维端网2025 年，企业进入 AI 驱动转型的关键时刻。随着生成式 AI 的快速演进与落地，组织对于数据基础设施的要求也在发生根本性改变。数据不再只是存储与处理的对象，而是成为 AI 的燃料。这一背景下，IBM 宣布收购 Hakkoda Inc.——一家专注于数据现代化与 AI 顾问服务的公司，释放出明确的信号：企业数据现代化与 AI 就绪性，正跃升为数字战略的核心。
值得一提的是，此次收购是 IBM 持续加大对 AI 和自动化技术投资的又一举措。今年 2 月，IBM收购了用于构建 AI 应用程序的平台 DataStax，并最近完成了对基础设施和安全自动化公司 HashiCorp 的收购。
这一战略为 IBM 带来了丰硕成果。在 2024 年第四季度，该公司实现了五年来最大的营收增长，股价因此飙升 10%。IBM 当时表示，其 AI 订单和销售额累计超过 50 亿美元。
Hakkoda：专精云端数据平台与生成式 AI 资产的实力玩家
Hakkoda，这家颇具成长潜力的咨询公司，专注于 Snowflake 平台之上，以一种高度资产化、可复制的方式，为客户打造现代化的数据管道。
不仅如此，他们更懂行业：金融服务的敏感、医疗数据的复杂、公共部门的谨慎与决策链条的繁复——Hakkoda 一一理清，在每一个具体行业中找到了“如何让 AI 生根发芽”的路径。
Hakkoda 的核心竞争力聚焦于三大支柱：
深厚的 Snowflake 实施能力：Hakkoda 不仅是 Snowflake 的重要合作伙伴，也是该生态中最早实践基于 Snowflake 构建生成式 AI 数据资产的顾问公司之一。
以资产为中心的交付模型：其咨询服务并非传统的“人力时间制”，而是围绕可重复使用的数据与 AI 模块来提供快速、可扩展的业务成果。
全球分布的服务能力：遍布美国、拉丁美洲、印度和欧洲的团队，使 Hakkoda 能服务多区域、多产业客户，尤其在金融、医疗、公共服务等对数据敏感性极高的行业拥有优势。
IBM Consulting 的策略进阶：AI 就绪性成为主轴
此次并购不仅是 IBM Consulting 在服务能力上的扩展，更是其 AI 战略深化的落地步骤。
在业界看来，AI 成功的关键不在于模型，而在于可用、高质量的数据。Hakkoda 的能力补强了 IBM 在数据资产准备、迁移、治理与货币化等方面的端到端能力。
同时，IBM 长期以行业顾问能力著称，而 Hakkoda 的平台技术专精补上了 IBM 在云原生数据平台上的拼图，使其能以更短的时间、更低的成本交付 AI 驱动的解决方案。
而另一大亮点在于，Hakkoda 的“产品化咨询”模式为 IBM 咨询服务带来可复制、可量化的交付路径，推动从“定制咨询”到“平台+资产”的演进。
对 MSP 的启示与挑战：数据与 AI 融合成新标准
随着 Hakkoda 纳入 IBM 体系，市场对 MSP（托管服务提供商）的期望也在被重新定义：
1、仅基础设施支持”已不够
客户现在要求的不仅是云平台的运行支持，还包括数据的整合、治理、迁移和 AI 模型的交付能力。MSP 若无法在数据与 AI 之间建立价值链，极可能被边缘化。
2、向“解决方案即服务”进化是出路
Hakkoda 提供了一个模板：构建以成果为导向的服务产品，通过资产化的方法缩短交付周期，提高客户粘性。MSP 可以通过开发面向特定行业的 Snowflake 模块、AWS 集成工具或生成式 AI 插件来差异化。
3、产业认证成为竞争壁垒
Hakkoda 的快速崛起背后，是其对 Snowflake 和 AWS 的深度认证体系。对 MSP 来说，获得平台认证已成为新门槛；同时，参与云平台生态也意味着能进入更多企业数字化转型的核心场景。
4、合作优于单打独斗
在 AI 驱动的数据现代化时代，单一 MSP 无法满足复杂需求。与 IBM、Snowflake、AWS 等生态中的强力伙伴协作，共建行业解决方案，是抢占未来市场的关键策略。
结语
IBM 收购 Hakkoda 的意义超越并购本身，它昭示了一个新时代的到来——企业不再为 AI “试验”做准备，而是在为 AI 的规模化落地打造核心数据引擎。而这一引擎，必须建立在云原生、平台化、可扩展的数据架构之上。
对所有参与数字化转型的组织和服务商来说，现在是重新定义价值链的时刻：你是否拥有支持客户从数据到 AI 全链路的能力？你是否能将这些能力模块化、资产化、规模化交付？而这，将决定你在未来 AI 战场中的位置。
With the rapid evolution and implementation of generative AI, organizations are undergoing a fundamental shift in their data infrastructure requirements. Data is no longer merely a subject for storage and processing—it has become the fuel for AI. Against this backdrop, IBM’s acquisition of Hakkoda Inc.—a company specializing in data modernization and AI consulting—sends a clear signal: data modernization and AI readiness are becoming the new core of digital strategy.
