AWS Unveils Vision for AI-Driven Enterprise Future at re:Invent 2024

Fast-moving and disruptive: Top AWS technologist outlines vision for AI's enterprise future - SiliconANGLE

Fast-moving and disruptive: Top AWS technologist outlines vision for AI's enterprise future The near-term future of enterprise AI will be model-driven, democratized, powered by agents, and under increasing pressure to control costs. These key trends were highlighted in today's keynote presentation by Swami Sivasubramanian (pictured), vice president of AI and data at Amazon Web Services Inc., who spoke at the company's annual re:Invent gathering in Las Vegas. His remarks followed a series of AWS announcements on Tuesday that defined the cloud giant's approach to enterprise AI and model usage. Sivasubramanian made it clear that his company remains closely attuned to the fast-moving dynamics that surround the evolving world of enterprise AI. "It's been a monumental year," Sivasubramanian said. "Disruption is the new normal." The announcements today showed how AWS is seeking to keep pace with developments in the explosive growth of AI model adoption. In September, Hugging Face Inc., the open-source hub for AI models, announced that it surpassed a million models in its repository, a near-doubling from what it reported in April. As enterprise AI adoption expands, AWS has focused on supplying tools for enterprise clients to manage data-fueled models used for making decisions and predictions. Wednesday's news included the addition of new models and providers within Amazon Bedrock, along with capabilities for Amazon SageMaker to build and deploy machine learning models for any use case within fully managed infrastructure. "We are currently facing an inflection point when it comes to model training," Sivasubramanian said. "We offer a diverse set of options that are capable of tackling any task imaginable." Amazon Bedrock is also receiving enhancements designed to help enterprises control costs associated with increased AI deployment. AWS announced new prompt caching tools for Bedrock that will reduce repeated processing which can run up a sizable bill. The company also unveiled Intelligent Prompt Routing that will automatically direct prompts to different foundation models and seek affordable alternatives. "Bedrock will automatically route your prompt to the model that will give you the best response at the lower cost," Sivasubramanian said. The enhancements to Bedrock also highlighted enterprise interest in deploying and managing AI agents. AWS customers such as Argo Labs are using Intelligent Prompt Routing for its voice agent solutions used by restaurants. When diners call to place orders or book tables, the chatbot can dynamically route the query to the most suitable model for a response. "Agents unlock new levels of automation that were not possible before," Sivasubramanian told the re:Invent gathering. The impact of AI agents is also becoming more visible in the world of home mortgage lending. In a presentation during the keynote session on Wednesday, Shawn Malhotra, chief technology officer of the fintech platform Rocket Companies Inc., described how his firm used AI agents to guide clients through the mortgage application process. He claimed that it has become three times more likely that Rocket will close a client via an AI-driven chat than through a human interface. Malhotra, who joined Rocket in May after leading AI initiatives for Thomson Reuters, painted a picture of AI agents as an important step for transforming the financial world. "The journey to own a home is still riddled with friction and stress," Malhotra said. "This is an industry begging to be disrupted." AI's role as a catalyst for disruption has been a continuing theme at re:Invent this week. In an exclusive interview with SiliconANGLE in advance of the conference, Sivasubramanian spotlighted generative AI's ability to democratize data for nontechnical users as one of the technology's more significant achievements. The AWS executive, who has been with the cloud giant for 19 years, led the company's development of the DynamoDB database for running high performance applications at scale, and has been instrumental in building AI and machine learning tools as product offerings for the firm. One of those became SageMaker, launched at re:Invent in 2017 as a unified platform for data, analytics and AI. On Wednesday, Sivasubramanian announced that Amazon Q Developer would now be available in SageMaker Canvas, enabling users to connect machine learning expertise with business needs. By making machine learning more accessible through a natural language interface, capabilities once limited to data scientists and AI experts will now become readily available to nontechnical users. AWS views Q Developer as a key step in democratizing data for business users. "With Q, you can ask for insights in natural language and get dashboards or data stories in minutes," Sivasubramanian told SiliconANGLE. "Tasks that used to take weeks now happen in seconds."

