Why AWS’ AI Chatbot Amazon Q Bests Google, Microsoft GenAI Tech: Ruba Borno

AWS’ global partner leader, Ruba Borno, talks with CRN about the general availability of Amazon Q Tuesday and why the AI-powered assistant is better than rivals Google and Microsoft’s generative AI technology.

AWS’ Ruba Borno is bullish that Amazon Q is now the world’s best generative AI-powered assistant as the new AI chatbot becomes generally available Tuesday.

AWS’ global partner leader said Amazon Q and AWS’ generative AI stack have major market differentiations compared with rivals Microsoft and Google.

“You have got to take a look at our entire generative AI strategy to really be able to articulate the differentiation [compared with Microsoft and Google],” Borno, vice president and leader of AWS’ Worldwide Channels and Alliances, told CRN. “So with Amazon Q, there are 40-plus integrations. That, for us, is really tied to our critical goal of making sure our customers have choice and flexibility.”

[Related: AWS Earnings Preview: Will AI Push AWS Across $100B Mark?]

The three largest cloud companies in the world—AWS, Microsoft and Google—have all been investing millions of dollars over the past 18 months in creating new AI-powered technologies, from next-level chatbots and large language models (LLMs) to cloud infrastructure designed to accelerate artificial intelligence workloads.

Today, the $97 billion cloud computing market-share leader announced the general availability of its new GenAI assistant, Amazon Q.

With Amazon Q, AWS customers can choose from among more than 40 built-in connectors for popular data sources and enterprise systems, including Amazon S3, Google Drive, Microsoft SharePoint, Salesforce, ServiceNow and Slack.

“Not only do we have integrations with all of these partners in the application layer and at the model layer with Bedrock, we also are doing that in a way that has the highest price-to-performance ratio in the industry today,” said Borno. “This is all tied to our goal of making sure that our customers are able to access the right outcomes for the lowest price in the market.”

Customers can use Amazon Q to have conversations, solve problems, generate content, gain insight and take action by connecting to their company’s information repositories, code, data and enterprise systems. The new AI chatbot helps users complete tasks using simple natural language prompts. On the security front, Amazon Q provides access controls that restrict responses to only using data or acting based on the employee’s level of access and provides citations and references to the original sources for fact-checking and traceability.

Borno spoke with CRN about Amazon Q and AWS’ AI security differentiation versus Microsoft and Google Cloud, as well as what AWS partners should be doing right now to drive Amazon Q and AI sales.

“Customers’ expectation of our partners to have generative AI skills, to have generative AI offerings, to have impact stories, has gone up significantly,” Borno said. “I would say partners have to move faster than they ever have before to meet the customers’ expectations.”

Google and Microsoft are also creating new AI-powered chatbots with generative AI capabilities. What is Amazon Q’s market differentiation compared with Microsoft and Google here?

You have got to take a look at our entire generative AI strategy to really be able to articulate the differentiation.

So within Amazon Q, there are 40-plus integrations. That, for us, is really tied to our critical goal of making sure our customers have choice and flexibility.

With Amazon Q, we have Amazon Bedrock, that middle layer which gives customers and partners the choice of different LLMs to use. So that is fit-for-purpose LLMs. All of that runs on our infrastructure, which is the best price-to-performance infrastructure out there.

That’s why Anthropic is using [AWS] Trainium [chips] to train their model to have the lowest cost for training. They’re also using [AWS] Inferentia [accelerators] for the inferences, which is where the majority of the workloads are going to be in the future for generative AI. So they’re using Inferentia to get the best price to performance.

So as you can see, you’ve got to look all the way down. So not only do we have integrations with all of these partners in the application layer and at the model layer with Bedrock, we also are doing that in a way that has the highest price-to-performance ratio in the industry today. This is all tied to our goal of making sure that our customers are able to access the right outcomes for the lowest price in the market.

What is another reason why Amazon Q is a market differentiator?

Our security. Specifically, we have Guardrails for Amazon Bedrock, which allows customers to implement safeguards to block harmful content using the best -in-class technology.

I think that is something that we don’t talk about enough as an industry. It is what’s going to hold back customers from adopting generative AI, if they don’t have a clear understanding of how security and responsible AI is implemented.

