Business software makers in financial management, design and other areas are rolling out generative artificial intelligence tools that pack troves of industry-specific data into customized applications, aiming for an edge in an already crowded market.
By leveraging data gathered from specific business functions—in some cases stockpiled from decades of commercial use—software firms can offer AI tools fine-tuned for distinct applications, industry analysts said. They can also keep underlying algorithms free of extraneous data scraped online from unknown sources, which can produce unreliable results, they said.
“One of the concerns for CIOs with regards to generative AI is understanding the lineage and provenance of the data sources that contribute to the output,” said
Tim Crawford,
CIO strategic adviser at Los Angeles-based enterprise IT advisory firm AVOA. By focusing on human resources, customer experience or digital marketing and media, Mr. Crawford said, “software vendors can ensure that the source data is both relevant and optionally restricted to internally sourced data.”
Adobe Inc.,
whose flagship software is used in areas such as corporate presentations, sales and marketing, last week launched its own generative AI model. Named Firefly, the tool is designed to turn user prompts into images and text effects specifically for commercial use. Adobe says it plans to integrate the new tool into such familiar workplace apps as Photoshop and Adobe Illustrator. Firefly is one of several AI-driven products and services the company unveiled this month.
Photo:
David Becker/Associated Press
Trained on the company’s library of hundreds of millions of professional-grade, licensed stock images as well as lapsed-copyright material, Firefly is designed to guard against results that infringe on intellectual-property rights, among other features tailored for commercial users, said
Amit Ahuja,
Adobe’s senior vice president of digital experience business.
These and other features set the tool apart from general-use text-to-image platforms, such as OpenAI’s Dall-E, which some analysts see as a direct threat to Adobe’s core business.
Through decades of enterprise-market experience, Mr. Ahuja said, “Adobe has been able to understand how AI fits into business workflows.” He said generative AI is a natural extension of that work.
Likewise,
Ashok Srivastava,
chief data officer at TurboTax owner
Intuit Inc.,
said his team is building a generative AI language model for financial management trained on years of interactions with its business customers.
“The ecosystem that we’re in spans everything from consumers to small businesses,” Mr. Srivastava said. That access, he said, gives the company’s in-house model a “deep understanding of the financial domain.”
By pairing company data with generative AI and natural-language technology, the goal is to generate sound financial strategies from users’ prompts, making the task of financial management feel more natural, Mr. Srivastava said.
The efforts come as enterprise-market leaders such as
Microsoft Corp.
,
Alphabet Inc.’s
Google and
Salesforce Inc.
are investing heavily in generative AI capabilities.
Spending in the global generative AI market is expected to reach $42.6 billion by the end of the year, growing at a compound annual rate of 32% to $98.1 billion by 2026, according to market analytics firm PitchBook Data Inc.
Both Salesforce and Microsoft, which plans to invest billions of dollars in ChatGPT maker OpenAI, are already working to integrate ChatGPT and its underlying language model, GPT-4, into a range of core enterprise software products and services, said
Arun Chandrasekaran,
distinguished vice president and analyst at IT research and consulting firm
Gartner Inc.
Google also has an aggressive road map for bringing its own generative AI models to enterprise customers via Google Cloud and G-suite, he said.
This week, several AI researchers and tech leaders, including
Tesla Inc.
CEO
—an early investor in OpenAI—called for a pause in the rapid development of AI tools to give the industry time to set safety standards and guard against its misuse.
Rowan Curran,
an analyst at IT research firm
Forrester Research Inc.
covering data science, machine learning, artificial intelligence and computer vision, said the generative AI ecosystem is “going to be too large and varied for any one vendor, even a ‘hyperscaler’, to dominate the space long term.”
Mr. Curran said he expects to see entry barriers to the generative AI market—such as prohibitively high costs to develop and train models—to loosen over time. That will enable more vendors to offer unique capabilities and fine-tune models that produce better results for the specific context in which they operate, he said.
“The explosion of attention around generative AI is driving the developers and providers of these tools to now launch them at a much faster rate than they may have done otherwise,” Mr. Curran said.
Write to Angus Loten at Angus.Loten@wsj.com
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