Inside the AI revolution: Swami Sivasubramanian on generative AI, agentic systems and AWS' vision - SiliconANGLE

Inside the AI revolution: Swami Sivasubramanian on generative AI, agentic systems and AWS' vision Amazon Web Services Inc. is betting big on artificial intelligence as it scrambles to gain mindshare from perceived leaders such as Microsoft Corp., OpenAI and Google LLC, and AWS Vice President of AI and Data Swami Sivasubramanian is the key executive driving those effort. In an exclusive video podcast conversation with Sivasubramanian, who was one of the pioneering engineers behind DynamoDB and RDS, we dove deep into the transformative power of generative AI, agentic systems and the critical role of data in shaping the future of enterprise applications. As we approach AWS re:Invent next week, this discussion offers unique insights into the innovations redefining productivity, data analytics and AI-driven business processes. Swami highlights how innovations such as the enterprise AI agent Q and gen AI app creation platform Bedrock are not only saving Amazon developers thousands of hours but also empowering business users to achieve "10X productivity" by simplifying data access and automating workflows. By democratizing data for nontechnical users and integrating diverse datasets, AWS is enabling enterprises to make faster, smarter decisions. Swami underscores that productivity is the true "killer app" of generative AI, setting the stage for a new era of efficiency and innovation across industries. Swami reflects on the journey that brought us to this moment in AI history: We are having this moment because a lot of things came together -- deep learning neural nets from 30 years ago, transformers unlocking unsupervised learning, and the cloud enabling seamless storage and computation. This convergence, he notes, created the foundation for large language models, which are now transforming industries by learning from massive datasets. But 2023, he says, was just the starting line: 2023 was about proof of concepts. In 2024, it's about real ROI -- deploying gen AI systems and agents that save money or increase revenue. A defining example of AWS' innovation in action is Q, an AI-powered agent that Swami uses personally: Q transformed how we upgraded Java packages. It analyzed dependencies, suggested changes, and automated 90% of code reviews. This saved 4,500 developer-years and $250 million in capex. These savings go beyond coding. Enterprises like Pfizer and Toyota have leveraged Q to streamline processes, saving billions. Swami emphasizes that the real power of gen AI lies in mapping business problems to the right data and leveraging cutting-edge LLMs: The efficiency of productivity is going to be 10X. Hundreds of thousands of customers are already realizing this with AWS. One of the most exciting shifts Swami highlights is the democratization of data for business users. Traditionally, technical expertise was a bottleneck in unlocking insights. Now, tools like Q and QuickSight are enabling business professionals to harness the power of data without needing a Ph.D. in SQL: With Q, you can ask for insights in natural language and get dashboards or data stories in minutes. Tasks that used to take weeks now happen in seconds. This shift, he explains, is redefining productivity: Cloud made developers 10X productive by eliminating undifferentiated heavy lifting. GenAI is now doing the same for business users. Swami predicts a seismic shift as enterprises move beyond unstructured data (text, images) to integrate multi-modal datasets: Imagine querying relational databases, streaming real-time data, and blending this with unstructured data. That's the future. He cites BrainBox AI's ARIA assistant, which uses building schematics and energy consumption data to optimize efficiency: ARIA identifies patterns like increased energy use on a specific floor and provides actionable recommendations. This used to take months -- it now happens in minutes. This ability to fuse diverse data types opens the door to unprecedented innovation across industries -- from transportation to marketing to supply chain optimization. As generative AI becomes a critical business tool, concerns around security and accuracy grow. Swami underscores the importance of resilience in AI applications: Contextual grounding is key. Guardrails ensure AI responses are accurate, secure, and actionable. At AWS, we're investing heavily in these areas. He envisions a future where AI systems seamlessly integrate with enterprise data, offering not just accuracy but confidence: The ability to map data to LLM responses and refine contextual grounding will be a game-changer. Echoing AWS Chief Executive Matt Garman's sentiment, Swami reaffirms that productivity is the killer app for gen AI: From automating mundane tasks to enabling strategic decision-making, gen AI is empowering enterprises to achieve more with less effort. The result? A shift in the labor equation: Developers focus on innovation, not debugging. Business users gain instant insights without needing technical expertise. And enterprises achieve a step-function increase in efficiency. The cloud has changed the equation and made developers like 10X productive so what is happening with the gen AI world, the business users are now actually 10X productive. Our conversation with Swami highlights the pivotal moment in technology and business history. As AWS continues to invest and drive more viable generative AI, the opportunities for transformation are limitless. From streamlining code upgrades to revolutionizing enterprise processes, the innovations discussed here signal a new era where data, AI, and cloud infrastructure converge to unlock unprecedented value. This is just the beginning. The ability to turn months into minutes will redefine how we work, innovate, and solve problems. As AWS continues to shape the future of generative AI, the challenge will be balancing innovation with resilience -- ensuring these systems remain reliable, secure and transformative for businesses worldwide.