It’s worth noting that this acquisition is yet another move in IBM’s continued investment in AI and automation technologies. In February 2025, IBM acquired DataStax, a platform for building AI applications, and recently completed the acquisition of infrastructure and security automation firm HashiCorp.
This strategy has paid off handsomely for IBM. In Q4 2024, the company posted its strongest revenue growth in five years, with its stock price surging 10%. IBM reported that its AI-related orders and sales exceeded $5 billion.
Hakkoda: A Strong Player in Cloud Data Platforms and Generative AI Assets
Hakkoda, a rapidly growing consultancy, focuses on building modern data pipelines on the Snowflake platform in a highly asset-driven and replicable way for its clients.
More importantly, they understand industries deeply: the sensitivity of financial services, the complexity of healthcare data, the cautiousness and long decision chains in the public sector—Hakkoda has addressed them all, finding specific pathways to help AI take root in each vertical.
Hakkoda’s core strengths lie in three pillars:
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Deep Expertise in Snowflake Implementation:
Hakkoda is not only a key Snowflake partner but also one of the earliest consultancies to build generative AI data assets on the platform. -
Asset-Centric Delivery Model:
Its consulting model moves away from traditional time-and-materials to delivering fast, scalable business outcomes through reusable data and AI modules. -
Globally Distributed Service Capabilities:
With teams across the U.S., Latin America, India, and Europe, Hakkoda serves multi-regional, multi-industry clients—particularly excelling in highly data-sensitive sectors like finance, healthcare, and public services.
IBM Consulting’s Strategic Evolution: AI Readiness Becomes the Axis
This acquisition is not just an expansion of IBM Consulting’s service capabilities—it’s a concrete step in deepening its AI strategy.
Industry consensus is clear: the success of AI hinges not on the models, but on the availability of high-quality, usable data. Hakkoda enhances IBM’s end-to-end capabilities in preparing, migrating, governing, and monetizing data assets.
IBM has long been known for its industry consulting strength. Hakkoda’s technical depth in cloud-native data platforms complements IBM’s portfolio, enabling faster, more cost-effective delivery of AI-powered solutions.
Another standout is Hakkoda’s “productized consulting” model, which brings replicable and measurable delivery pathways to IBM’s services—accelerating the shift from custom consulting to “platform + assets” delivery.
Implications for MSPs: Data and AI Are Becoming the New Standard
With Hakkoda joining IBM, market expectations for Managed Service Providers (MSPs) are being redefined:
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Infrastructure Support Alone Is No Longer Enough
Clients now demand more than cloud platform operations—they want data integration, governance, migration, and AI model delivery capabilities. MSPs that fail to build value chains between data and AI risk becoming marginalized. -
Evolving into “Solutions-as-a-Service” Is the Way Forward
Hakkoda offers a blueprint: outcome-oriented service products built through asset-based methods that shorten delivery cycles and enhance client stickiness. MSPs can differentiate by developing industry-specific Snowflake modules, AWS integration tools, or generative AI plugins. -
Industry Certifications Are Emerging as Competitive Moats
Hakkoda’s rise is backed by its deep certification in Snowflake and AWS. For MSPs, platform certifications are now a threshold, and participation in cloud ecosystems grants access to core digital transformation opportunities across enterprises. -
Partnerships Over Going Solo
In the era of AI-driven data modernization, no single MSP can meet all complex needs. Collaborating with ecosystem leaders like IBM, Snowflake, and AWS to co-create industry solutions is a key strategy for future market success.
Conclusion
IBM’s acquisition of Hakkoda signals more than a corporate deal—it marks the dawn of a new era where enterprises are no longer preparing to experiment with AI, but are building the core data engines required for AI to scale. These engines must be rooted in cloud-native, platform-based, and scalable data architectures.
For all organizations and service providers involved in digital transformation, this is a defining moment to rethink the value chain:
Do you have the full-stack capabilities to support your clients from data to AI? Can you modularize, productize, and scale those capabilities?
Your answer will determine your place in the future AI battleground.
