Deloitte announced a strategic collaboration with Amazon Web Services (AWS) Professional Services on cloud migration and application modernization for enterprise and public sector customers.
The collaboration will harmonize Deloitte's global cloud practice and consulting expertise with the technical experience and competencies of AWS Professional Services. The goal is to enable customers to innovate and optimize future business outcomes by migrating and modernizing their workloads effectively and efficiently, utilizing world-class accelerators and best practices.
In addition, Deloitte will leverage its accounting and tax expertise to help customers self-fund these efforts, offsetting costs by aligning and optimizing related transformational savings.
"The nature of our C-suite relationships often enables us to design a holistic migration approach focused on driving the right business outcomes for our clients, including speed and efficiency of getting to the cloud, in a transformational context," said Patrick Jehu, Principal and AWS Professional Services GM, Deloitte Consulting LLP. "Our joint model with AWS uses automation to accelerate and optimize our clients' cloud migrations, and industry-leading solutions to modernize applications."
With Deloitte's consulting and advisory practices totaling over 20,000 global cloud practitioners, clients receive specialized expertise for their cloud strategy, organization transformation, migration, modernization and managed services, all supported by AWS and Deloitte in an end-to-end value delivery model. This boardroom-to-run approach simplifies complex modernization programs leveraging Deloitte's proven history of driving transformation programs at scale.
Todd Weatherby, VP of Professional Services, AWS, said: "Our innovation outcome-focused collaboration with Deloitte will help our customers maximize the value from their AWS cloud investments. The modernization vision jointly developed with Deloitte provides an end-to-end approach from strategy to managed services. The combination of Deloitte's extensive knowledge of our customers' core systems and AWS' technical thought leadership provides enhanced value to our customers."
The customer's journey in this approach begins with Deloitte's Cloud Transform Lab that helps build focus beyond migration, on modernizing business processes by leveraging AWS services like data analytics and artificial intelligence and machine learning (AI/ML). The lab helps build consensus across our customers' IT and business organizations and develops a plan to maximize the value and ROI that customers can realize by fully embracing the cloud. With the strategy in place, the joint delivery with AWS Professional Services ensures strong governance, adherence to AWS architectural best practices and access to migration and modernization patterns developed by AWS Professional Services. The delivery model also ensures that adequate domain expertise is available on the team leveraging Deloitte's deep industry and domain expertise to cater to complex, domain intensive workloads and regulatory requirements. The end-to-end approach also provides managed services options to our customers. Deloitte is a trusted member of the AWS Managed Services (AMS) program with experience and differentiated IP to migrate customers onto AMS.
In addition, Deloitte's Workforce Modernization capability recognizes that traditional ways of working need to change. Preparing employees for a virtual, team oriented, Cloud-based world requires new skills, retraining, agility and speed. Deloitte works with clients to transform their employees to these new skills to prepare for Cloud adoption, modernization and innovation.
Globally, many governments and large commercial clients still operate mission critical mainframe workloads. Deloitte's innoWake Product Suite and the Application Modernization Studio helps clients modernize their core systems to address evolving business models, optimize IT investments and adopt new technologies that support innovation and growth. This integrated offering comprises of five solutions (Discovery, Mining, Transformation, Modernization and Legacy DevOps) and employs patented products and automated processes to help clients achieve their modernization vision for mainframe applications in a low-risk, cost-effective manner.
Lastly, Deloitte and AWS bring an approach to help clients self-fund their cloud transformations. The self-funding approach analyzes multiple levers that drive savings, provides options for flexible managed service offerings and offers data-centered exit/leaseback options in collaboration with AWS. Such options can significantly offset the transformation costs by shifting CAPEX to OPEX and identifying savings that can fund the migration and modernization costs making cloud possible for everyone.
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...