market, which includes hardware, software and services, has the potential to grow, on average, 27 percent for the next three years, according to the research firm. “We do feel that this is going to accelerate, and it’s going to accelerate in a significant way,” Hasan said. For Quantiphi, most of its growth came before ChatGPT, a chatbot powered by a large language AI model, entered the pic- ture last fall. ChatGPT sent shockwaves through the tech industry with its ability to understand complex prompts and respond with an array of detailed answers—from blog posts on a variety of subjects to software code for web browsers and other kinds of applications—all offered with the caveat that it could potentially impart inaccurate or biased information. Nevertheless, enterprises are now rushing to figure out how to take advantage of generative AI, a broad category of AI models
tive AI strategies and what they need to build custom applications that leverage proprietary information since there are risks in sharing data with consumer-facing applications like ChatGPT. “If you don’t control that model, how would that information be leveraged to provide an answer to another party when they make a prompt into an outsourced model because that’s an API call?That’s a concern that has come up time and again with CIOs and CISOs that we’ve spoken to,” Brooks said. The issue with building a large language model from scratch that is like ChatGPT but protects proprietary data is that develop- ment can cost up to $100 million, according to Brooks. Fortunately, a middle ground has already emerged for enter- prises: Large vendors like AmazonWeb Services, Google Cloud, MicrosoftAzure and Nvidia are now offering pretrained models, among other kinds of building blocks, that solution providers can
that includes ChatGPT and renders new con- tent of different forms, including text, images and video, using large data sets.The trend has already invaded new features of major software staples like Microsoft 365 and a bevy of cybersecurity offerings. “What ChatGPT has done is given a lot of
use to develop custom generative AI solutions for customers. To Brooks, it’s a major opportunity that will require a diverse range of skills to ensure custom applications are pulling from the right data sets and providing the right kind of responses.
‘What ChatGPT has done is given a lot of people in a lot of di erent scenarios the rst glimpse of what a generative AI system could look like. It’s impressed a lot of people. It’s left a lot of people unsettled.
… But everyone is intrigued by it.’ — Asif Hasan, Co-Founder, Quantiphi
“It is something where we’ve had to really use our experience in security, data governance and data science as well as leverage our relationships with OEMs,” he said. But the generative AI opportunities in the channel don’t have to end with the development and management of applications. For NewYork-based global consulting giant Deloitte, there is also an opportunity to advise customers on best practices for ensuring their employees can take advantage of these disruptive tools. “How do they relearn that new way of doing things and ensure that they are working with the technology?A lot of the benefit of generativeAI is about augmenting human capability and advanc- ing it. So that also requires humans to relearn the way they do things,” said Gopal Srinivasan, a longtime Deloitte executive who leads the firm’s generative AI efforts with Google Cloud (see Q&A with Srinivasan on p. 11). Meanwhile, one solution provider that has already seen the promise of generativeAI in action for enterprises is LosAngeles- based SADA Systems. The situation: A 3-D manufacturing company was dealing with low utilization of its laser-cutting product among customers, so it wanted to use a text-to-image model to kickstart the creative process for users and give them a quick way to make designs. MilesWard, CTO at SADA, said the company provided guidance and, after the design generation tool went live, the laser-cutter vendor saw a 50-fold increase in usage the following week.
people in a lot of different scenarios the first glimpse of what a generative AI system could look like. It’s impressed a lot of people. It’s left a lot of people unsettled. … But everyone is intrigued by it,” Hasan said. Now Hasan is trying to keep up with the new interest sparked by generative AI. For the past few months, he’s been holding up to three executive briefings a day to answer a surge of customer questions and discuss new projects around the technology. “We are seeing at the top of the funnel interest levels at a scale we have never ever seen before in the last 10 years,” Hasan said. Generative AI: A Wild West Of Services And Products Tim Brooks, managing director of data strategy and AI solutions at St. Louis, Mo.-based WWT, said enterprises used to spend much of their time thinking about what kind of infrastructure they needed to power AI applications. But now thatAI infrastructure has become ubiquitous, Brooks has noticed that customers of the solution provider juggernaut have turned their focus to much finer details of AI projects, such as data governance, model risk management and other issues that can play a role in a project’s success. “I would say five years ago that rarely came up. Now that comes up in every conversation,” said Brooks.This is especially important now that many enterprises are trying to figure out their own genera-
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