Four technology consultancies — NTT DATA, a Japanese IT-services group; Reply, an Italian digital-services consultancy; CGI, a Canadian IT-services firm; and Slalom, a U.S. business-technology consultancy — have disclosed Strategic Collaboration Agreements, or SCAs, with AWS since late January, showing how enterprise AI programs are moving from strategy into implementation.
NTT DATA announced a multi-year agreement, Reply and CGI disclosed separate agreements on April 2 and Slalom followed with a four-year global agreement on April 16.
The agreements are centered around not only modernization but security, too. NTT DATA is tied to large-scale cloud modernization, industry cloud and European sovereignty. Reply is positioned around AI, migration, security, data, digital sovereignty, managed services and IoT.
CGI targets the U.S. public sector. Slalom focuses its agreement on legacy modernization, AI adoption and AI-native differentiation. Taken together, the four deals show AWS pairing its enterprise AI push with firms that can implement it in different operating environments.
Scaling delivery and digital sovereignty
NTT DATA aims to bring AWS a scaled delivery partner with regulated-industry coverage. The agreement covers cloud modernization, agentic AI adoption and industry solutions across financial services, healthcare, life sciences, public sector, manufacturing, retail and energy.
Shashi Gupta, managing director and head of AWS capability for cloud and security at NTT DATA Inc., told TechInformed the collaboration means “faster modernization of mission-critical workloads, more industry-specific cloud solutions, and accelerated adoption of generative and agentic AI.”
It also makes NTT DATA a launch partner for AWS European Sovereign Cloud, with the firm promising sovereign-by-design cloud solutions and managed services for European governments and enterprises with data residency and operational autonomy requirements.
Gupta described AWS European Sovereign Cloud as “an important enabler” for customers with strict data residency and sovereignty requirements, particularly in regulated sectors.
That agreement also includes a dedicated AWS Business Group aligned with AWS sales and delivery, with close to 11,000 AWS-certified experts and a target to certify nearly 10,000 more over the next three years.
Gupta described the certification plan as “a direct investment in scalable, future-ready delivery capacity,” adding that engineers are being trained early on emerging AWS services, often before general availability.
The implementation bottleneck, Gupta said, remains concentrated in legacy modernization and data architecture. Fragmented and unstructured data environments make it difficult to operationalize AI at scale, he said, even as governance and skills remain important parts of the adoption problem.
Removing the legacy hurdle
Slalom’s agreement starts from a different constraint: legacy systems. Its four-year SCA groups the work into three initiatives: “Zero Legacy,” “AI Everywhere” and “AI-Native Differentiation.” Slalom said the legacy-modernization track uses AWS services including Amazon Bedrock, Amazon Q and AWS Transform, with a stated aim to reduce timelines on multi-year modernization programs by 50% to 70%.
Slalom cited La-Z-Boy as the practical example. The furniture maker worked with Slalom and AWS to map mainframe dependencies through AI-assisted analysis, de-risk modernization and create a path to decommissioning the mainframe. Slalom said La-Z-Boy plans to reduce annual run costs by more than $1 million after shutting off the mainframe.
Compliance and agentic automation in Europe
Reply’s agreement brings the European compliance and architecture layer into view. The Italian firm said the SCA focuses on enterprise-grade generative AI, agentic AI systems for autonomous workflows, domain-specialized models and governance frameworks aligned with evolving regulation such as the EU AI Act.
The same agreement covers Zero Trust, compliance automation linked to DORA, NIS2 and GDPR and digital sovereignty through AWS European Sovereign Cloud.
Reply also pointed to customer examples. It developed DevBot for Audi, described as a multi-agent system that automates cloud operations, implemented AI-driven solutions with BMW and built an agentic AI architecture for Aeroporti di Roma to provide real-time passenger assistance across digital channels. That Rome airport example gives the SCA a customer reference beyond internal IT modernization.
Addressing public sector and platform expansion
CGI’s agreement narrows the focus to U.S. public sector missions. The firm said its multi-year SCA with AWS will support trusted AI, secure cloud adoption and digital transformation across government, education, nonprofit and healthcare organizations.
The five declared workstreams cover AI for analytics, fraud prevention and operational decision support, Zero Trust cybersecurity, government data interoperability, citizen-facing digital services and legacy system modernization.
The consulting agreements come as AWS is also building the platform side of enterprise AI. In February, OpenAI and Amazon announced that AWS would become the exclusive third-party cloud distribution provider for OpenAI Frontier, a platform for building, deploying and managing teams of AI agents, while the companies co-develop a stateful runtime environment on Amazon Bedrock.
AWS is also making an industry-specific AI push in manufacturing. At Hannover Messe, Infor and AWS announced new and enhanced manufacturing and distribution AI agents built natively on AWS, with Xpress Boats reporting a 98% improvement in process issue diagnosis speed, a 95% reduction in returns processing time and a 50% reduction in expedited shipping costs after using Infor Process Mining, automation tools and Infor GenAI.
Bridging the gap from strategy to execution
Enterprise demand has moved beyond AI curiosity and toward operational delivery. KPMG’s Q1 2026 Global AI Pulse, based on 2,110 senior executives across 20 countries, found that 95% of organizations surveyed have an AI strategy, but only 8% report established return on investment.
KPMG also found that 39% are now scaling AI or driving organization-wide adoption and that organizations plan to invest an average of $186 million in AI over the next 12 months.
KPMG’s report states the constraint directly: “not access to technology, but the ability to operate AI at scale.” That line helps explain the commercial shape of the AWS agreements. AWS has the cloud platform, model partnerships and industry software alliances.
The four SCAs show how that platform work is being paired with systems integrators that can modernize legacy systems, manage sovereignty requirements, translate AI into sector workflows and staff the programs.
The practical markers to watch are more visible: NTT DATA’s certification target, Slalom’s modernization claims, Reply’s regulated-industry AI references and CGI’s public-sector workstreams.