IBM: Seven Key AI Announcements From April 2025

IBM is also expanding its watsonx.ai and watsonx.governance platforms to integrate with Nvidia NIM. This move enables organisations to access AI models across hybrid and multi-cloud environments while maintaining robust governance and monitoring of AI deployments. IBM says the integration offers enhanced flexibility for enterprises building interoperable and responsible AI systems.

In response to the increasing compute demands of generative AI and high-performance computing, IBM Cloud has introduced Nvidia H200 Tensor Core GPU instances. These new offerings are engineered for large-scale AI workloads and are expected to provide the performance needed for training and deploying large foundation models, the company said.

Further strengthening its AI consulting capabilities, IBM is launching AI Integration Services through IBM Consulting. These services utilise Nvidia Blueprints to help clients implement agentic AI across various industries. Use cases include autonomous inspections in manufacturing and proactive video analysis in the energy sector. The consulting arm will also assist enterprises in modernising compute-intensive workloads across hybrid cloud environments, using Red Hat OpenShift and Nvidia AI technologies such as NeMo, AI Enterprise, and Clara.

According to a 2024 IBM report, 77 percent of executives now believe generative AI is market-ready, up from 36 percent in 2023. IBM and Nvidia said this collaboration between them will enable IBM to provide hybrid AI solutions that take advantage of open technologies and platforms while also supporting data management, performance, security, and governance.

“IBM is focused on helping enterprises build and deploy effective AI models and scale with speed,” said Hillery Hunter, CTO and General Manager of Innovation, IBM Infrastructure. “Together, IBM and Nvidia are collaborating to create and offer the solutions, services and technology to unlock, accelerate, and protect data – ultimately helping clients overcome AI’s hidden costs and technical hurdles to monetise AI and drive real business outcomes.”

“AI agents need to rapidly access, fetch and process data at scale, and today, these steps occur in separate silos,” said Rob Davis, vice president, Storage Networking Technology, Nvidia. “The integration of IBM’s content-aware storage with Nvidia AI orchestrates data and compute across an optimised network fabric to overcome silos with an intelligent, scalable system that drives near real-time inference for responsive AI reasoning.”

2. IBM Acquires Hakkoda to Expand Data and AI Consulting Capabilities

IBM has acquired global data and AI consultancy Hakkoda in a move to bolster IBM Consulting’s data transformation services and expand its AI-powered consulting capabilities. The acquisition, which closed on April 2, 2025, brings Hakkoda’s expertise in modern data platforms and generative AI into IBM’s portfolio of enterprise AI solutions.

Hakkoda, a Snowflake partner, specialises in data estate migration, modernisation, and monetisation. Its addition to IBM Consulting enhances IBM’s ability to help clients build integrated enterprise data estates that are optimised for speed, cost and efficiency across multiple business use cases.

Hakkoda also brings a portfolio of generative AI-powered assets that can speed up data modernisation projects, along with industry-tailored solutions in sectors such as financial services, the public sector, and healthcare and life sciences. Hakkoda will further expand IBM’s ability to bring both consulting expertise and AI to clients using its AI-powered delivery platform, IBM Consulting Advantage.

“IBM is at the leading edge of the consulting industry with how we’re supercharging our consultants with AI,” said Mohamad Ali, Senior Vice President and Head of IBM Consulting. “With Hakkoda’s data expertise, deep technology partnerships and asset-centric delivery model, IBM will be even better positioned to deliver value faster to clients as they transform with AI.”

Erik Duffield, CEO and Co-founder of Hakkoda, emphasised the alignment in vision: “From the beginning, Hakkoda has committed to being ‘in the arena,’ not observing the greatest transformation in history but shaping it.

Global demand for enterprise intelligence services is surging, with IDC estimating the market will grow from USD 169 billion in 2024 to more than USD 243 billion by 2028, driven by a 13 percent compound annual growth rate, IBM highlighted.

Headquartered in New York, Hakkoda expands IBM’s global consulting footprint with a team of experts across the United States, Latin America, India, Europe, and the United Kingdom. Financial terms of the deal were not disclosed.

3. IBM Unveils z17 Mainframe Engineered for the AI Age

IBM introduced the IBM z17, the next generation of its flagship mainframe platform, built to embed artificial intelligence (AI) across hardware, software, and systems operations. Powered by the new IBM Telum II processor, the z17 marks a significant leap in enterprise computing, offering real-time AI processing, enhanced security, and a modernised developer experience.

The z17 expands IBM’s AI capabilities beyond transactional AI to enable new workloads, boasting the ability to handle 50 percent more AI inference operations per day than its predecessor, the z16. Engineered to support over 250 enterprise AI use cases such as mitigating loan risk, managing chatbot services, supporting medical image analysis or impeding retail crime, the system positions enterprises to score 100 percent of transactions in real time.

