University of Kwazulu-Natal

Ibm Unveils Ai Tools To Accelerate Ai Agent Adoption Ibm Think 2025

Bonisiwe Shabane
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ibm unveils ai tools to accelerate ai agent adoption ibm think 2025

ARMONK, N.Y., May 6, 2025 /PRNewswire/ -- Today at the company's annual THINK event, IBM (NYSE: IBM) is unveiling new hybrid technologies that break down the longstanding barriers to scaling enterprise AI – enabling... IBM estimates that over one billion apps will emerge by 2028, putting pressure on businesses to scale across increasingly fragmented environments. This requires seamless integration, orchestration and data readiness. A new IBM CEO study shows that business leaders expect the growth rate of AI investments to more than double over the next two years, with most actively adopting AI agents and preparing to... Yet their pace of investments has led to disconnected technology – and only 25% of AI initiatives have achieved the ROI they expected. IBM is combining hybrid technologies, agent capabilities and deep industry expertise from IBM Consulting to help businesses operationalize AI.

"The era of AI experimentation is over. Today's competitive advantage comes from purpose-built AI integration that drives measurable business outcomes," said Arvind Krishna, Chairman and CEO, IBM. "IBM is equipping enterprises with hybrid technologies that cut through complexity and accelerate production-ready AI implementations." To get started with generative AI, first focus on areas that can improve human experiences with information. IBM ramps up its efforts to push AI deeper into the enterprise by expanding its Watsonx platform and unveiling new integration and data tools that aim to address one of the technology’s biggest obstacles:... The announcement, made during the company’s Think event, outlines IBM’s strategy to help organisations design and deploy AI agents that integrate with complex digital environments and fragmented data sources.

IBM says a key issue hindering enterprise AI is the failure to integrate systems across hybrid and multi-cloud setups. The company’s internal research shows that although interest in AI continues to grow, only 25% of AI initiatives have met expectations in terms of return on investment. IBM points to technology sprawl and a lack of orchestration as reasons for this shortfall. ARMONK, N.Y. — At the company’s annual THINK event, IBM unveiled new hybrid technologies for scaling enterprise AI – designed to enable businesses to build AI agents with their own enterprise data. IBM estimates that over 1 billion apps will emerge by 2028, putting pressure on businesses to scale across increasingly fragmented environments.

This requires integration, orchestration and data readiness. The company said a new IBM CEO study shows that business leaders expect the growth rate of AI investments to more than double over the next two years, with most adopting AI agents and... Yet their pace of investments has led to disconnected technology – and only 25 percent of AI initiatives have achieved the ROI they expected, IBM said. IBM is combining hybrid technologies, agent capabilities and support from IBM Consulting to help businesses operationalize AI. “The era of AI experimentation is over. Today’s competitive advantage comes from purpose-built AI integration that drives measurable business outcomes,” said Arvind Krishna, Chairman and CEO, IBM.

“IBM is equipping enterprises with hybrid technologies that cut through complexity and accelerate production-ready AI implementations.” Build AI agents in watsonx Orchestrate that work with 80+ leading business applications IBM Corp. is using its Think 2025 conference in Boston this week to introduce a sweeping set of artificial intelligence and hybrid cloud technologies aimed at accelerating enterprise adoption of AI agents. The venerable tech giant said it’s focused on making the new breed of autonomous software that can take actions independently while working toward a specified goal, easier to build and orchestrate. The new technologies are designed to address what Chief Executive Arvind Krishna called the “fragmentation of infrastructure” that has stalled many AI initiatives.

He cited internal research that found that only 25% of enterprise AI projects have delivered expected returns on investment. IBM is tackling this shortfall with tools for building and orchestrating AI agents, unifying enterprise data and scaling AI inference, the process of running trained models. Central to IBM’s announcements is watsonx Orchestrate, a platform the company claims enables businesses to build AI agents in less than five minutes. The system includes over 150 prebuilt agents, integrations with more than 80 enterprise applications, and orchestration tools that enable multiple agents to collaborate across complex workflows. “We think this will appeal to both low-code and pro-code developers,” Krishna said in a press briefing. “Agents are going to form an integral part of how generative AI is used in enterprises.”

