Kyndryl Unveils Agentic AI Framework that Dynamically Evolves to Drive Enhanced Business Performance
For example, in the case of a plant, AI could predict growing demand for a certain type of seasonal shrub and increase its orders as interest rises, then place the plants in the most obvious in-store location. The Atos Polaris AI platform is made available to Atos clients for AI transformation projects as well as selective strategic partnerships. AI agents continuously analyze behavioral signals from systems like email, browsers, simulated exercises, training assignments and developer tools. This allows them to identify anomalies and evolving threats beyond what manual reviews or periodic training can detect.
How Agentic AI Can Transform Human Risk Management
Kyndryl, a provider of mission-critical enterprise technology services, today launched the Kyndryl Agentic AI Framework, a new approach to deploying agentic AI to augment human teams. The enterprise-grade Framework orchestrates and dispatches a portfolio of specialised, self-directed, self-learning AI agents that dynamically respond to shifting conditions and keep humans in the loop for oversight. One of the largest opportunities for companies to create value with generative AI and AI agents is said to be in the redesign of business processes and operations. This is likely to attract a significant amount of AI investment budgets, as the technology promises to transform organizations into AI-powered companies with dramatically increased productivity through a new type of service known as intelligent operations. NEW YORK, July 17, 2025 /PRNewswire/ — Kyndryl, a leading provider of mission-critical enterprise technology services, today launched the Kyndryl Agentic AI Framework, a new approach to deploying agentic AI to augment human teams. The enterprise-grade Framework orchestrates and dispatches a portfolio of specialized, self-directed, self-learning AI agents that dynamically respond to shifting conditions and keep humans in the loop for oversight.
Achieving buy-in from the people in your organization
The days of betting on a single large language model (LLM) provider are over. A consistent theme throughout Transform 2025 was the move towards a multi-model and multi-cloud strategy. Enterprises want the flexibility to choose the best tool for the job, whether it’s a powerful proprietary model or a fine-tuned open-source alternative. Companies like Intuit, Capital One, LinkedIn, Stanford University and Highmark Health are quietly putting AI agents into production, tackling concrete problems, and seeing tangible returns.
That’s because it stems from a flawed premise — specifically, that AI agents should be expected to replace humans outright. “Common barriers to achieving integrated agent systems include fragmented data environments, lack of interoperability between tools, and siloed organizational structures,” says PwC’s AI expert. Both AI leaders agreed that enabling rapid development at scale demands thoughtful architectural design. At Intuit, the creation of GenOS empowers hundreds of developers to build safely and consistently. The platform ensures each team can access shared infrastructure, common safeguards, and model flexibility without duplicating work.
Together, these behaviors transform passive knowledge collection into dynamic action, and that’s what gives companies a competitive edge when disruption hits. Ultimately, the pairing of agentic AI and APIs doesn’t just boost productivity—it strengthens your organization’s absorptive muscle. And that’s the kind of agility that turns disruption into a competitive edge.
Challenges to consider
Some field operations perform a set of common tasks at different locations and must adapt to local conditions and requirements. For field operations that perform a wider variety of work types in highly differentiated conditions, AI agentic experiences partner with field engineers to provide real-time information and guidance. People who believe AI agents are exciting because they’ll replace humans have it all wrong. AI agents are exciting not because they’ll replace humans, but because they’ll replace traditional enterprise software. Building trust in AI agents hinges on humans believing there’s a meaningful value proposition at the end of the AI journey. People need to see clear benefits, whether it’s efficiency, insight, or new capabilities.
- That said, Nair emphasized that Lowe’s approach is to augment staff and not put them out of work; using AI for store-layout optimization requires “human creativity,” he said, in addition to “data-powered insights” and “efficient technology.”
- This is as true of AI agents as it is of any other sort of intelligent entity we leverage inside the enterprise, including humans.
- Retraining mid-level managers and production planners is essential to drive trust, prevent confusion and build alignment around new workflows.
- Many first-generation mobile applications were direct adaptations of their web equivalents.
The strategic use of agentic AI can help bridge the gap between awareness and action by reducing response time from detection to intervention, scaling personalized experiences across thousands of employees and ensuring interventions are timely, relevant and effective. This elevates HRM from being a compliance tool to a behavior-change engine. With every interaction, agents can learn what works—refining nudges, timing, content and delivery channels to increase engagement and behavior change. Instead of generic e-learning, agents deliver micro-interventions tailored to the user’s context, behavior and role. A salesperson clicking suspicious links might receive a quick deepfake vishing call of a real threat scenario. A developer committing secrets to GitHub might get an immediate Slack nudge with secure coding tips.
- Unlike earlier forms of AI that wait for human prompts, agentic systems initiate and complete multistep workflows.
- Infosys’s approach minimizes customization overhead and accelerates value realization, making ERP modernization more adaptive and cost-effective.
- A prudent strategy begins by allowing AI agents to suggest actions while keeping humans firmly in the decision-making loop.
How to use genAI for requirements gathering and agile user stories
Join leaders from Block, GSK, and SAP for an exclusive look at how autonomous agents are reshaping enterprise workflows – from real-time decision-making to end-to-end automation. Atos, a global leader in AI-powered digital transformation, announced the launch of the Atos Polaris AI platform, a comprehensive system of AI agents that operate autonomously to orchestrate complex workflows. The report also found that increases in and experimentation with agentic AI over the next 24 months will spur workforce transformation and innovation throughout the organization. The majority of software executives (69%), anticipate AI will introduce new, more specialized roles (e.g., oversight, governance, prompt engineering, agent architect, and agent orchestration) to accommodate the evolving role AI will play within organizations. More than three out of five respondents (63%) also feel that AI will require substantial upskilling or reskilling within existing development teams. Fast forward to 2025, and absorptive capacity is a mission-critical concept that’s essential for all future-focused organizations, especially as agentic AI takes hold.
Together, they don’t just automate tasks—they power continuous learning and adaptation. Unlike earlier forms of AI that wait for human prompts, agentic systems initiate and complete multistep workflows. Even when SaaS platforms announce agentic experiences, data teams should evaluate whether data volume and quality on the platform are sufficient to support the AI models. Agentic AI refers to systems that operate with a degree of autonomy—capable of perceiving, deciding and acting in pursuit of a defined goal.
OutSystems is a leading AI-powered low-code development platform, empowering IT leaders with a better way to build the software that matters most. The OutSystems platform helps companies develop, deploy, and maintain mission-critical applications by unifying and automating the entire software lifecycle. With OutSystems, organizations leverage gen AI to deliver software instantaneously, adapt faster to changing requirements, and reduce technical debt by building on a future-proof platform. Helping customers achieve their business goals by addressing key strategic initiatives, OutSystems delivers production software up to 10x faster than traditional development. Recognized as a leader by analysts, IT executives, business leaders, and developers around the world, global brands trust OutSystems to tackle their impossible projects and turn their big ideas into software that moves their business, people, and the world forward.
