Kyndryl Launches AI Orchestration for Business to Accelerate Agent-Driven Transformation
Kyndryl has announced Kyndryl AI Orchestration for Business, a new capability built with the Kyndryl Agentic AI Framework designed to move enterprises beyond experimentation and siloed workflows to enterprise-wide AI impact.
As organizations in retail, consumer packaged goods (CPG), travel and transportation, and other industries struggle to leverage AI to meet customer expectations around personalized experiences, real-time responsiveness and seamless fulfillment, Kyndryl AI Orchestration for Business helps to address these challenges. The capability autonomously interacts with AI agents across supply chains, commerce, finance, IT and customer operations to enable seamless coordination, cross-functional alignment and controlled execution at scale – supporting governed, policy-driven AI agent functionality.
“Enterprises are moving fast to embrace AI, but most are stuck in isolated pilots that don’t change or improve their daily operations,” said Rachel Calhoun, Vice President and Global Retail, CPG, and Travel and Transportation Leader at Kyndryl. “Kyndryl AI Orchestration for Business helps companies bring order and clarity to AI complexity – coordinating how AI agents act across business functions, with clear guardrails and human oversight. ”
Kyndryl AI Orchestration for Business combines data, events and AI agents from across the enterprise to support role-based decision making and real-time action. Instead of reacting to issues after they occur, leaders and frontline teams receive proactive alerts, recommended actions and embedded agentic workflows that allow them to augment their own workstreams to intervene or approve automated actions before disruptions impact customers or revenue.
Kyndryl AI Orchestration for Business supports agentic workflows for use cases across store and enterprise operations, including:
- Agentic Commerce: Connects supply chain, pricing, promotions and customer engagement – allowing organizations to anticipate demand shifts, manage disruptions and personalize customer experiences without sacrificing control
- Proactive supply chain disruption management: Identifies supply risks, impacted SKUs and financial exposure in real time, prompting planners and managers to act before stock‑outs reach stores or customers
- Role‑based operational orchestration: Delivers alerts, recommendations and actions to the right roles – such as demand planners, supply chain leaders and pricing teams – enabling faster, more coordinated decisions across functions
- Policy‑driven execution and auditability: Embeds operational, regulatory and business rules directly into agent workflows at the reasoning level using policy as code, with full transparency into how decisions are made and executed
- Coordinated commerce and customer experience enablement: Aligns supply, inventory, pricing and fulfillment decisions in real time to reduce disruptions, protect revenue and deliver a more consistent customer experience
Kyndryl Consult experts help organizations design, deploy and scale AI orchestration using the Kyndryl Agentic AI Framework and the company’s experience managing mission-critical systems across hybrid cloud, on-premises and edge environments. The cloud- and model-agnostic platform integrates with existing enterprise systems and supports modernization at each organization’s preferred pace. Kyndryl accelerates enterprise transformation through AI-native industry architectures, workflow catalogs and modernization services that help organizations unlock legacy data and transactions from mainframe and distributed systems, re-architect applications, and enable agentic workflows across complex technology environments.
Source: Kyndryl
Rocket Software Joins HPE Unleash AI Partner Program to Accelerate AI Adoption
Rocket Software has announced an expanded strategic collaboration with HPE, joining the HPE Unleash AI partner program to help enterprises accelerate AI adoption across mission-critical environments.
The collaboration builds on Rocket Software’s recent acquisition of Vertica and deepens the integration of the Vertica high-performance analytics platform with HPE infrastructure. Rocket DataEdge Data Replicate and Sync is the first Rocket Software product validated within the HPE Unleash AI ecosystem, enabling organizations to make system-of-record data available to AI and analytics platforms in real time without disrupting core business systems.
Together, Rocket Vertica, HPE GreenLake and HPE Alletra Storage MP X10000 provide a foundation for enterprise AI by combining high-performance analytics with scalable object storage for data-intensive, mission-critical workloads. The companies say the combined approach can help enterprises reduce data movement, lower costs and accelerate time to insight across hybrid environments.
