Adobe has been a trailblazer in the digital document space for over a decade, offering a myriad of intelligent capabilities across creative, experience, and document applications. This has provided unparalleled value to billions of Adobe Acrobat subscribers worldwide, setting a new standard for document productivity and creativity. However, with the advent of generative AI, Adobe is not only expanding its horizons but also embracing new challenges and opportunities. This blog delves into Adobe’s approach to integrating generative AI into digital documents, highlighting the launch of Adobe Firefly, the introduction of AI Assistant in Reader and Acrobat, and the innovative Liquid Mode.
Adobe Firefly: A New Era of Generative AI
At the core of Adobe’s generative AI initiative is Adobe Firefly, a family of generative creative models that represents a significant commitment to thoughtful AI innovation and leadership. This commitment is not just about developing and deploying technologies but also about fostering practices and collaborations with industry and government partners to create a world where game-changing discoveries can thrive alongside responsibility .
AI Assistant in Reader and Acrobat: A Leap Forward
Adobe is taking a bold step into the future of generative AI in digital documents with the introduction of AI Assistant in Reader and Acrobat, now in beta. This AI-powered conversational engine is deeply integrated into PDF workflows, marking a new chapter in generative AI innovation. The goal is to equip customers, from individuals to the largest enterprises, with the confidence to use AI Assistant effectively, ensuring that the technology is used responsibly and ethically .
Leveraging Large Language Models (LLMs)
As a leader and visionary in artificial intelligence, Adobe builds foundation models in the categories where it has deep domain expertise and partners with best-in-class large language models (LLMs) for text-based experiences. Adobe takes an agnostic approach to LLM-integrations, curating the best technologies, partners, and models to deliver the right output for customers’ needs. For AI Assistant features in Reader and Acrobat, Adobe is currently leveraging the Microsoft Azure OpenAI Service. Adobe will continue to explore and test a variety of technologies to provide customers with quality, responsible experiences .
Building Trust in Generative AI
Generative AI is an incredibly exciting technology that’s already delivering tremendous value to customers. However, it’s also still in its early stages, and improving the technology is an ongoing journey. To help build trust with customers, Adobe is taking a multilayered approach:
– AI Ethics Testing and Reviews: All AI Assistant features in Reader and Acrobat, including third-party LLM integrations, go through Adobe’s responsible AI Ethics governance process and are developed and deployed in alignment with the company’s AI Ethics principles of accountability, responsibility, and transparency .
– Guardrails for LLMs: Adobe contractually obligates third-party LLMs to employ confidentiality and security protocols that match Adobe’s own standards. Adobe specifically prohibits third parties from manually reviewing or training their LLMs on Adobe customer data .
– Data Security Protocols: AI Assistant features in Reader and Acrobat are governed by data security protocols, including testing and evaluation methodologies in pre- and post-processing, and evaluation, testing, and evaluation built into engineering processes .
– Keeping Humans in the Loop: AI Assistant includes attributions in generated responses, making it simple for customers to confirm where the information came from. An in-app message reminds customers to double-check the source of the answers AI Assistant provides .
– Built for Business: AI Assistant includes enterprise-grade data security and information governance .
– Ongoing Customer Feedback: Adobe provides customers with multiple channels for feedback and encourages active conversations to help the company identify and address issues quickly .
Liquid Mode: A Building Block for Document Intelligence
Liquid Mode — Adobe’s breakthrough reading experience that delivers an easier way to read documents on mobile — is powered by proprietary AI models that offer a deep understanding of PDF structure and content. Liquid Mode turns static information into dynamic data, automatically reflowing PDF documents to make them more readable and accessible on any sized screen. On the 30th anniversary of Adobe Acrobat and PDF, Liquid Mode achieved a major milestone, with customers using the feature to read more than 1 billion files on mobile devices. The technology has revolutionized reading experiences for individuals of all abilities and was recognized as one of Time Magazine’s 2023’s Best Inventions .
Into the Future
Adobe’s journey into generative AI for digital documents is not just about introducing new technologies but also about redefining the future of document management. By integrating AI into digital documents, Adobe aims to redefine document productivity, making it more accessible, efficient, and insightful for everyone. This vision is part of Adobe’s broader strategy to lead the way in AI innovation, ensuring that the technology is developed and used responsibly .
Conclusion
As Adobe embarks on this new chapter of generative AI innovation, it is clear that the company is committed to leveraging AI to transform digital document experiences. The introduction of AI Assistant in Reader and Acrobat, along with Adobe Firefly, represents a significant step forward in making documents more intelligent, collaborative, and creative. By focusing on responsible AI development and ethical considerations, Adobe is setting the stage for a future where generative AI plays a pivotal role in document management and beyond.
The integration of AI in banking and financial services is not just a trend; it’s a necessity for banks to remain competitive and meet the evolving needs of their customers. The COVID-19 pandemic has accelerated the shift towards digital banking, with an estimated 20 to 50 percent increase in the use of online and mobile banking channels. This shift has led to rising customer expectations, particularly in terms of personalization and convenience. Consumers now expect digital experiences that anticipate their needs and offer tailored services at the right time, through the right channel .
The Need for AI-First Banks
The financial sector is witnessing a steady increase in the use of advanced AI technologies. Nearly 60 percent of financial-services sector respondents in McKinsey’s Global AI Survey report that their companies have embedded at least one AI capability. The most commonly used AI technologies include robotic process automation for structured operational tasks, virtual assistants or conversational interfaces for customer service divisions, and machine learning techniques to detect fraud and support underwriting and risk management. This indicates a move towards a comprehensive approach to deploying advanced AI across the full lifecycle of banking operations, from the front- to the back-office .
Obstacles to AI Deployment
Despite the growing adoption of AI, banks face several challenges in scaling AI technologies throughout their organizations. The most common obstacle is the lack of a clear strategy for AI. Other challenges include a weak core technology and data backbone, and an outmoded operating model and talent strategy. Legacy systems often lack the capacity and flexibility required to support the variable computing requirements, data-processing needs, and real-time analysis that closed-loop AI applications require. Additionally, many banks’ data reserves are fragmented across multiple silos, making it difficult to analyze relevant data and generate intelligent recommendations or offers at the right moment .
The Future of AI in Banking
To meet customers’ rising expectations and compete in the AI-powered digital era, the AI-first bank of the future will offer intelligent, personalized, and omnichannel experiences. This will involve the seamless integration of banking capabilities with relevant products and services beyond banking, providing a consistent experience across physical and online contexts across multiple devices. Internally, the AI-first institution will be optimized for operational efficiency through extreme automation of manual tasks and the replacement or augmentation of human decisions by advanced diagnostic engines in various areas of bank operations. This will be achieved through the broad application of traditional and leading-edge AI technologies, such as machine learning and facial recognition, to analyze large and complex reserves of customer data in near real-time .
Conclusion
The future of banking is AI-first, with banks needing to become AI-first to meet the evolving needs of their customers and stay competitive. This involves setting clear priorities, creating the necessary capabilities, and developing a sustainable strategy for integrating AI into banking operations. By overcoming the obstacles to AI deployment and embracing a comprehensive approach to AI, banks can transform their operations, enhance customer experiences, and secure a competitive edge in the digital era .