call centers, that’s a massive operational efficiency for all of our clients. If we can help retirees get their pensions through interacting with a Watson-powered AI chatbot that is an enterprise use case where all of these technologies come into play. By the way, all my three examples are real clients where we are resulting in anywhere from hundreds to thousands of people, efficiency for each of these clients. So that’s how we get it.
If I look inside IBM, how we do promotions, how we do people movement, how we begin to improve our code to cash, how we improve our customer service and people ask complicated questions around triage of IT systems going down are all very real examples where we are improving client service and saving money all at the same time.
Patricia Murphy: Shannon, thank you very much. Sheila, can we go to the next question.
Operator: Our next question comes from Erik Woodring with Morgan Stanley. Your line is open.
Erik Woodring: Hey, guys. Good afternoon. Thanks for taking the question. I wanted to just touch on the consulting business. Signings were very strong in the December quarter, up 17%. Your quarterly book-to-bill was an improvement from the September quarter. Can you maybe just, again, just step back and elaborate on the environment, what we’re in, what you saw in 4Q that potentially stood out to you where strength in signings is coming from changes to contract duration? Maybe just double-clicking on the consulting business. Just to help us understand what gives you confidence to be kind of at the high end of your midterm model for 2023? Thanks.
Jim Kavanaugh: Thanks, Eric, for the question. I’ll take this. When we entered the fourth quarter, we had a pretty solid pipeline. And we talked about reaffirmed mid-teens growth for consulting for the year, which as you know, is well above our model. But again, as I talked about on the previous question, we had made the investments in bringing in skill capability, expanding ecosystem, strategic partnerships and acquisitions. But we saw that pipeline entering the quarter we saw a very solid and pretty disciplined sales closure rate as we move through the year. Now, how did the year end that positions us for 2023 and let me just put some stats to really bring it home. Number one, ecosystem velocity, we saw continue to increase throughout the year of our strategic partnerships.
I think we said in the prepared remarks, strategic partnerships, one grew revenue 25% in 2022 and was about 40% of our consulting base of business. That is up about 50% year-over-year. We have saw €“ seen extensive acceleration. And by the way, in the fourth quarter, our signings growth which delivered a 1.3 book-to-bill, our hyperscaler partnerships with Azure and with AWS, our signings were 2x. And our ISV portfolio with the likes of SAP, Salesforce, Adobe, we were up over 50% in signings. So our book of business and the partnerships we have tremendous strength that’s fueling our backlog, point number one. Point number two, Red Hat. We continue to see acceleration of consulting being the tip of the spear that’s really driving the scale and adoption of our hybrid cloud platform.
And oh, by the way, is also dragging IBM technology and software. Since inception, a little over three years, we signed $7.4 billion of business in Red Hat, tremendous strength and that, again, fuels our backlog for 2023. And then you look at full year, we grew both large transformational deals, and we grew small deals double digit, both sides. So it’s pervasive across the board. So when we look at our backlog, we look at all of our indicators of our business on the realization of that model. We look on the acquisition portfolio and how it’s scaling. We feel pretty confident about the high end of our high single-digit model in 2023. Oh, by the way, to Toni’s question, at operating margins being accretive.
Patricia Murphy: Erik, thanks for the question. Let’s go to the next one please.
