As AI evolves rapidly, executives want to seize AI's potential to make processes more efficient, operations less costly and data more intelligent. But modernizing with AI requires putting it into practice, and implementation becomes complex when scaled across an organization. With the rapid advancement of AI, CIOs are exploring new ways to deliver immediate value to stakeholders by providing solutions that automate manual, time-consuming, non-value-added tasks that rapidly save costs and/or help them find new insights to launch new revenue channels and increase profitability.With 84% of global commerce touching an SAP application, the systems that run finance, supply chains, HR and customer experience already hold the data and context needed to power meaningful AI use cases. The challenge is unlocking that value — connecting AI to business processes in a way that is scalable, governed and aligned with how companies actually operate.For example, at one AWS partner company with 10,000 employees, which utilizes ERP to manage their day-to-day operation, almost 20-25% of these employees leverage their ERP system to support their work processes. And many of these employees (ERP users) probably handle ERP exceptions such as invoice mismatches. While traditionally, an ERP user would manage ERP exceptions manually, creating a solution based on AI agents can automate many of those exceptions, potentially saving millions of dollars with just a 10% increase in efficiency.As CIO and business users need help identifying, building and deploying AI solutions that can quickly provide tangible results, SAP and AWS have created a new program that offers a strategic shortcut which is already helping enterprises to rapidly develop and deploy AI solutions.The joint SAP and AWS AI Co-innovation Program provides an adoption strategy with structured support for organizations to transform their business processes. Launched at SAP Sapphire 2025, this program allows enterprises to harness the strengths of SAP and AWS from concept through enterprise-wide deployment via their partners. Designing and deploying AI can quickly and often drain critical resources. In their urgency to innovate and deliver results, executives may end up duplicating efforts, underestimating resource requirements, unnecessarily reinventing use cases from scratch or improperly allocating teams. As per the AWS partner organization, “Customers working with SAP and AWS experienced moving AI projects into production 25% faster.” For stakeholders, many of these inefficiencies can be avoided by accurately assessing current capabilities and setting clear expectations. No matter where they are on the journey, the SAP and AWS AI Co-Innovation Program is designed to serve organizations across maturity levels.Gain Advanced InsightsThe AI Co-Innovation Program helps business leaders get a clearer picture of critical issues, like rising operational costs or increased inefficiencies associated with old processes or manual tasks, and lost opportunities associated with the lack of visibility into end-to-end business processes.That was the case for a CPG customer working with the IT consulting services provider, advisor and transformation partner Capgemini. They discovered that due to poor visibility of supplier performance and delivery timelines, inefficient scheduling and the need for frequent manual intervention, the customer was facing escalating procurement expenses and supply chain delays culminating in a loss of sales.Capgemini worked with AWS and SAP to co-develop Intelligent Supply Service Monitor with GenAI, which combines real-time data with natural language processing to monitor supplier performance, identify disruptions earlier and streamline issue resolution — which is expected to lower their customer’s operational costs, minimize store drops and increase client satisfaction. “The AWS and SAP AI Co-Innovation Program was developed as a response to our joint customers who are trying to modernize their complex ERP processes by leveraging cloud native capabilities, including AI and advanced analytics,” says Sara Alligood, Global Head of SAP at AWS. “We worked backwards from these customer needs to build a program that would accelerate innovation through AI.” To take full advantage of AI tools that require vast computational power, organizations need a dynamic and robust cloud platform. Running SAP workloads on the AWS cloud enables customers to integrate their critical data with the latest AI solutions from Amazon Bedrock (including Nova foundation models). Through SAP Business Technology Platform (SAP BTP), organizations can build and extend SAP applications in a clean-core compliant way — ensuring governance, security and seamless integration with SAP S/4HANA Cloud and other SAP applications.With the power of a robust cloud platform, the SAP and AWS AI Co-Innovation Program helps enterprises build solutions with diverse data sources including both SAP and non-SAP workloads. Case in point: This approach proved critical to a global professional IT services company’s success when they partnered with AWS and SAP to build a solution for utility providers facing increased operational threats from rising floodwater, which risks critical infrastructure and service reliability.Through the Co-Innovation program, they built a GenAI-powered flood prediction system that combines real-time weather data with operational SAP data, so utilities can receive early warnings, take preventative action and maintain service continuity. Through scalable integration of internal and external data, they enabled smarter decision-making and reduced overall risk. Receive Structured Support The SAP and AWS AI Co-Innovation Program delivers critical support that enables customers to implement scalable solutions. Experienced partners, AI and industry experts, solutions architects and dedicated support teams from AWS, SAP and partners, provide this comprehensive assistance.“Our AI Co-Innovation Program with AWS enables customers to apply AI to core business processes while addressing the unique way they run their business. A joint SAP and AWS partner ecosystem brings these innovations to life with deep industry expertise, ensuring impactful business outcomes,” says Marc-Oliver Klein, VP Partner Product Management, SAP Business AI.To further ease adoption, SAP and AWS can also fund approved proof-of-concept development to offset service and cloud costs, removing the budgetary hurdles that often delay progress. “The scope of the AI Co-Innovation Program does not fully outsource AI and ideally augments an existing AI center of excellence for our customer,” says Alligood.As AI adoption accelerates, enterprise leaders are increasingly concerned about cyber and data security. This is especially true in highly regulated sectors like healthcare and finance, where data breaches can bring not only reputational damage but also serious legal consequences.The Co-Innovation Program ensures businesses can move quickly with AI while maintaining the trust and protection their industries demand in constantly evolving regulatory environments — which can also create difficulties in strategic planning and decision-making. It pairs Amazon Bedrock’s comprehensive enterprise-grade security and AWS’s global partner network with SAP’s rigorous frameworks so that customers can innovate with confidence, remain adaptive to changing regulations and protect compliance and data integrity. Deloitte partnered with a leading life sciences organization to build a finance solution that combines SAP financial data and business context with AWS Bedrock to gain real-time visibility into profit drivers and market trends, and navigate regulatory complexity with informed, adaptive planning and improved forecasting accuracy. This helped Deloitte’s client with their product mix and competitive pricing.Unleash AI Throughout Your EnterpriseEnterprises that tap into the SAP and AWS Co-Innovation AI Program will have the combined power of AWS and SAP expertise, tailored to support any stage of the customer’s AI journey. Organizations are already leveraging the program to define and overcome real-time challenges, minimize costly redundancies, reduce unknown risks and streamline operations. The result? Faster, simpler and more efficient AI deployments that stop backlogging teams or draining resources — and start transforming processes to drive new value.