Get the latest updates delivered to your inbox every day, and stay up-to-date for free 🧠📈 Get the latest updates delivered to your inbox every day, and stay up-to-date for free 🧠📈 How IBM's new AI solutions ease deployment and integration for your business IBM unveils a suite of enterprise-ready agents, data integration tools, and much more. IBM is holding its annual THINK conference this week, and, unsurprisingly, artificial intelligence is the star of the show. The common theme across IBM's broad swath of product unveilings is a focus on solutions that make it easier to scale enterprise AI in organizations, tackling challenges organizations face with AI deployment and integration.

AI agents are the latest breakthrough in the AI space, taking the assistance that AI chatbots provide a step forward by actually performing tasks for people. Although agentic AI is a technology most enterprises should take advantage of, businesses face several implementation challenges, including finding ways to integrate it seamlessly into their various apps, data, and environments. Also: Why scaling agentic AI is a marathon, not a sprint To address these challenges, IBM unveiled a suite of enterprise-ready agents in watsonx Orchestrate. According to IBM, these AI tools enable businesses to build their own agents in under five minutes with both no-code and pro-code options; leverage pre-built agents for specialized use in specific domains such as... IBM also announced a new Agent Catalog in watsonX Orchestrate, which lets businesses more easily identify and access the best agent for their business use case from 150+ agents and prebuilt tools made available... IBM also introduced webMethods Hybrid Integration, a solution designed to help enterprises integrate AI into their business operations with agent-driven automation.

According to IBM, this makes it easier to manage "integrations across apps, APIs, B2B partners, events, gateways, and file transfers in hybrid cloud environments." Based on interviews with several companies using webMethods, an independent... The study found that over three years, this composite organization experienced a 176% ROI, a 40% reduction in downtime, 33% time savings on complex projects, and 67% time savings on simple projects. Generative AI applications require a lot of data, and the efficiency of the AI model depends on the quality of that data. However, getting data into the ideal condition is often a challenge for businesses, as this typically takes lots of manual work to locate the unstructured data and then organize and structure it in a... IBM's new watsonx.data seeks to help with that issue by combining an open data lakehouse with data fabric capabilities to help businesses unify and activate data across different formats and silos. According to IBM, wastsonx.data will help users connect their unstructured data with AI apps and agents, which would lead to 40% more accurate AI than when using the conventional RAG method.

Also: RAG can make AI models riskier and less reliable, new research shows To further help enterprises work with unstructured data, IBM also launched watsonx.data integration, a single interface where users can access, manage,... IBM also unveiled a new content-aware storage (CAS) capability available as a service in IBM Fusion with IBM Storage Scale. This capability can continuously analyze unstructured data and extract relevant information, which is then made available to RAG applications for faster processing. IBM thinks that over a billion new applications will be built with gen AI : Here's how they're going to help that happen with agentic AI At its Think 2025 conference in Boston, IBM announced a suite of hybrid AI tools aimed at simplifying the deployment and management of generative AI agents across enterprise environments. These tools are designed to integrate seamlessly with existing platforms such as Salesforce, Workday, and Adobe, while also enabling users to develop custom AI agents using IBM’s Granite models or third-party models from Meta...

“We help our clients integrate. We want to meet them where they are,” said IBM CEO Arvind Krishna, emphasizing the company’s commitment to flexibility and client-centric solutions. The new capabilities are part of IBM’s watsonx platform, which offers a comprehensive suite of tools for building, deploying, and governing AI models. The platform supports rapid development, with IBM stating that custom AI agents can be created in under five minutes. IBM’s focus on hybrid cloud solutions positions it uniquely in the AI market, catering to clients who require a mix of public and private cloud infrastructures. This approach is particularly appealing to industries with stringent data security and compliance requirements.

