Capgemini and AWS Join Forces to Drive Enterprise Generative AI Adoption at Scale

Capgemini, a global leader in technology consulting and services, and Amazon Web Services (AWS), the world‘s most comprehensive and broadly adopted cloud platform, have announced a major expansion of their strategic partnership to accelerate enterprise adoption of generative AI. The multi-year collaboration agreement aims to help organizations across industries move beyond initial pilots and proofs-of-concept to deploy generative AI solutions at scale, enabling new innovations and driving significant business value.

The partnership comes as enterprises increasingly recognize the transformative potential of generative AI, with the global market for these technologies expected to grow from $10.8 billion in 2023 to over $100 billion by 2028, according to research from Markets and Markets. However, many organizations have struggled to move beyond experimentation due to challenges around data quality, model training and deployment, infrastructure costs, and trust and governance issues.

To help clients overcome these hurdles, the Capgemini-AWS partnership will combine Capgemini‘s extensive AI and data capabilities, deep industry expertise, and proven ability to deliver at scale with AWS‘s cutting-edge machine learning platforms and services, including Amazon Bedrock, Amazon SageMaker, and AWS AI & ML Embark. The collaboration will focus on three key areas:

1. Industry Solutions: The development of pre-built, industry-specific generative AI solutions that address common use cases and challenges in sectors such as automotive, aerospace, financial services, healthcare, and retail. These solutions will leverage Capgemini‘s domain knowledge and AWS‘s AI/ML technologies to accelerate time-to-value for clients.

2. CoE Expansion: A significant expansion of Capgemini‘s network of AWS Centers of Excellence (CoEs) to provide clients with access to the latest generative AI innovations, best practices, and expert support. The CoEs will focus on upskilling 30,000 Capgemini professionals on AWS technologies and certifications over the next three years to build a deep bench of AI talent.

3. Platform Innovation: The joint development of a new AI platform optimized for training and deploying large language models using Amazon Bedrock. The platform aims to reduce the total cost of ownership for generative AI applications while improving sustainability through optimized resource utilization and efficiency.

Accelerating Value Realization Across Industries

One of the key priorities for the partnership will be creating tailored generative AI solutions that address the unique needs and challenges of different industries. By packaging Capgemini‘s industry-specific data models, ontologies, and process templates with AWS‘s advanced AI/ML services, the collaboration aims to enable clients to rapidly prototype and scale high-impact use cases.

For example, in the automotive sector, the partnership will focus on developing generative AI applications for autonomous vehicle development, predictive maintenance, and personalized in-vehicle experiences. This could include using AI to generate synthetic training data for self-driving algorithms, automatically analyzing sensor data to predict component failures, and creating intelligent voice assistants that can engage in natural conversations and provide contextual recommendations to drivers and passengers.

In healthcare, the collaboration will target use cases such as drug discovery, clinical trial optimization, and personalized patient care. Generative AI models could be used to design novel molecular compounds, identify patient cohorts for clinical studies, and create individualized treatment plans based on a patient‘s genetic, clinical, and demographic data.

According to Cyril Garcia, CEO of Capgemini Invent and Member of the Group Executive Board, "Our clients are looking for ways to embed generative AI into their business operations to drive innovation, efficiency, and growth. By combining our deep industry expertise and AI capabilities with AWS‘s market-leading technologies, we can help organizations accelerate their adoption of these transformative solutions and realize value at scale."

Building the AI Workforce of the Future

To support the ambitious goals of the partnership and address the growing skills gap in the AI talent market, Capgemini has committed to training and certifying 30,000 of its professionals on AWS‘s latest machine learning and generative AI technologies over the next three years. This initiative is part of Capgemini‘s broader €2 billion investment in AI and data capabilities announced in 2022.

The upskilling program will cover a range of roles and skills, including data science, machine learning engineering, cloud architecture, and AI ethics and governance. It aims to create a global community of AI experts who can help clients navigate the complex technical and organizational challenges of adopting generative AI at scale.

The focus on skills development comes as demand for AI talent continues to outpace supply, with a recent report from the Global AI Talent Report estimating a worldwide shortage of 1.2 million AI professionals in 2023. By investing heavily in training and certification, Capgemini and AWS hope to build a sustainable pipeline of AI talent that can support the growth and maturity of enterprise generative AI adoption in the years to come.

"The success of generative AI in the enterprise will depend not just on the availability of powerful tools and platforms, but on the skills and expertise of the people who use them," said Anne-Laure Thieullent, Artificial Intelligence and Analytics Group Offer Leader at Capgemini. "Our investment in training 30,000 AI professionals on AWS technologies will enable us to provide clients with the end-to-end capabilities needed to ideate, design, implement, and scale transformative generative AI solutions."

An Extensible Platform for Generative AI Innovation

To accelerate the development and deployment of generative AI solutions, Capgemini and AWS will jointly create a new AI platform optimized for training and deploying large language models using Amazon Bedrock. The platform aims to provide clients with a flexible, cost-effective, and sustainable foundation for building and scaling generative AI applications across use cases and industries.

Key features and capabilities of the planned platform include:

• Workflow automation: End-to-end automation for data ingestion, cleaning, preprocessing, model training, testing, and deployment, enabling data scientists and ML engineers to focus on high-value tasks.
• Auto-scaling infrastructure: Dynamic provisioning and scaling of compute resources based on workload requirements, optimizing performance and cost.
• MLOps best practices: Built-in support for model versioning, monitoring, and governance to ensure the reliability, security, and compliance of generative AI applications.
• Pre-built integrations: Seamless integration with AWS AI/ML services and third-party tools and frameworks, enabling developers to leverage best-of-breed capabilities.
• Sustainability optimization: Intelligent workload placement and resource management to minimize the carbon footprint and environmental impact of AI model training and deployment.

By providing an extensible, enterprise-grade platform for generative AI, Capgemini and AWS aim to accelerate the pace of innovation and enable clients to build and scale solutions faster and more efficiently than ever before. The platform will be designed to support a wide range of use cases and industries, with flexible deployment options for on-premises, cloud, and hybrid environments.

Driving the Future of Enterprise AI

As generative AI continues to advance and mature, partnerships like the one between Capgemini and AWS will play an increasingly critical role in helping enterprises harness the full potential of these technologies. By combining deep industry expertise, cutting-edge AI/ML platforms, and a focus on skills and talent development, this collaboration represents a major milestone in the evolution of enterprise AI.

Looking ahead, we can expect to see a steady stream of innovation emerging from this partnership as Capgemini and AWS work together to co-create industry solutions, enablers, and accelerators that make it easier for organizations to adopt and scale generative AI. The development of a new AI platform optimized for large language models will provide a powerful foundation for these efforts, enabling clients to rapidly prototype and deploy high-impact applications.

At the same time, the investment in upskilling 30,000 Capgemini professionals on AWS technologies will help build a deep bench of AI talent that can support clients on their generative AI journeys. This focus on skills and expertise will be critical to ensuring that the adoption of these technologies occurs in a responsible, ethical, and sustainable way, with robust governance frameworks in place to manage risks and unintended consequences.

As the partnership evolves, it has the potential to significantly accelerate the pace of enterprise AI adoption and establish new benchmarks for the industry. By demonstrating the art of the possible and providing a clear roadmap for success, Capgemini and AWS can help organizations across sectors realize the transformative potential of generative AI and drive new innovations that reshape industries and markets.

It will be exciting to see how this collaboration unfolds in the coming years and the impact it has on the future of enterprise AI. One thing is clear: with the combined strengths of Capgemini and AWS, the possibilities for generative AI in the enterprise are vast and limited only by the boundaries of human imagination.