“At Rocket Software, we believe the future of AI is built on trusted, high-performance data wherever it lives,” said Michael Curry, President of Data Modernization, Rocket Software. “Our partnership with HPE and the acquisition of Vertica bring that vision to life by combining powerful AI with hybrid flexibility to help enterprises unlock value faster.”
Source: Rocket Software
IBM Launches Global AI Builders Challenge With IBM Bob for University Students, Expanding Availability of IBM Bob to 20,000 Post-Secondary Institutions Worldwide
IBM has announced the AI Builders Challenge, a global challenge with IBM Bob – IBM’s new AI-powered development partner – that will help university students build practical AI and software development skills for the future of work.
The Challenge comes as employers increasingly expect graduates to know how to use AI, yet many students lack opportunities to practice those skills before entering the workforce. A recent survey from the American Association of Colleges and Universities and Elon University found that 63 percent of faculty said graduates were not very or not at all prepared to use generative AI in the world of work. The AI Builders Challenge is intended to help address that gap by giving students practice with AI in a setting where their work has to be tested, explained and improved.
Announced during IBM’s Future of AI in Higher Education Summit in New York City, the Challenge gives students a hands-on way to develop AI skills in software development while creating projects they can showcase beyond the classroom. The announcement coincides with IBM’s expansion of free access to IBM Bob for higher education, making the technology available to 20,000 post-secondary institutions worldwide.
Through IBM SkillsBuild, students will use IBM Bob in a challenge-based experience that reflects the kind of software development work they may encounter in the workplace. The Challenge is tied to real-world themes, including “Create with AI: The Future of Creative Industries”, “Mission Beyond Earth: Space Exploration”, and “Work Reimagined: Transforming Industries through Intelligent Work Systems.”
Unlike earlier AI tools that focused mainly on speeding up code generation, IBM Bob is designed to work with developers across the entire software development lifecycle. IBM Bob integrates orchestration, execution and governance directly into development workflows, helping teams move from isolated tasks to coordinated delivery.
For students, this means learning how to use AI to support code generation while gaining experience applying AI to development work that requires an understanding of how software systems need to be modernized and scaled in real environments. By building a project through the AI Builders Challenge, students can create a tangible example of applied AI work that can be shared with potential employers.
The Challenge, organized by BeMyApp, is open to eligible university students 18 years of age or older across participating countries and welcomes students from all majors. Participants can work individually or in teams, submit final projects through GitHub and access support through Discord, mentors, office hours and webinars. Winners will be selected by a panel of judges who will evaluate submissions based on technical execution, innovation, challenge fit, implementation and feasibility.
Winners will compete for a share of the $15,000 USD total prize pool, including a Grand Prize of $5,000 for the top project across the Challenge. Four winners will be selected for each of two monthly competitions to win prizes ranging from $750 to $2,250 USD. Participants will also gain opportunities to build a professional network through the Challenge community and IBM ecosystem. The Grand Prize winner will be invited to IBM TechXchange, IBM’s global conference where developers, engineers, scientists, and researchers build real‑world skills, giving the winner visibility with a global technology audience.
This effort builds on IBM’s commitment to skill 30 million people by 2030 and IBM’s broader university strategy, which aims to help students, faculty and institutions move from AI literacy to AI fluency. Through IBM SkillsBuild, IBM provides free learning, digital credentials, faculty enablement, hands-on labs and challenge-based experiences that help learners build skills they can demonstrate in an AI-driven economy.
Source: IBM
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New IBM Study Finds CIOs and CTOs Face Growing AI Control Gap as Enterprise Deployment Scales
A new IBM Institute for Business Value study reveals that as AI moves from experimentation to enterprise-wide deployment, two-thirds of surveyed CIOs and CTOs report being held accountable for AI systems they do not fully control, while governance struggles to keep pace at scale.
The global study of 2000 C-level technology executives (tech CxOs) finds that the lack of visibility is widespread. The majority of surveyed executives (70%) say teams across the business are deploying technology faster than IT can track.
At the same time, technology leaders face growing pressure to scale AI faster, even as many lack the structures to support it. By 2027, surveyed tech CxOs anticipate a 38% increase in the number of AI agents deployed. While 80% of respondents report CEO-driven AI transformation mandates, only 11% believe they are fully ready for the scale of AI agent deployment expected in the next year. Governance is also falling behind, with 77% of organizations surveyed reporting AI adoption is already outpacing current governance capabilities.
