AWS partner competency asks for GenAI tech, business skills

The cloud provider's generative AI certification takes months to complete, involves numerous technical and operational demands, and requires four detailed customer case studies.

Service providers looking to obtain the AWS seal of approval for generative AI can expect months of work as they tick off dozens of requirements and prepare detailed customer case studies.

AWS last week identified 32 companies as the first batch of services partners to complete its generative AI competency. An AWS partner competency demonstrates a company's expertise in providing services or developing software for particular industries, use cases or workloads. The cloud provider offers more than 40 such specializations.

Companies that meet the latest competency criteria could gain a point of differentiation among AWS customers looking for help cultivating generative AI use cases or taking proof-of-concept (PoC) applications into production. Market research firm Canalys found that 87% of the 303 cloud customers it polled rank partner specializations as a top-three selection criteria. Canalys expects generative AI to become a $158.6 billion channel ecosystem opportunity by 2028.

AWS partner competency: Meeting the specs

Service providers that have earned the generative AI competency said the process involved meeting technical and business operations requirements as well as documenting customer success.

The actual competency took about two and a half months to complete.
Daniel GoldbergChief marketing officer, Loka

"The actual competency took about two and a half months to complete," said Daniel Goldberg, chief marketing officer at Loka, a consultancy based in Los Altos, Calif. He said the company set the groundwork for the competency years ago, establishing an AI and machine learning practice.

Goldberg described competencies as the most technically demanding certification AWS offers for partners, adding that the generative AI variety was no exception. The competency's 50-plus requirements included an extensive audit of Loka's generative AI operations, maintaining expertise in a generative AI center of excellence, security best practices and more, he said.

Fiona Greeley, head of client services operations at DoiT International -- a Santa Clara, Calif., company that provides multi-cloud services and FinOps technology -- said the competency process spanned a few months. She said the spectrum of requirements included common AWS partner practice standards and specific generative AI criteria.

The following are a few examples of the GenAI requirements:

  • A description of a partner's methodology for determining whether customers are ready for generative AI and identifying likely use cases.
  • An overview of how a partner selects and customizes a foundation model for generative AI applications. Considerations include the prompts to be used and the process for updating them, the process for preparing and housing data in a vector database, and customization approaches using tools such as Amazon SageMaker.
  • Details on how a partner identifies generative AI opportunities and trains salespeople on how to pursue those deals.
Graphic depicting a typical AWS Generative AI Competency holder's profile.
AWS' latest competency could help partners stand out from the GenAI crowd.

Compiling generative AI case studies

The competency process also calls on partners to provide four in-production generative AI customer case studies.

Olivia Martinez, manager of partner marketing and communications at Mission Cloud, a managed cloud services provider based in Los Angeles, said the case studies demonstrate the company's "expertise in using AWS generative AI technologies to complete customer projects."

Reghu Hariharan, co-founder at Quantiphi -- a digital engineering company in Marlborough, Mass., that focuses on AI -- said the four "PoC-to-production" case studies it submitted included details on project delivery, deployment, automation and data security. Each case study provided a technical architecture diagram explaining the rationale for each AWS service used in the deployment. An AWS solutions architect vetted the diagrams, he added.

The case studies also tasked partners to describe how their deployments scale to accommodate demand, using services such as Amazon CloudFront and AWS Auto Scaling. Requirements also included cost optimization -- in line with the current industry focus on keeping cloud expenses in check.

Generative AI competency for software partners

In addition to the service providers, 15 software partners have obtained the AWS Generative AI Competency.

The list included familiar names in AI such as Anthropic and Nvidia. It also included one service provider. Quantiphi met the competency's requirements for both software and service partners -- the only company thus far to do so.

Quantiphi provided an hourlong demo of its generative AI platform, Baioniq, to obtain the software certification, Hariharan said.

Gaining partner benefits

The next round of partners pursuing the AWS Generative AI Competency can expect several benefits. Hariharan cited AWS technical and business accreditation that a partner can provide to customers as proof points of its generative AI capabilities. Other advantages include access to AWS technicians to help with PoCs and training materials for accelerating PoC execution, he said.

Greeley said the competency helps partners showcase their generative AI expertise and grow their GenAI services business. That's because the competency certifies that a partner has proven success in guiding and implementing GenAI strategies for customers, she added.

With that certification in hand, DoiT will collaborate with customers to move them from experimentation to implementation, Greeley said. She cited its generative AI work at Sweeeft, an HR software company: DoiT migrated Sweeeft's large language model workloads to AWS. The generative AI strategy has helped the software provider's customers reduce hiring time by as much as 60% and accelerate training by four times, she said.

Partners believe the AWS competency will put them at the forefront of customers' generative AI deployments. The timing is particularly important as pilots begin to scale, one of the top trends service providers anticipate this year.

Goldberg said Loka has used AWS offerings such as Amazon Bedrock, Amazon SageMaker JumpStart and AWS Silicon to get more than 100 companies started on the generative AI path.

"Nearly half have or are moving into production," he said.

John Moore is a writer for TechTarget Editorial covering the CIO role, economic trends and the IT services industry.

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