AI For Jobs

AI has the potential to create jobs, spur economic prosperity, and enhance productivity. Studies show that AI will complement 63 percent of U.S. jobs, freeing workers up to focus on doing their work more effectively and efficiently. Thirty percent of jobs will be unaffected by AI. This technology is a tool for workers to use, and it will help pave the way for a stronger, better American workforce.

Helping Data Scientists Attain Insights Faster

AstraZeneca and Amazon

Much of the health and life sciences industry faces an ever-increasing amount of commercial data that it struggles to efficiently analyze. AstraZeneca, the science-led biopharmaceutical company, is no different. In managing a vast and ever-increasing amount of data, the company realized it was missing an opportunity to gain valuable business insights about its treatments.

AstraZeneca worked with Amazon Web Services (AWS) to build a solution using Amazon Sagemaker, which helps data scientists and developers prepare, build, train, and deploy machine learning models quickly. Using AI and machine learning, AstraZeneca can now analyze commercial data at scale to gain insights and automate manual processes, saving time and effort for its data scientists. Before deploying ML models, it took AstraZeneca over a month of intensive effort to establish an environment for data scientists that would give them access to the necessary data. These AI-driven improvements in research and development are now helping AstraZeneca accelerate the commercialization of new therapeutics, ultimately speeding up the delivery of life-changing medicines to patients.

Boosting Worker Productivity


Zoom is using AI to drive collaboration and unlock people’s full potential. Zoom IQ is a generative AI assistant that businesses of all sizes are using across teams to further enhance productivity, balance workday priorities, and collaborate more effectively. Zoom IQ allows users to quickly draft email content, summarize Team Chat threads, organize ideas, draft whiteboard content, and more, which frees up more time for creative work and other collaborations.

Enhancing Financial Reporting and Accounting


Intuit is harnessing the power of AI-driven tools to enable accountants to process large amounts of data at unprecedented speeds, automate routine tasks, improve fraud detection, and provide more personalized financial advice to clients.

Intuit is using AI to improve data analysis around financial planning for clients, with over 730 million “AI-driven consumer interactions per year, leading to 58 billion machine learning predictions per day.” Using its own Generative AI Operating System (GenOS) platform, Intuit can implement large language models that specialize in tax, accounting, cash flow, and more. This helps reduce repetitive tasks for workers and helps streamline and reduce errors with data entry, transaction categorization, and invoice processing.


Empowering Employees

Delta Air Lines

Delta Air Lines is embracing AI to empower employees and improve customer experience and operational efficiency. Delta’s proprietary AI-driven platform analyzes millions of operational data points — from aircraft positions to flight crew restrictions to airport conditions — to create hypothetical outcomes that help Delta’s professionals make critical decisions before, during, and after large-scale disruptions, like severe winter weather or a volcanic eruption. It also allows workers to identify how better decisions could have been deployed in past situations, helping Delta to take its reliability to the next level during challenging travel events.


Humanizing Customer Service

T-Mobile and Amazon

T-Mobile uses the predictive capabilities of AI to provide advanced insights that its customer service agents can use to enrich customer experiences and create stronger human-to-human connections. T-Mobile developed AI models that extract meaning from vast amounts of textual data to predict what information would best serve a specific customer’s needs and then provide human agents with that contextual information in real time. This helps guarantee that each customer’s issues are quickly and accurately resolved.

T-Mobile’s data includes hundreds of thousands of incoming customer requests a day and knowledge repositories where potential answers to customer queries can be found. To train its predictive AI models, T-Mobile needed to add labels to this massive amount of data. T-Mobile turned to Amazon SageMaker Ground Truth to speed up and scale the labeling of training data, which is essential for AI and ML models to produce predictions with high accuracy. Instead of doing this manually, Ground Truth learns from these annotations in real-time and automatically applies labels to much of the remaining dataset. Using Ground Truth not only streamlined that process but freed T-Mobile’s data scientists to focus on more specialized tasks, such as model creation, analysis, validation, and deployment.


Helping Employees Flag Defective Products


As products go through Amazon fulfillment center operations, up to five different employees use a six-point visual check to assess whether products are damaged. This is a time-consuming task that is difficult for employees to keep top of mind because damaged items in Amazon’s inventory are rarely found.

To solve this problem and allow employees to focus on other important tasks, scientists at Amazon Fulfillment Technologies have developed advanced AI capabilities that can spot irregularities and flag defective products before they ship. To train the damage-detecting AI model, researchers taught it how to distinguish between damaged and undamaged products by scanning every item that passed through a major Amazon warehouse and supplying the images to the AI model so it could analyze the scans to discover hidden patterns and continuously improve the system’s ability to detect damage. This gives the AI model the capability to make the types of subjective decisions about damage that humans make all the time.

Once deployed, the AI damage detector will help reduce customer costs and delivery times and help free up operations employees to stay focused on other core tasks and activities.


Improving Customer Experience


DoorDash’s 2023 Restaurant Ordering Trends Report revealed that one in five customers prefer to order takeout via phone, but 50% of customer calls were left unanswered. In response, DoorDash introduced AI-powered voice ordering technology that allows restaurants to answer every customer call they receive, helping to meet demand, improve customer experiences, and increase restaurant sales. The new system couples AI with live agents to ensure customer calls are answered with little to no wait, enabling operators to capture the unmet customer demand. During peak times at restaurants, AI answers calls and provides customers with a personalized voice ordering experience in multiple languages while allowing employees to focus on in-store customers.