According to IBM, the platform is the product of five years of development and more than 300 patent filings, built with direct input from over 100 clients and in collaboration with IBM Research and Software teams. Central to its design is the second-generation on-chip AI accelerator in the Telum II processor, which supports up to 450 billion inference operations per day with sub-millisecond response times.

Complementing the mainframe’s built-in AI, IBM will launch the IBM Spyre Accelerator in Q4 2025 — a PCIe card designed to enhance generative AI performance and support multi-model AI workloads. According to IBM, this accelerator will allow clients to run AI assistants directly on the z17 without moving sensitive data off-platform.

Developers and IT teams will also benefit from integrated AI tools such as IBM watsonx Code Assistant for Z and watsonx Assistant for Z, now embedded in IBM Z Operations Unite. These tools enable AI-driven incident detection and resolution, streamlining systems management.

“The industry is quickly learning that AI will only be as valuable as the infrastructure it runs on,” said Ross Mauri, general manager of IBM Z and LinuxONE, IBM, in a statement on April 8, 2025. “With z17, we’re bringing AI to the core of the enterprise with the software, processing power, and storage to make AI operational quickly. Additionally, organisations can put their vast, untapped stores of enterprise data to work with AI in a secured, cost-effective way.”

In tandem, IBM previewed z/OS 3.2, the next version of its operating system, planned for Q3 2025. z/OS 3.2 will support hardware-accelerated AI and expand access to NoSQL databases and hybrid cloud data, enhancing enterprise insights from broader data sets.

IBM announced the availability of IBM Vault, a secrets management solution from HashiCorp that secures keys, certificates, and tokens across hybrid environments. Additionally, IBM plans to introduce AI-powered data classification and threat detection on z/OS, helping identify malicious activity using natural language processing and Telum II acceleration.

IBM is also enhancing support services for z17 through AI-driven lifecycle solutions delivered by IBM Technology Lifecycle Services. These services aim to improve incident resolution and operational efficiency for mission-critical workloads.

Availability

IBM z17 will be generally available starting June 18, 2025, with the IBM Spyre Accelerator expected in Q4 2025.

Also Read: IBM Releases New AI Models Built for Business

4. IBM Announces USD 150 Billion Investment in America Over Next Five Years

IBM announced plans to invest USD 150 Billion in America over the next five years. This includes an investment of more than USD 30 billion in research and development to advance and continue IBM’s American manufacturing of mainframe and quantum computers, the company said in a statement on April 28, 2025.

“Technology doesn’t just build the future — it defines it,” said Arvind Krishna, IBM chairman, president and chief executive officer. “We have been focused on American jobs and manufacturing since our founding 114 years ago, and with this investment and manufacturing commitment we are ensuring that IBM remains the epicenter of the world’s most advanced computing and AI capabilities.”

IBM said it manufactures the cutting-edge mainframes that are the technology backbone of the American and global economies in Poughkeepsie, New York. More than 70 percent of the entire world’s transactions by value run through the IBM mainframes that are manufactured right here in America, IBM said.

IBM also added that it operates the world’s largest fleet of quantum computer systems, and will continue to design, build and assemble quantum computers in America.

5. IBM Launches New Autonomous Security Capabilities with Agentic AI

IBM introduced new agentic and automation capabilities to its managed detection and response service offerings to help enable autonomous security operations and predictive threat intelligence for clients. The company is launching the Autonomous Threat Operations Machine (ATOM), an agentic AI system providing autonomous threat triage, investigation, and remediation with minimal human intervention.

IBM is also introducing the new X-Force Predictive Threat Intelligence (PTI) agent for ATOM, which leverages industry vertical-specific AI foundation models to generate predictive threat insights on potential adversarial activity and minimise manual threat hunting efforts, according to the company’s statement on April 28, 2025.

“By delivering agentic AI capabilities, IBM is automating threat hunting to help improve detection and response processes so clients can unlock new value from security operations and free up already scarce security resources,” said Mark Hughes, Global Managing Partner for Cybersecurity Services, IBM.

PTI is built on industry-specific foundational models and curates intelligence from over 100 sources, including IBM’s own X-Force Threat Intelligence, open-source RSS feeds, APS, and client-specific organisational context.

With ATOM acting as a vendor-agnostic digital operator, IBM enables integration with a wide array of security tools from partners such as Google Cloud, Microsoft, and others.

As part of IBM Consulting’s broader cybersecurity services portfolio, these enhancements aim to streamline operations in Security Operations Centers (SOCs) and help enterprises transition toward autonomous, AI-powered security environments.

“New advanced AI capabilities help transform cybersecurity operations, driving efficiency and precision in threat hunting, detection, investigation and response,” IBM said.

Also Read: IBM Study Predicts Vehicles to Be Software-Defined and AI-Powered by 2035

6. Box and IBM Partner to Accelerate AI Adoption for Enterprise Content Workflows

Box, the Intelligent Content Management (ICM) platform, and IBM announced on April 29 that they are partnering to help organisations accelerate the adoption of enterprise-level AI for content-driven workflows using IBM watsonx and Box AI. Additionally, Box is using IBM watsonx.governance internally for life-cycle management of AI models to monitor, govern and provide guardrails for various regulations.

