IBM’s $11 Billion Confluent Bet: The Real-Time Data Play That Reshapes Enterprise AI

The deal is structured to close by the middle of 2026, subject to customary closing conditions and regulatory approvals from government authorities.[1][22] Notably, Confluent has agreed to pay IBM a $453.6 million reverse termination fee in scenarios where the transaction terminates under certain conditions specified in the merger agreement, a sizable breakup fee that reflects the deal’s strategic importance to both parties and discourages Confluent from shopping the company to alternative bidders once definitive agreements are signed.[30] IBM articulated financial expectations around the transaction that align with historical playbook for its open-source infrastructure acquisitions: the company anticipates the acquisition will be accretive to adjusted EBITDA within the first full year following close and accretive to free cash flow in year two, projections that assume meaningful revenue synergies and operating cost efficiencies as Confluent integrates into IBM’s cloud software segment.[22][35] The transaction closes a period of intense M&A activity in the data infrastructure sector, following Salesforce’s $8 billion acquisition of Informatica in May 2025 and building upon IBM’s prior acquisitions of Red Hat for $34 billion in 2019 and HashiCorp for $6.4 billion in February 2025.[24][14]

Confluent: The Apache Kafka Commercialization Story and Market Position

To understand the strategic compelling nature of this acquisition, one must first appreciate Confluent’s market position as the commercial steward of Apache Kafka, the open-source distributed event streaming platform that has become the de facto standard for real-time data movement across enterprise technology architectures. Apache Kafka, originally developed at LinkedIn in 2011 to handle massive volumes of real-time data feeds, evolved from a specialized messaging queue into a comprehensive event streaming platform capable of processing over one million messages per second with latencies as low as 2 milliseconds—performance characteristics that remain essential for modern application architectures spanning financial transactions, e-commerce interactions, Internet of Things device signals, and increasingly, the continuous data flows required by autonomous AI agents.[5] Confluent, founded in 2014 by the original architects of Apache Kafka including Jay Kreps, has built a comprehensive commercial platform atop this open-source foundation, adding enterprise-grade features including managed cloud infrastructure, connectors for hundreds of data sources and destinations, stream processing capabilities via Apache Flink, data governance and schema management, security controls, and deployment flexibility spanning fully managed cloud services, self-managed on-premises deployments, and hybrid bring-your-own-cloud models.[5][28]

Confluent’s financial profile reflects the market maturity of the data streaming category and the company’s competitive positioning. The company reported annual recurring revenue exceeding $1 billion as of the second quarter of 2025, with subscription revenue reaching $286.3 million in the third quarter of 2025, representing 19 percent year-over-year growth.[38][42] More tellingly for enterprise technology investors focused on cloud adoption momentum, Confluent Cloud subscription revenue grew 24 percent year-over-year in the third quarter, demonstrating that the company’s managed cloud offering continues to gain share relative to self-managed platform deployments.[42] The company reported remaining performance obligations of $1.73 billion as of the end of Q3 2025, growing 43 percent year-over-year and representing a powerful leading indicator of future revenue growth, particularly as customers expand consumption across use cases and Confluent deepens penetration within its existing installed base.[38][42] Critically for valuation and strategic fit, Confluent’s customer base encompasses more than 6,500 organizations across major industries, with over 40 percent of the Fortune 500 operating Confluent data streaming in production environments, ranging from real-time fraud detection in financial services through personalized retail experiences to predictive maintenance in manufacturing and supply chain optimization across logistics networks.[28][35][50]

The company’s operational metrics reveal expanding profitability and efficient capital deployment despite historically operating at substantial losses during its growth phase. In the third quarter of 2025, Confluent reported a non-GAAP operating margin of 9.7 percent, with GAAP operating margin improving to negative 27.9 percent from negative 37.4 percent in the prior year quarter, representing a substantial 9.5 percentage point improvement in just one year.[42] Operating cash flow similarly showed meaningful progress, reaching $30.8 million in Q3 2025 compared to $15.6 million in the prior year quarter, with the company demonstrating the ability to generate positive free cash flow while maintaining investment in research and development and sales infrastructure to support continued growth.[42] Perhaps most critically for investors evaluating Confluent’s commercial health, the company reported net revenue retention exceeding 130 percent for three consecutive quarters entering the IBM transaction, indicating that expansion within existing customer accounts more than offsets customer churn, a powerful metric that demonstrates the embedded nature of Confluent’s platform within customer technology stacks.[16]