“For CIOs and CTOs, the challenge now is scaling AI systems that operate continuously and autonomously, often within governance models and architectures designed for a far slower, more predictable environment,” said Matt Lyteson, CIO, IBM. “It is no longer just about deploying AI faster. It’s redesigning how organizations control, govern and invest in it and embedding control and visibility from the start, so they can scale with confidence.”
As AI scales, operational and security risks are growing
- Analysis shows that in organizations relying on manual governance, incident risk increases as AI adoption scales, whereas those that embed control directly into their AI systems experience 25% fewer incidents.
- Most (59%) of tech CxOs surveyed cite security and compliance concerns as top barriers to scaling AI agents.
- Surveyed organizations experienced an average of 54 AI agent incidents last year, in which an unintended and/or harmful occurrence required human correction.
- According to respondents, 17% of those AI agent incidents reported were high severity, requiring more than four hours to contain:
- 37% resulted in data exposure or security breaches
- 33% caused cascading system failures
- 17% triggered compliance issues
Organizations that redesign AI control and investment see stronger outcomes
- AI spend is projected to grow from just under 15% of IT budgets in 2025 to nearly 25% by 2027 – a 71% increase in two years, raising the stakes for CIOs and CTOs.
- Yet, 84% of tech CxOs have not fully operationalized AI financial management, and 85% still lack full visibility into real-time AI spend.
- Analysis finds that organizations that build control into their AI systems:
- deploy 16x more AI agents than those relying on manual governance
- deliver 18% higher operating margins
- spend 4x less of their AI budget
- Analysis shows organizations with strong financial discipline:
- deploy 2.4x more AI agents with no higher AI/IT budget
- are 3x more likely to say they are fully prepared for AI scale
- Surveyed organizations that designed for adaptability early – keeping workloads portable and models replaceable rather than locked into hard dependencies – reported a 10% higher return on AI investment in 2025.
The full study, including recommendations for technology leaders on redesigning structures that govern speed, control and investment, can be found at: https://www.ibm.com/thought-leadership/institute-business-value/en-us/c-suite-study/cxo
Source: IBM
OpenLegacy Integrates into AWS Transform for Modernization to Keep Mainframe Workloads Connected as They Move to the Cloud
AWS and OpenLegacy have announced OpenLegacy’s integration with AWS Transform for Modernization, AWS’s service for modernizing legacy systems. The integration helps enterprises keep modernized cloud workloads connected to the mainframe systems still in place, enabling the incremental, workload-by-workload approach that AWS Transform for Modernization makes possible, while reducing risk and disruption to business operations.
The integration is set to be showcased at AWS Summit New York on June 17, 2026 by Omri Kessel, AWS General Manager, Agentic AI Modernization, marking the first public demonstration of the embedded OpenLegacy experience within AWS Transform for Modernization.
Because AWS Transform for Modernization recovers the business logic buried in legacy code at machine speed, enterprises no longer have to modernize an entire environment at once. They can modernize incrementally, one workload at a time. For that incremental approach to work, each workload that moves to AWS has to keep communicating with the rest of the mainframe estate, and that is what OpenLegacy enables.
Enterprises operate hybrid models throughout the journey, where cloud-native services and the live mainframe must stay tightly connected as each migration wave progresses.
OpenLegacy enables this through its decoupling capability, which automatically generates integration bridges and API facades to and from the mainframe, keeping modernized cloud workloads connected to the systems still running on the mainframe. By preserving communication between the old and new environments throughout the migration, organizations modernize incrementally while reducing operational risk.
The experience is composed directly into AWS Transform for Modernization’s jobs and modernization flow. When users reach the decomposition stage of a migration, OpenLegacy’s technology operates within the AWS Transform environment to generate cloud APIs and integration points without requiring a separate toolset. Modernization teams maintain continuity between transformed applications and the systems still on the mainframe as projects advance in phases.
Source: PR Newswire
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