“The majority of an organisation’s data is often unstructured — buried within contracts, spreadsheets, presentations and more. This data can be highly valuable for AI, but often highly sensitive. Building a trusted technology pipeline for AI to access this data can be essential for security and compliance efforts, particularly in highly regulated industries,” the official release said.

Box customers now have the option of leveraging Box AI with IBM watsonx to help unlock the value of their enterprise content and data. The solution uses IBM’s enterprise AI studio, watsonx.ai, to deliver a selection of models for Box AI – including the open-source, IBM Granite models and the latest Meta Llama models.

According to Box and IBM, infusing AI capabilities into business process automation and content management can help organisations tackle a wide range of AI-driven use cases such as data extraction, automated document processing and content analysis. IBM is using Box AI with IBM watsonx within its own workforce, and Box is now making this solution available to other enterprise customers.

“The impact AI is having on the enterprise is unlike anything we’ve seen since the birth of the internet,” said Aaron Levie, co-founder and CEO of Box. “Traditionally, knowledge work has been constrained by the time it takes to research, create and review content — but AI changes that, accelerating these processes exponentially. By deepening our partnership with IBM and leveraging watsonx, we’re empowering enterprises to harness AI responsibly and at scale.”

“Organisations are seeking purpose-built AI solutions that empower their teams to make faster, data-driven decisions,” said Rob Thomas, Senior Vice President, Software and Chief Commercial Officer, IBM. “Our partnership with Box enables businesses to seamlessly integrate AI into their core processes, helping to enhance productivity and transform operations.”

Box uses IBM watsonx.governance internally to help address responsible AI deployment across model lifecycles, from development to production. IBM has enabled Box AI with IBM watsonx to elevate employee productivity within its own workforce, providing them with interaction directly with their Box content. Box AI with IBM watsonx is now available to Box Enterprise Advanced customers via Box AI Studio and Box AI APIs, the official release said.

7. IBM and EY Launch EY.ai for Tax Built with IBM watsonx to Automate Global Tax Compliance

IBM and EY on Thursday announced the availability of EY.ai for tax, built with IBM watsonx. “The alliance couples watsonx, IBM’s portfolio of artificial intelligence (AI) technologies, with the EY organisation’s deep domain experience to address the largest challenges facing tax departments,” the companies said in a joint statement on May 1, 2025.

EY.ai for tax

EY.ai for tax, built with IBM watsonx, is powered by open-source AI models, including IBM Granite, to help organisations automate tax compliance and streamline global data management. With this announcement, IBM and the EY organisation are helping clients address their limited resources, multiple enterprise resource planning (ERP) systems across client environments, talent shortages and complex regulations by creating novel generative AI solutions that multiply productivity, the official release said.

The suite is already operational within IBM’s own tax department, supporting its goal of automating 80 percent of foreign tax compliance and delivering major efficiency gains.

“The solutions are currently in use by IBM’s Tax Department to automate previously manual, time-consuming processes, and the solutions are expected to save tens of thousands of hours annually. By streamlining tax compliance with AI, IBM is on track to exceed its goal of automating 80 percent of its foreign tax compliance. Prioritising security and trust, these solutions help safeguard sensitive tax data to help avoid potential negative consequences, such as costly penalties and reputational damage,” IBM said.

“The success of the alliance has been proven with the deployment of EY.ai for tax, built with IBM watsonx, with the IBM tax department. We flipped the long-held view of tax as an administrative function to a value creation function for businesses with AI-enabled solutions that are highly cost effective and performant all while prioritizing governance and trust,” said Martin Fiore, EY Americas Deputy Vice Chair – Tax.

The First Three AI-Powered Solutions:

• Intelligent Tax Data Lake: Built on watsonx.data and watsonx.ai, this solution automates the ingestion, consolidation, and enrichment of tax data from disparate sources. For IBM, it handles data from 36 systems, enabling high-quality data output and minimising manual reconciliation.
• Detect and Correct with Business Documents: Using watsonx.ai and IBM Research’s Docling toolkit, this system extracts and analyses data from unstructured documents like invoices, comparing it with ERP entries to identify and correct errors—dramatically increasing processing capacity.
• Withholding Tax Determinations: Built with watsonx.ai, this solution automates the evaluation of withholding tax rates across thousands of intercompany transactions each month, improving accuracy and speed while reducing compliance risks.

“We manage massive volumes of granular data from disparate sources to file thousands of tax returns across hundreds of legal entities worldwide. By combining EY domain expertise in tax and IBM’s AI technology, we were able to transform the way our tax department handles global tax compliance, freeing up the team to focus on more strategic work,” said IBM Vice President and Chief Tax Officer Kanthi Morrissey.

According to the official release, IBM and EY teams are working to further enhance these solutions and to expand them to other tax processes with an eye towards further re-use and applications.