IBM’s Strategic Imperative: Building the AI Data Foundation Layer

IBM’s acquisition of Confluent must be understood within the broader strategic context of how IBM’s leadership has chosen to position the company within the evolving artificial intelligence infrastructure landscape. Rather than competing directly with NVIDIA for hardware dominance or attempting to build proprietary foundational AI models to compete with OpenAI, Google, and Anthropic, IBM Chairman and Chief Executive Officer Arvind Krishna has deliberately constructed a strategy around controlling critical middleware and data infrastructure layers that will prove essential as enterprises transition from experimental AI pilots to production-scale autonomous workflows. IBM Chief Executive Arvind Krishna articulated this vision directly: “IBM and Confluent together will enable enterprises to deploy generative and agentic AI better and faster by providing trusted communication and data flow between environments, applications and APIs. Data is spread across public and private clouds, datacenters and countless technology providers. With the acquisition of Confluent, IBM will provide the smart data platform for enterprise IT, purpose-built for AI.”[22][35]

This strategic positioning follows a carefully orchestrated acquisition sequence building an integrated open-source infrastructure stack. IBM’s 2019 acquisition of Red Hat for $34 billion established the company as the leading steward of enterprise hybrid cloud infrastructure through Linux, Kubernetes, and container technologies, fundamentally reshaping how enterprises operate across on-premises, private cloud, and public cloud environments.[10][13] The February 2025 completion of IBM’s acquisition of HashiCorp for $6.4 billion added infrastructure automation and security lifecycle management capabilities, enabling enterprises to provision and configure cloud infrastructure at scale through Terraform and Vault technologies.[14] The Confluent acquisition now adds the real-time data streaming and governance layer, completing a comprehensive stack spanning infrastructure orchestration, automation, governance, security, and data movement. These three acquisitions alone represent approximately $51.4 billion in total investment, with IBM investing in open-source technologies that have become de facto standards within enterprise technology architecture, each with large installed bases of existing users who will benefit from commercial support, enterprise features, and integration with complementary technologies within IBM’s expanding portfolio.[3][11]

The timing of this acquisition reflects IBM’s assessment that enterprises have reached an inflection point in AI adoption where data infrastructure has become a critical limiting factor in scaling autonomous workflows. A November 2025 IBM-commissioned study of 1,700 Chief Data Officers globally revealed a widening gap between enterprise AI ambitions and execution readiness: while 81 percent of Chief Data Officers reported prioritizing investments to accelerate AI capabilities, only 26 percent felt confident their organization could leverage unstructured data in ways that deliver business value, with barriers including data accessibility, completeness, integrity, accuracy, and consistency preventing organizations from fully leveraging enterprise data for AI workloads.[7] This data readiness gap represents precisely the problem that Confluent’s platform addresses by making data accessible in real-time across system boundaries, keeping it clean and governed as it flows through organizational data infrastructures.

The Agentic AI Inflection: Why Enterprise Data Streaming Becomes Infrastructure

The strategic timing of IBM’s Confluent acquisition reflects a fundamental inflection in how enterprise technology stacks must evolve to support agentic AI deployments, where autonomous software agents continuously read data, make decisions, execute actions, and update system state in real-time response to changing business conditions. Traditional enterprise technology architectures built around batch processing, periodic reporting, and human-driven decision-making operated on data that was static or moved infrequently between systems. Agentic AI fundamentally alters this paradigm by requiring continuous, real-time data flowing between operational systems, analytics platforms, AI inference engines, and decision automation systems—a requirement that transforms data streaming from an optional capability for specialized use cases into foundational infrastructure.[17][20] As IBM articulated in recent positioning: “Without real-time, trustworthy, and easily accessible data, AI is stuck in the lab.”[20]

The magnitude of this market opportunity becomes apparent when examining the expected growth trajectory of agentic AI adoption across enterprises. Cowen estimates that enterprise spending on agentic AI will expand from less than $1 billion in 2024 to approximately $51.5 billion by 2028, representing a compound annual growth rate of roughly 150 percent as enterprises move beyond experimentation with narrow AI use cases toward deploying autonomous agents spanning customer service, operations, finance, supply chain management, and product development functions.[37] IDC projects that over one billion new logical applications will emerge by 2028, with these applications requiring continuous access to connected and trusted data operating in real-time across hybrid cloud environments—data that Confluent’s platform is architecturally designed to deliver.[35][47] A 2025 Confluent-commissioned data streaming report found that 68 percent of organizations cite inconsistent data sources and 63 percent cite data silos as top barriers to converting data into business impact, challenges that real-time data streaming directly addresses by creating unified data flows across organizational silos.[17]