AWS advances AI in enterprise strategy with practical solutions - SiliconANGLE

How AWS drives practical AI adoption through enterprise collaboration The transformative potential of artificial intelligence is redefining AI in enterprise strategy, shifting from experimentation to enterprise-wide applications. No longer confined to IT departments, AI is driving innovation and enabling senior executives to reimagine value creation and risk management, according to Brian Bohan (pictured), global lead and consulting partner center of excellence at Amazon Web Services Inc. "Now is the time for practical AI," he said. "It's about getting into enterprise scale. You've got to have the right infrastructure for the right cost, for the performance ... the right security, the right governance and the right ... organizational structure." Bohan spoke with theCUBE Research's John Furrier for theCUBE's "Cloud AWS re:Invent coverage," during an exclusive broadcast on theCUBE, SiliconANGLE Media's livestreaming studio. They discussed AI's role in business transformation, the criticality of governance and the growing influence of centers of excellence. Centers of excellence have become essential for organizations adopting AI in enterprise strategy at scale. These hubs bring together stakeholders to identify opportunities, prioritize impactful use cases and establish governance frameworks. Consulting partners such as Slalom LLC and Deloitte Touche Tohmatsu Ltd. are leading the way, helping clients such as United Airlines Inc. and TP ICAP Group PLC leverage AI to address specific business needs, according to Bohan. "It really starts with the art of the possible, bringing in a set of business leaders into conversations at the table where they hadn't been before," he said. "Now, they can really see how this technology applies to their businesses. It can change their businesses and change how they're interacting with their downstream customers. It opens up all kinds of possibilities, and so it really starts with a visioning exercise." Governance remains a cornerstone of scaling AI responsibly. Accenture Inc.'s responsible AI platform, powered by Amazon Web Services' Bedrock, translates compliance policies into actionable safeguards, enabling companies to adapt to regulatory changes while maintaining operational integrity, according to Bohan. "They built a responsible AI platform on Bedrock, and what allows you to do that is you can take those policies, instantiate them in the Accenture platform, and then before you go to production, it'll run a series of checks and tell you where you're in violation of those policies and give you remediation options," Bohan said. "But we know things change. Data changes, policies change [and] regulations change. It's an evergreen checking and monitoring that happens." Another significant development is the tailored application of AI to specific roles, such as chief financial officers and chief marketing officers, to enhance measurable business outcomes. For CFOs, AI-powered tools streamline financial decision-making by focusing on return on investment and value creation. At the same time, marketing leaders use generative AI to refine processes across their workflows, according to Bohan. "We've turned the CFO into a customer deriving benefit," Bohan said. "It's about applying gen AI into end-to-end workflows, bringing a new set of decision-makers to the table." Looking ahead, AWS continues collaborating with consulting partners to create industry-specific solutions, advancing AI in enterprise strategy while fostering innovation. Tools such as Infosys Ltd.'s Topaz and Wipro Ltd.'s Studio 360, built on AWS Bedrock, empower businesses to innovate and tackle unique challenges. "It's all about execution," Bohan said. "[It's about] getting in the market, working with our account teams and our customers about landing those solutions, landing those projects and delivering value." Here's the complete video interview, part of SiliconANGLE's and theCUBE's "Cloud AWS re:Invent coverage":

