A key highlight of Amazon Web Services Inc. Chief Executive Adam Selipsky’s re:Invent keynote Tuesday was the announcement of Amazon Q.
Selipsky (pictured) set it up by looking at the uses of generative artificial intelligence and how almost everyone has experimented with it by now.
“What the early providers in the space have done is really exciting and is genuinely super useful for consumers,” he said. “But in many ways, these applications don’t really work at work. Their general knowledge and their capabilities are great, but they don’t know your company; they don’t know your data, your customers or your operations.”
These systems also don’t know your role in the organization, your preferences, how you use information and what you can access (and can’t). Selipsky noted that many chief information officers have banned the most popular gen AI text systems inside their organizations. In addition, chief information security officers don’t want to bolt on security after the fact. They’d rather build security into the tech from the ground up.
“So when we set out to build generative AI applications, we knew we had to address these gaps,” he said. “It has to be built in from the very start. Q lets you answer questions quickly, with natural language interactions, and you can easily chat, generate content and take action. And it’s all informed by an understanding of your systems, data repositories and operations.”
Selipsky added that Q provides “rock-solid security” by understanding existing identities, roles and permissions. “If your user does not have permission to access something without Q, they cannot access it with Q either,” he said.
There are four use cases for Amazon Q, which Selipsky outlined. Beware the word “expert” will feature prominently in the marketing of this service. According to him, Amazon Q is:
- Your AWS expert
- Your business expert
- Your business intelligence expert
- Your contact center expert
Amazon Q: AWS expert
“We’ve trained Amazon Q on 17 years’ worth of AWS knowledge so it can transform the way you think, optimize and operate applications workloads on AWS,” Selipsky said. “We put Amazon Q where you work.”
Q can assist with AWS Management Console documentation in IDE using Code Whisperer. It can also work in team chats such as Slack. You can chat with Q to explore AWS capabilities, learn unfamiliar technologies and architect solutions. Q can also help with options for building a web app in AWS. Ask it, “How do I build a web application with AWS? What are my options?” and Q will provide a complete overview.
“It’s going to answer with the list of potential services that you could use, such as Amplify, Lambda or EC2,” he added. “And then it will offer reasons why you might consider each service. From there, you can further narrow down your options through natural language, like ‘Which of these would be preferred if my app only needs to run for a few seconds and only has very infrequent traffic?’” Selipsky pointed out that Q answered that, in this case, Lambda would be the best option.
The capabilities appear deep, with Q’s ability to provide step-by-step instructions for getting started, links to documentation, and analysis of end-to-end network configurations.
AWS: business expert
“What about the other people in your organization or those in marketing, finance, HR, product management and more?” Selipsky asked. “There’s so much information spread across organizations documents, all of your data, all of your applications, and people in all these different roles.”
Selipsky noted that Q has connections to 40 of the top enterprise systems out of the box, which means that employees can ask complex questions and get detailed answers relevant to their role in an organization. And, he emphasized, this is all done securely.
Matt Wood, vice president of artificial intelligence at AWS, gave re:Invent a first look at how Q can work with a business: using data sources such as S3, Salesforce, Microsoft, Google and Slack.
“Once connected, Amazon Q starts indexing all of your data and content, learning everything there is to know about your business,” Wood said. “This includes understanding the core concepts, product names, organization structure — all the details that make your business unique.”
Q also uses gen AI to understand and capture the semantic information that makes your business unique. Wood noted that the data remains under the control of the enterprise at all times: AWS never stores it externally or uses it to train underlying models.
The new service can also take actions on your behalf using plugins. “As an example, if you update your tracking priorities, Q can automatically create tickets in JIRA, notify leaders in Slack, and update dashboards in ServiceNow,” Wood said. “Q allows you to inspect actions before they run so you can review them and find additional information, and after the action runs, Q will link to the results for verification.”
Q is opening up lots of possibilities for business leaders. Companies using popular consumer-grade tools will find that Q can run circles around them because it understands your business — up to the minute — and isn’t locked in a view of the world from a year ago.
AWS: BI expert
“We have worked for a while to make business intelligence more accessible to people without BI expertise,” Selipsky said. “We think anyone should be able to ask questions if their data using natural language.”
The machine learning-powered BI service QuickSight now has Amazon Q built in. Users can create dashboards and reports in minutes, rather than the hours it typically takes, by asking Q to visualize what they’d like to see.
“Q comes right back with a diagram, and you can add it to your dashboard with ease,” he said. “And you can tell Q to refine the visual further. So, you want to change the chart to a stacked bar chart by month and color-coded by region? Your wish is Q’s command.”
We all use data to tell stories, Selipsky said. It looks like Q will help with that — enabling the creation of reports and then bet recommendations — all with visualization options.
The presentation of these capabilities was interesting. Generative AI pointed at a company’s assets will be a boon to employees who’ve spent countless hours combing through PowerPoint, Excel, emails, SharePoint or Google Drive for the data nuggets they need.
AWS: contact center expert
“Today, contact center agents spend a lot of time gathering customer information to understand their questions, and then they spend even more time searching for the right answer,” Selipsky said.
He said Amazon Connect had already improved this process for agents with machine learning transcripts and analytics.
“But we knew we could make it even better for your agents and certainly for the customers waiting on the other end of the line for help,” he said. “Enter Amazon Q and Connect, available today. And this is going to give contact center agents a major assist.”
Agents can chat with Q inside Connect to respond more swiftly to questions. It’s on each call and can assist in real-time with responses, actions and links to relevant articles without typing. In addition, Connect will now give supervisors and administrators post-call summaries they can use to track follow-ups and development opportunities.
Takeaways
Overall, Amazon Q looks like one of the enterprise’s most promising developments for gen AI. For obvious reasons, its abilities with AWS itself — as the so-called “AWS expert” — garnered most of the commentary in Selipsky’s keynote. But if Q can also master business, BI and contact centers, it will be hard to beat.
The release of Amazon Q should also help dispel the myth that AWS is behind in generative AI. As I’ve stated often, I believe it’s fair to say AWS is behind in the marketing of generative AI, but Amazon Q creates a single, consistent assistant for almost all things Amazon.