The practical implications of this data infrastructure requirement for agentic AI became visible in Confluent’s product roadmap released in November 2025, when the company announced “Confluent Intelligence,” a capability combining data streaming, stream processing, and AI reasoning to enable developers to build agentic AI systems that act on real-time data. This product integrates Confluent’s core Kafka streaming engine with Apache Flink stream processing and native integrations with Anthropic’s Claude AI models, allowing developers to build and run event-driven AI agents directly atop Confluent’s platform infrastructure, with agents natively ingesting and processing real-time data for context-aware automation.[28] IBM’s acquisition ensures that this emerging product capability will be deeply integrated with IBM’s watsonx AI platform, IBM’s consulting organization, and IBM’s enterprise sales relationships with large Fortune 500 organizations operating across regulated industries including financial services, healthcare, telecommunications, and government.

Synergy Opportunities: The Path to Value Creation

IBM’s articulated rationale for the Confluent acquisition emphasizes three primary categories of value creation: strategic fit, synergy opportunities, and attractive financial profile. The strategic fit dimension reflects Confluent’s natural alignment with IBM’s hybrid cloud and AI strategy, addressing a critical gap in IBM’s existing portfolio. With IBM’s Red Hat providing the infrastructure layer and HashiCorp providing infrastructure automation and security lifecycle management, IBM lacked a comprehensive real-time data movement and governance platform. Confluent fills this gap precisely at the moment when enterprises require such capabilities to scale agentic AI across hybrid cloud environments.[22][35]

The synergy opportunities IBM identifies span multiple dimensions of potential value creation. First, product synergies will emerge through deep integration of Confluent’s data streaming capabilities with IBM’s watsonx AI platform, which provides enterprise-grade foundation models, fine-tuning capabilities, and governance controls for building and deploying AI applications at scale. By integrating Confluent into watsonx, IBM can enable customers to build AI agents that access continuously updated, real-time data directly from production systems, eliminating the latency and staleness problems that plague enterprise AI deployments attempting to operate on batch-extracted historical data. Second, automation synergies will emerge through integration of Confluent with IBM’s automation portfolio, enabling enterprises to automate previously manual workflows by combining real-time data visibility via Confluent with workflow automation via IBM’s existing automation products. Third, consulting synergies will allow IBM’s consulting organization—which operates at scale across enterprise transformations in major industries—to recommend Confluent as a foundational element of enterprise AI and data modernization initiatives, leveraging IBM’s existing relationships and go-to-market reach to accelerate Confluent adoption within IBM’s existing customer base.[22][35]

The financial synergies IBM anticipates extend to operational efficiency improvements through IBM’s scale and productivity initiatives. IBM management expects that Confluent’s gross margins will expand through operational leverage and shared services, with the company anticipating the acquisition will achieve adjusted EBITDA accretion in year one and free cash flow accretion in year two post-close.[22][35] These conservative financial projections contrast with the reality that Confluent already demonstrated strong unit economics and positive net revenue retention above 130 percent, suggesting that even modest integration with IBM’s existing customer base could generate outsized returns. The company’s operating margin trajectory—moving from negative 37.4 percent to negative 27.9 percent in just a single year—demonstrates Confluent’s ability to scale revenue faster than operating expenses, a profile consistent with businesses that achieve meaningful operating leverage once they reach sufficient scale.[42]

Perhaps most strategically valuable will be the cross-selling opportunities within IBM’s existing customer base. With IBM serving thousands of enterprise customers across financial services, healthcare, telecommunications, retail, and government sectors—many of them operating large, distributed hybrid cloud environments—there exists substantial opportunity to introduce Confluent as a foundational element of enterprise AI strategies within existing customer relationships. Confluent’s strong embedded position with 40 percent of the Fortune 500 suggests that relatively few incremental customers represent meaningful untapped opportunities, but rather the value creation opportunity lies in expanding consumption within existing accounts as customers recognize the dependency of AI and automation initiatives on unified real-time data infrastructure.

