Oracle leads AI engineering market as agentic tools gain ground

The Business Research Company says the artificial intelligence engineering market is moderately fragmented, with Oracle leading global sales in 2024 and the top 10 players holding 25% of revenue. The report points to rising demand for agentic AI, cloud-native deployment, and governance tools as companies compete for enterprise adoption. Why it matters: - The AI engineering market is becoming a core battleground for cloud providers, enterprise software vendors, chipmakers, and machine learning platform companies. - Market leadership will likely hinge on who can deliver scalable deployment, reliable AI operations, governance, and interoperability for enterprise customers. - The report frames the market as a growing infrastructure layer for production AI, not just model development. What happened: - The Business Research Company published its Artificial Intelligence (AI) Engineering Market Report 2026, covering market size, trends, and a global forecast for 2026-2035. - Oracle Corporation led global sales in 2024 with a 5% market share. - The market was described as moderately fragmented, with the top 10 players accounting for 25% of total market revenue in 2024. - The report says enterprise demand is shifting toward AI lifecycle management, cloud-native engineering environments, automated machine learning, and generative AI integration. - The report identifies the full report and a free sample . The details: - Oracle’s AI engineering portfolio includes AI infrastructure, machine learning services, cloud AI platforms, and enterprise AI development solutions. - The report says those tools support model training, scalable deployment, workflow automation, and operational intelligence. - Nvidia Corporation, Microsoft Corporation, Alphabet Inc., Amazon Web Services Inc., International Business Machines Corporation, Tencent Holdings Limited, Dell Technologies Inc., Meta Platforms Inc., and Cisco Systems Inc. were listed among the leading companies. - The top 10 companies by reported share were Oracle at 5%, Nvidia at 3%, Microsoft at 3%, Alphabet at 3%, Amazon Web Services at 3%, IBM at 2%, Tencent at 2%, Dell at 2%, Meta Platforms at 2%, and Cisco at 1%. - Other major companies in the market include Samsung Electronics Co. Ltd., Capgemini SE, Siemens AG, Cognizant Technology Solutions Corporation, Palantir Technologies Inc., Huawei Technologies Co. Ltd., Baidu Inc., General Electric Company, Sony Group Corporation, SAP SE, Salesforce Inc., Qualcomm Incorporated, Intel Corporation, Zebra Technologies Corporation, Infosys Limited, Accenture LLP, Hewlett Packard Enterprise Company, Alibaba Group Holding Limited, Verint Systems Inc., and UiPath Inc. - Major raw material suppliers listed in the report include Nvidia, Intel, Advanced Micro Devices, Taiwan Semiconductor Manufacturing Company, Samsung Electronics, Micron Technology, SK Hynix, Qualcomm, Broadcom, Marvell Technology, Arm Holdings, GlobalFoundries, ASML Holding, Applied Materials, Lam Research, KLA, Western Digital, Synopsys, and Cadence Design Systems. - Major wholesalers and distributors include TD SYNNEX, Arrow Electronics, Ingram Micro, Exclusive Networks, Avnet, Redington, Carahsoft, Softcat, Presidio, SHI International, Insight Enterprises, Computacenter, CDW, Bytes Technology Group, ePlus, Crayon Group, Bechtle, and Zones. - Major end users include JPMorgan Chase, Walmart, Siemens, General Electric, Tesla, UnitedHealth Group, Goldman Sachs, FedEx, Uber, Airbus, Pfizer, Shell, Boeing, AT&T, Toyota, Procter & Gamble, Unilever, PepsiCo, and Target. Between the lines: - Agentic AI engineering is emerging as a key competitive theme because it improves workflow orchestration and enables more autonomous decision-making. - In April 2026, Oracle launched the Oracle AI Database Agent for Gemini Enterprise with Google Cloud. - The product includes natural language database interaction and secure AI-driven workflow integration. - The report says the platform uses semantic understanding architecture, agent-to-agent compatibility, and a governance-enabled AI framework to improve operational efficiency and support AI-powered business process automation. - The report’s strategy list points to four main moves: expanding AI engineering platforms, integrating generative AI and automation, adopting MLOps and cloud-native frameworks, and advancing responsible AI and governance frameworks. - The concentration data suggests the market remains open enough for competition, while still favoring firms with deep infrastructure, software, and enterprise distribution advantages. What’s next: - The report expects technology innovation, ecosystem partnerships, and infrastructure expansion to shape competitive positioning as enterprise AI adoption grows. - The new 2026 report package adds market attractiveness scoring, TAM analysis, company scoring matrices, Excel forecasting dashboards, hotspots infographics, key technologies, and updated tables. - The Business Research Company says it publishes continuous and custom research services, including competitor tracking and supplier and distributor packages. The bottom line: - AI engineering is moving from a niche tooling category to a strategic enterprise platform market, with cloud scale, governance, and automation now central to share gains.