Transforming how business works: Dilip Kumar on Q for Business, gen AI and AWS' vision for productivity - SiliconANGLE

Transforming how business works: Dilip Kumar on Q for Business, gen AI and AWS' vision for productivity Generative artificial intelligence is ushering in a new era of productivity, transforming how businesses access, analyze and act on their data. At the forefront of this revolution is Dilip Kumar, head of Q for Business at Amazon Web Services Inc. In an exclusive conversation at AWS headquarters in Seattle, Dilip revealed how Q for Business empowers organizations to streamline workflows, harmonize data and unlock untapped potential through generative AI. "Businesses have treasure troves of data, but they're often siloed and hard to access," Dilip explained. "Q App Studio and for Q Business bridges that gap, enabling individuals and teams to work smarter, faster and more collaboratively." AWS Q for Business is a solution for modern challenges, where business users often face roadblocks in accessing data and creating actionable insights. Dilip highlighted how Q for Business is transforming workflows across organizations by: Generative AI is reshaping the dynamics between IT and business teams, fostering collaboration rather than friction. Historically, IT was tasked with provisioning technology for business users. Now, business users are leveraging tools like Q for Business to directly drive value. "The business people are the new IT, Business users are no longer just consuming technology -- they're using it to be productive and to serve their organizations better," Dilip explained. This shift is creating a more harmonious workplace, where technology eliminates mundane tasks and enables employees to focus on strategic goals. At the heart of Q for Business is Q Apps, a low-code solution that empowers users to create and automate tasks with ease. "Q Apps allow users to automate repetitive workflows and share them across teams," Dilip said. "It's a simple, intuitive process that transforms how businesses operate." Popular use cases for Q Apps include: One of the most significant challenges enterprises face is integrating data across multiple systems and formats. Q for Business addresses this by harmonizing structured, semi-structured, and unstructured data into a unified, actionable platform. "Q for Business doesn't just deliver search results -- it completes the discovery loop," Dilip said. "It provides context, memory, and actionable insights that drive workflows forward." This capability transforms enterprise search into enterprise action, enabling users to go beyond finding answers to solving problems. As businesses adopt generative AI, one value proposition stands out: productivity. From automating workflows to reducing friction between teams, Q for Business is delivering step-function improvements in efficiency. "When you remove undifferentiated heavy lifting, you give people the freedom to focus on meaningful work," Dilip said. "It's incredibly liberating and harmonizing." This is especially evident in how generative AI transforms interactions between developers and business users. Friction is replaced by collaboration, with AI enabling each group to focus on their strengths. Implementing Q for Business is designed to be simple and accessible: "You can start with basic search and quickly progress to building apps that automate and scale workflows across your organization," Dilip explained. Q for Business represents the first step toward more advanced agentic systems -- AI tools that can autonomously decompose complex queries, execute tasks, and deliver orchestrated solutions. "The key is orchestration," Dilip said. "It's about breaking down problems into manageable pieces and composing solutions that work seamlessly for the user." As AWS continues to innovate with Q for Business, the potential for generative AI to transform industries is clear. From harmonizing data to automating workflows, Q for Business is not just a tool -- it's a catalyst for change. "We're in a golden age of productivity," Dilip concluded. "The combination of generative AI, data harmonization and actionable insights is redefining what's possible in the workplace."