Competitive Landscape: Industry Consolidation in Data Infrastructure

IBM’s $11 billion investment in Confluent must be situated within a broader wave of consolidation and competitive repositioning occurring across data infrastructure as technology giants recognize that controlling real-time data foundations will prove essential to capturing value in the AI era. This transaction follows Salesforce’s May 2025 acquisition of Informatica for approximately $8 billion, which consolidated Salesforce’s data management capabilities within its broader AI and customer relationship management platform.[24][27] Salesforce Chief Executive Marc Benioff explicitly framed the Informatica acquisition as essential for enabling what Salesforce calls “agentic AI” across enterprise customers, with the combination of Informatica’s data integration, quality, and governance capabilities alongside Salesforce’s Einstein AI and Agentforce product delivering what Salesforce positions as a unified architecture for enterprise-grade autonomous agents operating safely and responsibly at scale.[24]

The competitive positioning here reveals a pattern: Salesforce recognized that building powerful AI agents requires not just sophisticated models or foundation technologies, but foundational data infrastructure that ensures AI agents operate on accurate, governed, contextually rich data drawn from multiple enterprise systems. Similarly, IBM’s Confluent acquisition reflects identical strategic logic: enterprise agentic AI success requires continuous streams of trusted, real-time data connecting disparate operational systems, analytics platforms, and AI inference engines. The practical implication is that enterprises utilizing Confluent for agentic AI data infrastructure will increasingly find value in combining Confluent with IBM’s hybrid cloud stack, consulting capabilities, and automation products, creating compounding dependencies that strengthen IBM’s competitive position within enterprise technology architectures.

Beyond Salesforce, the data infrastructure consolidation trend extends throughout the technology industry. Amazon Web Services, Google Cloud, and Microsoft Azure have each invested substantially in native data streaming and integration capabilities within their respective cloud platforms, recognizing that controlling data infrastructure strengthens overall cloud platform stickiness. Databricks announced structured streaming product capabilities in October 2025, positioning streaming analytics alongside its unified data analytics platform. The underlying competitive dynamic reflects market recognition that real-time data infrastructure has transitioned from specialized capability to foundational enterprise necessity, justifying substantial capital allocation by major technology companies competing for enterprise customer share.

Confluent’s competitive position within this landscape deserves careful consideration. The company maintains technology neutrality and cloud agnosticism to an extent unusual among enterprise software vendors acquired into large tech companies. Confluent operates across Amazon Web Services, Microsoft Azure, and Google Cloud Platform in equal technical standing, maintains integrations with competing data warehousing and analytics platforms including Snowflake and Databricks, and maintains relationships with direct competitors like Datadog and Sumo Logic without forcing customers into exclusive relationships.[28][29] IBM has publicly committed to maintaining Confluent’s technology neutrality and independent brand identity post-close, a commitment IBM has followed with prior acquisitions of Red Hat and HashiCorp by allowing those companies to maintain their distinct organizational identities and continue serving customers across multiple cloud providers.[33] This neutrality commitment proves essential for enterprise customers who maintain heterogeneous technology environments and require reassurance that their data streaming infrastructure will not become subject to strategic product decisions prioritizing IBM’s proprietary technologies over objective technical merit.

Comparable Transactions and Strategic Precedent

Understanding IBM’s Confluent acquisition requires context from IBM’s prior acquisition strategy in open-source infrastructure. IBM’s $34 billion acquisition of Red Hat in 2019 established the template for how enterprise software vendors can acquire and integrate foundational open-source infrastructure while maintaining the acquired company’s technical neutrality and independent brand identity.[10][13] Red Hat’s post-acquisition trajectory demonstrates the model: the company continues to maintain Linux distribution independence, continues to support customers across multiple cloud providers and on-premises environments, and continues to serve customers using competing infrastructure vendors. Red Hat’s role within IBM evolved into the centerpiece of IBM’s hybrid cloud strategy, with Red Hat contributing substantially to IBM’s cloud software segment revenue growth and establishing critical dependencies within enterprise technology stacks.[13]

IBM’s acquisition of HashiCorp in February 2025 for $6.4 billion extended this playbook into infrastructure automation and security lifecycle management, adding Terraform and Vault technologies that enable enterprises to define and manage infrastructure programmatically across multiple cloud providers and on-premises environments.[14] Like Red Hat, HashiCorp maintains a large community of open-source users who benefit from commercial support and enterprise features without exclusionary lock-in. The HashiCorp acquisition demonstrated IBM’s willingness to pay substantial multiples for relatively young companies with strong market positioning in critical infrastructure layers—HashiCorp was founded in 2011 and valued at $6.4 billion at acquisition, valuing the company at a substantial multiple of revenue for a company still in growth phase.[14]