In addition to the product announcements, IBM revealed plans to invest $150 billion in the United States over the next five years. This investment will support the manufacturing of mainframes, quantum computers, and AI technologies, reinforcing IBM’s commitment to domestic innovation and infrastructure. IBM is making aggressive forays in AI and at the company's annual THINK event, IBM is unveiling new hybrid technologies that break down the longstanding barriers to scaling enterprise AI – enabling businesses to... IBM estimates that over one billion apps will emerge by 2028, putting pressure on businesses to scale across increasingly fragmented environments. This requires seamless integration, orchestration and data readiness. A new IBM CEO study shows that business leaders expect the growth rate of AI investments to more than double over the next two years, with most actively adopting AI agents and preparing to...

Yet their pace of investments has led to disconnected technology – and only 25% of AI initiatives have achieved the ROI they expected. IBM is combining hybrid technologies, agent capabilities and deep industry expertise from IBM Consulting to help businesses operationalize AI. "The era of AI experimentation is over. Today's competitive advantage comes from purpose-built AI integration that drives measurable business outcomes," said Arvind Krishna, Chairman and CEO, IBM. "IBM is equipping enterprises with hybrid technologies that cut through complexity and accelerate production-ready AI implementations." AI agents are shifting from AI that chats with you to systems that work for you, yet many enterprises will struggle to integrate them across diverse environments, apps, and data.

IBM is providing a comprehensive suite of enterprise-ready agent capabilities in watsonx Orchestrate to help businesses put them into action. The portfolio includes: Making AI Work for the Enterprise: IBM’s 2025 Vision At the 2025 THINK conference, IBM doubled down on its commitment to enterprise AI by unveiling a series of powerful tools and enhancements designed to solve the real-world deployment and integration challenges businesses face. The event highlighted IBM’s strategic approach to simplifying AI adoption at scale, particularly through automation, intelligent agent technologies, and data-centric enhancements. While AI has become a centerpiece of modern digital transformation, many organizations still grapple with the complexities of implementation — from fragmented data ecosystems to poorly integrated tools.

IBM’s response is a highly coordinated release of solutions under its watsonx brand that aim to reduce friction and drive faster returns on AI investments. AI Agents Evolve: AI agents now move beyond chatbot roles to actually perform tasks across business functions. Agentic AI Challenges: Integration remains a primary barrier, especially across diverse platforms and datasets. Watsonx Orchestrate Suite Launches: IBM introduces enterprise-grade agents with both no-code and pro-code deployment paths. Rapid Agent Development: Build AI agents in under five minutes using IBM’s intuitive tooling. Domain-Specific Agents: Pre-built agents for HR, procurement, and sales enable faster vertical adoption.

Broad Integration Support: Connects seamlessly with over 80 enterprise apps, including AWS, Adobe, and Microsoft. Multi-Agent Coordination: Tools now orchestrate complex workflows involving multiple agents and apps. Governance and Monitoring: Built-in insights, compliance checks, and performance analytics are standard. Agent Catalog Introduced: A library of 150+ agents and tools streamlines enterprise access and adoption. WebMethods Hybrid Integration: A new solution for bridging on-premise and cloud systems with AI-driven workflows. Automation Through Agents: Helps organizations handle data transfer, events, APIs, and partner exchanges more efficiently.

Forrester TEI Study Highlights ROI: Composite customers achieved 176% ROI over three years using IBM’s integration solutions. Reduced Downtime: Businesses reported 40% less system downtime post-implementation. Efficiency Gains: 33% time saved on complex projects; 67% saved on simpler ones. Addressing the Data Gap: AI is only as good as the data it consumes; IBM’s solutions aim to optimize that. Watsonx.data Launched: Merges open data lakehouse architecture with data fabric layers for unified data activation. 40% Improvement in Accuracy: Using watsonx.data yields significantly better AI outcomes compared to traditional retrieval-augmented generation (RAG).

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