Revolutionizing software development: Deepak Singh on gen AI, AWS Q Developer and the future of coding - SiliconANGLE

Revolutionizing software development: Deepak Singh on gen AI, AWS Q Developer and the future of coding Generative AI isn't just a technological leap -- it's a transformative force reshaping the way software is developed and deployed. At the forefront of this revolution is Deepak Singh, vice president of the Next Generation Developer Experience at Amazon Web Services Inc. In an exclusive conversation at AWS headquarters ahead of its re:Invent conference next week in Las Vegas, Deepak shared his insights into how generative AI and tools such as AWS Q Developer are empowering developers, streamlining workflows and accelerating innovation across industries. "Using gen AI is going to change the way all of us build software," Deepak remarked. "It's about building faster, being more creative and spending less time on the tasks we don't like doing." The software development landscape is undergoing what Deepak describes as a "before and after moment" akin to the launch of AWS EC2 or serverless computing with Lambda. Gen AI-powered tools such as Q Developer are at the heart of this transformation, enabling developers to address longstanding pain points. Deepak highlighted two groundbreaking features of Q Developer: These tools don't just enhance efficiency -- they fundamentally change the development process by removing bottlenecks and empowering teams to focus on creativity and innovation. Deepak's role centers on reimagining how developers work, blending tools, environments and AI to meet developers where they are. This includes integrating Q Developer into commonly used platforms such as VS Code, IntelliJ and even Slack. Our goal is to eliminate friction. Whether you're coding in an IDE, debugging in Slack, or querying in a shell, Q Developer integrates seamlessly into your workflow. This flexibility extends beyond AWS environments. Recent partnerships with companies such as Wiz and Datadog enable customers to use Q Developer to analyze security issues and operational metrics directly within the AWS console. One of the most striking examples of Q Developer's potential is its role in legacy modernization. Deepak shared how Amazon used Q Developer to upgrade its Java codebase from JDK 8 to JDK 17, saving 4,500 developer-years and reducing costs by $260 million annually. Tasks like version upgrades or legacy modernization, which used to be tedious and time-intensive, can now be handled autonomously. This frees developers to focus on building innovative solutions. This shift reflects a broader trend toward systems thinking, where developers focus on architecture and high-level design while gen AI handles execution. According to Deepak, this mindset will define the next wave of innovation in software development. AWS' gen AI tools aren't just for seasoned developers -- they're democratizing software development for all builders. With tools such as Q Developer, even nondevelopers can create and manage applications. Deepak shared an example of data center technicians using gen AI to troubleshoot HVAC systems: They uploaded their documentation, and with a few prompts, built an app that identified and solved error codes. These technicians weren't developers, but gen AI enabled them to create a solution that might never have been built otherwise. This democratization extends to how Q Developer is accessed. A freemium model allows users to experiment with the tool using a free-tier Builder ID, while enterprises can scale up with advanced features through Pro licenses. The recent redesign of Q Developer includes enhanced reasoning capabilities and a new inline chat feature, which allows users to seamlessly switch between typing and complex prompts within their workflow. These updates reflect AWS' commitment to building goal-seeking agents that adapt to evolving customer needs. This is just the beginning," Deepak said. "As LLMs improve and tools like text editors become more integrated with AI, the possibilities are endless. Beyond coding, gen AI is driving a broader productivity boom across industries. Whether it's enabling faster software development, modernizing legacy systems, or unlocking creativity, the impact is profound. Deepak noted that customers like the BT Group and National Australia Bank are already seeing 37% to 50% acceptance rates for AI-generated code. Gen AI isn't just about doing more -- it's about doing it better," Deepak emphasized. "Whether you're a bank launching new products or a startup scaling quickly, these tools help deliver higher-quality results at unprecedented speed. As AWS prepares for re:Invent, the excitement around Q Developer and gen AI continues to grow. Deepak hinted at upcoming announcements that will expand the tool's capabilities and deepen its integration with third-party platforms. We're just scratching the surface of what's possible. As gen AI evolves, so will Q Developer -- helping builders, developers, and business users achieve their goals faster and more effectively. Deepak Singh's insights highlight how AWS is redefining the developer experience with gen AI, setting the stage for a future where software development is faster, smarter and more inclusive. With tools such as Q Developer, AWS is not only empowering developers but also enabling a new generation of builders to thrive in an AI-driven world. For those ready to embrace this revolution, the message is clear: The future of software development is here, and it's powered by generative AI.