IBM’s valuation of Confluent at $11 billion appears aggressive relative to Confluent’s approximately $1 billion in annual recurring revenue, implying an effective valuation of 11 times annual recurring revenue. This premium valuation reflects several factors: Confluent’s accelerating growth trajectory with remaining performance obligations growing 43 percent year-over-year, the strategic criticality of real-time data infrastructure to enterprise AI success, the high barriers to entry and switching costs once Confluent becomes embedded within customer technology stacks, and the substantial cross-selling opportunities within IBM’s existing customer base. For comparison, Salesforce’s acquisition of Informatica for $8 billion valued a company with approximately $600 million in annual revenue at roughly 13 times revenue, suggesting IBM’s 11 times revenue valuation for a faster-growing, higher-margin company represents a disciplined relative valuation.[24][27]

Market Dynamics and Total Addressable Market Expansion

The total addressable market opportunity that IBM is acquiring access to through Confluent has expanded substantially over the past four years, reflecting growing enterprise recognition that real-time data infrastructure has become essential to competitive digital operations. Confluent’s total addressable market has doubled from $50 billion in 2021 to $100 billion in 2025, a remarkable expansion that reflects multiple contributing factors: the acceleration of cloud adoption forcing enterprises to manage data across multiple cloud providers and on-premises environments, the emergence of AI as a core enterprise capability requiring continuous access to fresh data, the proliferation of Internet of Things and mobile applications generating continuous data streams that traditional batch processing architectures cannot efficiently handle, and the growing sophistication of enterprise automation use cases that depend on real-time data visibility.[35][47]

The streaming analytics market specifically is projected to grow from $35.05 billion in 2025 to $176.29 billion by 2032, representing a compound annual growth rate of 26.0 percent according to Fortune Business Insights analysis.[23] North America dominates the streaming analytics market with 17.56 percent market share, reflecting early adoption patterns in the technology industry that originated in North America. The retail and e-commerce segment is expected to achieve the highest growth rate during this forecast period as retailers increasingly recognize the competitive value of real-time data visibility into inventory levels, customer interactions, dynamic pricing optimization, and fraud detection across omnichannel commerce environments.[23]

This market expansion creates multiple opportunities for IBM to drive returns on its Confluent investment. First, Confluent can grow organically by capturing increasing market share as enterprises recognize the necessity of real-time data infrastructure for AI and automation. Second, IBM can accelerate Confluent adoption within its existing customer base through integrated sales motions connecting Confluent with IBM’s hybrid cloud, automation, and consulting offerings. Third, IBM can expand Confluent’s product capabilities by integrating with watsonx and other IBM platforms, making Confluent more valuable within enterprise environments while increasing switching costs for customers considering competitive alternatives.

Deal Structure, Governance, and Execution Risks

The structural protections built into IBM’s acquisition agreement with Confluent reflect sophisticated deal architecture designed to ensure transaction completion while protecting both companies against execution risks. Confluent shareholders representin