At AWS, that’s something that we’ve designed in from the beginning of our entire generative AI stack.

So responsible AI, making sure that we’ve got security built in, role-based access control so that individuals who shouldn’t have access to certain data are not getting insights through the application layer from that data.

Another key thing is that we’ve designed security in from the beginning. For a lot of our customers, they do have some concerns. So by deeply understanding our security and responsible AI strategy, it’ll help alleviate the concerns that they have there.

What is your advice to a partner who’s never sold something like Amazon Q before? What should they be doing right now?

Step No. 1: Get familiar with it.

We have a lot of free resources, training resources and educational information out there for our partners and for our customers. I’d encourage them to go to Skill Builder and look at the generative AI content that’s there so they can become familiar with it.

The second thing: Start playing with it.

Experimentation is the name of the game here. How to take those hundreds of use cases and whittle them down to the ones of highest impact requires experimentation.

The third thing: I would encourage them to invest the time in getting the AWS Generative AI Competency.

This is something that customers are asking for. Over 80 percent of customers look at a partner’s competencies before deciding who to work with.

Our Generative AI Competency was our largest competency launch in the history of the AWS Partner Network. We have 45 launch partners. Now with the pipeline, it’s predicted to be our fastest-growing competency ever because of the customer demand.

We’ve got partners such as Mission Cloud, MongoDB, Accenture, Deloitte and others who are demonstrating business impact. In order to get the competency, you have to have demonstrated business impact. So they went through those phases of learning, experimentation, actually deploying it and having customer impact in order to get the competency. That’s why customers are asking for this.

Overall, why should AWS customers and partners be excited about your new GenAI Amazon Q solution?

Amazon Q is at the top layer of the stack, the application layer of our generative AI stack, and it’s such a great example of how our generative AI strategy is leading with partners. Amazon Q is going to have more than 40 built-in connectors with our partners. It spans the types of partners in the AWS Partner Network.

For example, Datadog customers will be able to instrument Datadog with ease, maximize observability coverage, and receive guidance on incident troubleshooting and mitigate security risks for their cloud applications.

Speaking of security, Wiz customers will be able to use Wiz’s advanced security platform within Amazon Q’s developer experience. Then GitLab and AWS plan to integrate GitLab Duo and Amazon Q Developer to help customers develop software faster. We’ve got 40-plus connectors for commonly used business tools whether it’s Salesforce, ServiceNow, Slack and then of course AWS services, such as Amazon S3.

So Amazon Q helps developers write, debug, test, transform and implement code. The transformation part is really key.

We’ve had customers that have been using this for quite some time. One customer is Toyota Connected North America, and Amazon Q provided them with an ability to accelerate the effectiveness of their technical debt assessment by 25 percent. So they’re specifically using the code transformation capability to accelerate their application and services upgrades by up to 30 percent.

If we look at how our partners are using Q to support customers, one of our global system integrator partners, TCS, Tata Consulting Services, they worked with a large life sciences customer to use Amazon Q to reimagine the cloud operations of that customer. So we’re expecting to see a lot more use cases and customer impact emerge.

What I’m really excited about with Amazon Q is the customer impact—you can measure it nearly instantly after it’s deployed.

I’m really excited about the potential for [Amazon] Q as we on-board more and more partners to the Amazon Q partnership portfolio. We’ll be adding more and more value to customers and partners.

What’s your message to channel partners for the second half of 2024?

The pace of change and the pace of customer expectations is faster than it ever has been before. I hear this from our partners, frankly, more than us saying it to them. I just came from our London Summit that had 22,000 attendees and our Partner Summit had 1,000 partners.

The No. 1 message and theme is that our customers are expecting changes, responsiveness and impact in days or weeks, not in months.

So that means that customers’ expectation of our partners to have generative AI skills, to have generative AI offerings, to have those impact stories, has gone up significantly. And they can’t wait months in order to start developing those because by then it’ll be too late.

Our customers are trying to implement changes now. Customers are brainstorming hundreds of use cases, and they need partners to support them on this transformation.

So making sure that our partners are developing the capabilities, developing the competencies, and thinking through customer impact. I would say partners have to move faster than they ever have before to meet the customers’ expectations.