5 use cases for how Generative AI can supercharge document productivity across the enterprise

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5 use cases for how Generative AI can supercharge document productivity across the enterprise

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Alex Gay, Senior Director of Product Marketing, Adobe Document Cloud 

Most business today can be described as MORE—more technology, more meetings, more projects, more data, and more documents. Coupled with the increasing expectations to do more with less, it’s a lot for knowledge workers to handle. In fact, according to MIT Sloan, 80 percent of knowledge workers experience information overload and it’s impacting productivity. Adobe’s Future of Digital Work survey reported that knowledge workers waste nearly a full day (8.2 hours) a week just looking for information they need to do their jobs. 

A lot of that information resides in documents like contracts, financial filings, white papers, sales decks, and research reports. Most of the data in those documents (80-90%) is unstructured, making it especially difficult to analyze and action. Generative AI presents an incredible new opportunity to empower every knowledge worker to get more value from their documents and work more productively. However, deploying generative AI across the organization quickly, yet in a secure and compliant way can be challenging for IT leaders. 

Trust meets value

For more than 30 years, the world’s largest organizations have trusted Adobe Acrobat with their most important information. When it comes to generative AI, we know enterprises need technologies that provide fast time-to-value and meet their security and governance requirements. That’s why we’ve introduced Acrobat AI Assistant for our enterprise customers, a generative AI-powered conversational engine that can be quickly and safely deployed and used. AI Assistant can be deployed in minutes — and used in a familiar environment for employees. And because the features only work on documents users provide, they align to companies’ existing governance processes. We supplement LLM technologies with our own IP, greatly enhancing the quality and reliability of the output and prohibit third-party LLMs from storing, using or training on our customers’ data. And like other Adobe AI features, AI Assistant is developed and deployed according to our AI Ethics principles.

We rolled out AI Assistant to our own employees and they became early adopters of the technology. This fast time to value has been exciting to see, as our employees are discovering faster ways to do their best work. As a result, a range of use cases has started to emerge. The following are a few real-world examples of how our teams are using AI to turn document data into actionable insights and free up time for more valuable tasks.

  1. Marketing and communications: Creating compelling content at scale

Today’s marketing professionals are voracious consumers and producers of content. They read research reports, white papers, and media coverage to stay up-to-date and then produce an ever-increasing amount of content to keep both internal and external audiences informed and engaged. Research suggests that 2-4 blog posts a week is ideal to keep interest in the brand high – and social channels require even more fresh content. 

Employees from our marketing team are saving 5+ hours each week using Acrobat AI Assistant to get insights quicker and consolidate and format information into different types of assets – from executive updates to blogs to social posts – using clickable citations to verify the information is correct. 

2. Sales: Closing bigger deals – faster – and nurturing customer relationships

For sales teams to be successful, they need to deeply understand customer pain points, opportunities, and industry trends so they can create personalized pitches for new customers and customized solutions to help existing customers evolve their business. 

To do that, our sales teams spend a lot of time sifting through complex and lengthy documents like annual reports and 10-Ks for key insights like a customer’s mission, recent financial performance, risks, roadmap, and longer-term objectives. The team started using AI Assistant to summarize the most important points from the documents and ask specific questions to inform their pitches. They also used generative AI to quickly locate and verify details on topics like security practices and information governance in highly technical documents for customer RFPs, and to generate content like email summaries for their teams or summaries for slide decks. With AI, our sales team can now do the same work in about 4 hours or half the time it normally took them – opening opportunities to work with more prospects and customers. 

3. Finance: Analyze reports and provide timely recommendations 

Adobe’s finance team spends hours each week on tasks like reading financial statements, earnings, and industry reports, summarizing recommendations for internal clients, creating reports and blogs based on their analysis and creating emails to update their colleagues. By leveraging AI Assistant to do things like summarize earnings highlights, create first versions of blog posts and draft emails, each employee can save about 7 hours each week and get timely information to stakeholders much quicker.

4. Legal: Promptly access impact of new regulations and save time toward compliance

Our legal teams and compliance officers are charged with tracking and understanding a growing number of new regulations affecting the business. They also need to communicate key points to executives, which requires distilling complex information and removing legal jargon. AI Assistant is helping Adobe’s legal team streamline these processes by instantly generating synopses of regulations, distilling key takeaways, and then automatically formatting them into emails, reports, or slides – cutting time they normally spent in half.

5. Research & development: Stay on top of industry trends

At Adobe, our investment in R&D drives our innovation and growth. R&D’s job is to keep themselves and product teams current on the lates industry and technology trends. This requires a tremendous amount of reading and summarizing information to share with the department and cross-functional teams, and for inclusion in product requirement documents. Without AI Assistant, each researcher could spend more than 10 hours each week reading and summarizing information. Leveraging generative AI, they’ve been able to reduce that down to just four hours a week. 

Generative AI is an incredibly exciting new technology and it’s exciting to see it transform from a curiosity into providing real value for knowledge workers across just about every role. To learn more about Acrobat AI Assistant, visit here. 



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