https://abcnews.go.com/Technology/wireStory/ibm-buys-data-streaming-platform-confluent-11-billion-128207498, https://www.confluent.io/blog/ibm-to-acquire-confluent/, https://www.youtube.com/watch?v=wlkf5KUq9K4, https://www.ibm.com/roadmaps/data/2025/, https://www.confluent.io/what-is-apache-kafka/, https://www.ibm.com/solutions/artificial-intelligence, https://newsroom.ibm.com/2025-11-13-ibm-study-chief-data-officers-redefine-strategies-as-ai-ambitions-outpace-readiness, https://www.geeksforgeeks.org/apache-kafka/apache-kafka-vs-confluent-kafka/, https://theaiinsider.tech/2025/12/08/ibm-to-acquire-confluent-for-11b-to-create-smart-data-platform-for-enterprise-generative-ai/, https://www.redhat.com/en/about/press-releases/ibm-closes-landmark-acquisition-red-hat-34-billion-defines-open-hybrid-cloud-future, https://newsroom.ibm.com/2024-04-24-IBM-to-Acquire-HashiCorp-Inc-Creating-a-Comprehensive-End-to-End-Hybrid-Cloud-Platform, https://www.ibm.com/products/watsonx, https://www.ibm.com/investor/news/ibm-completes-acquisition-of-red-hat, https://newsroom.ibm.com/2025-02-27-ibm-completes-acquisition-of-hashicorp,-creates-comprehensive,-end-to-end-hybrid-cloud-platform, https://developer.ibm.com/articles/awb-the-open-source-ecosystem-of-watsonx/, https://www.saastr.com/5-interesting-learnings-from-confluent-at-500000000-in-arr/, https://www.confluent.io/blog/data-streaming-ai-success/, https://www.confluent.io/confluent-cloud/, https://stocktwits.com/news-articles/markets/equity/why-ibm-may-want-confluent-3-charts-reveal-ai-play-s-promise/cLIYjkHREll, https://www.ibm.com/new/product-blog/ai-real-time-data, https://www.confluent.io/get-started/, https://newsroom.ibm.com/2025-12-08-ibm-to-acquire-confluent-to-create-smart-data-platform-for-enterprise-generative-ai, https://www.fortunebusinessinsights.com/streaming-analytics-market-108619, https://www.salesforce.com/news/press-releases/2025/05/27/salesforce-signs-definitive-agreement-to-acquire-informatica/, https://insidehpc.com/2025/12/ibm-in-11b-acquisition-of-confluent/, https://www.teleprompter.com/blog/live-streaming-statistics, https://fortune.com/2025/12/06/informatica-ceo-amit-walia-why-8-billion-merger-with-salesforce/, https://blocksandfiles.com/2025/12/08/ibm-confluent/, https://www.dbta.com/Editorial/News-Flashes/IBM-Moves-to-Acquire-Confluent-in-11-Billion-Deal-172703.aspx, https://www.ainvest.com/news/confluent-soars-ibm-slips-11b-ai-deal-traders-edge-2512/, https://estuary.dev/blog/best-data-streaming-platforms/, https://www.prnewswire.com/news-releases/ibm-to-acquire-confluent-to-create-smart-data-platform-for-enterprise-generative-ai-302635317.html, https://www.confluent.io/blog/ibm-to-acquire-confluent/, https://engage.confluent.io, https://newsroom.ibm.com/2025-12-08-ibm-to-acquire-confluent-to-create-smart-data-platform-for-enterprise-generative-ai, https://fortune.com/2025/12/03/ibm-ceo-no-way-hyperscalers-google-amazon-turn-profit-data-center-spending/, https://www.ropesgray.com/en/insights/alerts/2025/11/artificial-intelligence-q3-2025-global-report, https://www.investing.com/news/transcripts/confluent-at-45th-annual-william-blair-growth-stock-conference-ai-and-data-strategy-93CH-4083631, https://www.itjungle.com/2025/12/08/ibms-ceo-says-genai-is-great-for-enterprise-but-it-will-not-be-agi/, https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai, https://www.ibm.com/docs/en/watsonx/wdi/saas?topic=integrations-watsonxdata-integration-plans, https://www.chartmill.com/news/CFLT/Chartmill-36017-Confluent-Inc-NASDAQCFLT-Surpasses-Q3-2025-Earnings-Estimates-Stock-Jumps-98, https://cloud.google.com/transform/essential-ingredients-for-an-ai-ready-data-foundation, https://www.ainvest.com/news/confluent-soars-ibm-slips-11b-ai-deal-traders-edge-2512/, https://www.red94.net/news/43034-confluent-stock-soars-26-after-ibm-announces-11-billion-all-cash-acquisition-dea/, https://www.ibm.com/think/topics/agentic-ai-vs-generative-ai, https://newsroom.ibm.com/2025-12-08-ibm-to-acquire-confluent-to-create-smart-data-platform-for-enterprise-generative-ai, https://galileo.ai/blog/data-quality-in-ai-agents, https://www.confluent.io/blog/area/customers-and-business/, https://insidehpc.com/2025/12/ibm-in-11b-acquisition-of-confluent/, https://dev.to/farahkim/the-dark-side-of-building-ai-agents-on-poor-data-quality-l18, https://partner.microsoft.com/en-lb/case-studies/confluent, https://newsroom.ibm.com/2025-12-08-ibm-to-acquire-confluent-to-create-smart-data-platform-for-enterprise-generative-ai, https://siliconangle.com/2025/10/08/data-streaming-provider-confluent-reportedly-exploring-sale/, https://lucidworks.com/blog/enterprise-ai-adoption-in-2026-trends-gaps-and-strategic-insights, https://captaincompliance.com/education/ibms-planned-11-billion-confluent-deal-puts-data-privacy-in-the-spotlight/, https://www.confluent.io/blog/confluent-acquires-warpstream/, https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai

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