The great AI agent acceleration: Why enterprise adoption is happening faster than anyone predicted

A KPMG survey released on June 26, a day after our event, shows that 33% of organizations are now deploying AI agents, a surprising threefold increase from just 11% in the previous two quarters. This market shift validates the trend VentureBeat first identified just weeks ago in its pre-Transform survey. Although many of Lowe’s AI projects are still in their infancy, Nair is optimistic about their role in the century-old retailer’s future. He said his team will continue to “get better at connecting insights and predictions” to “adapt stores even faster” and create “smarter and more personal” experiences for its loyal customers. Of course, as retailers like Lowe’s become more reliant on AI to improve efficiencies, concerns are growing that the technology could wipe out millions of blue-collar jobs in the next few years. 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.”

62 percent of respondents also reported improved scalability of development efforts, and 60 percent pointed to gains in enhanced testing and quality assurance (QA) efficiency. With AI acting as the catalyst for a reimagined software development process, these advancements go beyond efficiency gains. They’re empowering developers to shift their focus from repetitive tasks to crafting unique solutions in partnership with business leaders and solving more complex user challenges, leading to the creation of new roles and improved innovative agility and scalability. The Kyndryl Agentic AI Framework can help organizations confidently deploy AI with trust and security in mind.

How agentic AI will transform mobile apps and field operations

Infosys is transforming ERP deployments by embedding AI across functions like finance and supply chain, enabling faster, more agile rollouts compared to traditional ERP projects. Our AI-powered suite accelerates SAP S/4HANA Cloud transformations by automating complex tasks such as code migration and invoice processing, reducing manual effort and errors. This results in streamlined implementations with enhanced accuracy in demand forecasting and improved operational efficiency. Infosys’s approach minimizes customization overhead and accelerates value realization, making ERP modernization more adaptive and cost-effective. By leveraging AI-driven automation and intelligent insights, Infosys helps enterprises achieve smoother, more responsive ERP transformations that align closely with evolving business needs. The Kyndryl Agentic AI Framework enables enterprises to adopt, deploy and scale agentic AI-powered solutions – whether on-premises, in the cloud or in a hybrid IT setting – to transform and improve their business operations.

What we know now about generative AI for software development

It can also be tailored to meet enterprises’ needs and adapt to industries through self-directed learning, enabling organizations to apply the Framework to a wide range of use cases and projects with speed and confidence. The Kyndryl Agentic AI Framework enables enterprises to adopt, deploy and scale agentic AI-powered solutions – whether on-premises, in the cloud or in a hybrid IT setting – to transform and improve their business operations. The Framework combines advanced algorithms, self-learning, optimization and secure-by-design AI agents that translate complex data into clear, understandable insights. The report says that with agentic AI, leaders can automate large-scale processes, create hyper-personalised digital experiences, and drive innovation with agility.

• This includes robust data pipelines, APIs, and governance frameworks to help agents operate reliably and responsibly at scale.
• As GitHub and Atlassian noted, engineers are now learning to manage fleets of agents.
• A poorly timed or incorrect AI action can damage credibility and reduce engagement.
• While pushing for autonomy, human oversight remains crucial at critical junctures.
• However, you can’t simple wave a magic wand and get enterprise-wide agentic AI that works perfectly.

While tech leaders like Elon Musk, Mark Zuckerberg and Sam Altman are talking about the dawn of superintelligence, enterprise practitioners are rolling up their sleeves and solving immediate business challenges. This trend is creating a powerful but constrained ecosystem, where GPUs and the power needed to generate tokens are in limited supply. Looking ahead, companies must approach the agentic AI shift with clarity.

In HRM, that goal is to reduce human-induced cybersecurity risk by monitoring and learning from individual behaviors and contextual data in real time. Sagi Eliyahu is the co-founder and CEO of Tonkean, an AI-powered intake and orchestration platform that helps enterprise-shared service teams such as procurement, legal, IT and HR create processes that people actually follow. Tonkean’s agents use AI to anticipate employees’ needs and guide them through their requests. He recommends that leaders prepare their people for an AI-enabled future, which involves learning to work alongside agents, to unlocking value from data, to building high-performing teams where humans and agents collaborate to drive innovation.

workforce transformation

Here are the four biggest takeaways from the event for technical decision-makers. The next time you stop by Lowe’s for a new house plant, supplies to prepare for hurricane season, or a part to fix a bathroom leak, the quantity and in-store location of the product will likely have been influenced by artificial intelligence. There’s also a strategic angle to the acquisition, said Everest Group Managing Partner Rajesh Ranjan.

AI Agents are moving into production, faster than anyone realized

• Manufacturers exploring early AI integrations are already seeing promising gains—in areas like operational speed, forecasting accuracy and decision support—positioning themselves to stay competitive as AI capabilities continue to mature.
• But today’s risks are not static—they’re behavioral, contextual and moment-driven.
• CTOs from Expedia and Kayak discussed how they are adapting to new search paradigms enabled by LLMs.

In finance, that might look like automatically flagging compliance risks, generating real-time audit reports or adjusting cash flow forecasts in response to market shifts. Information security and infrastructure teams should also reassess vendors and review their internal infrastructure to support agentic capabilities, especially those requiring access to more sensitive information. Technology leaders should also review their architecture and assess their technical debt and readiness for integrating AI capabilities. Recent research shows that 92% of manufacturers say outdated infrastructure critically hinders their generative AI initiatives, and fewer than half have conducted a full-scale infrastructure readiness assessment. The organizations that thrive in this new era will be those that use agentic AI not as a magic solution, but as a catalyst within a thoughtful, holistic human risk strategy—one that evolves alongside the threats it aims to defeat.

There is also an increasing trend in agentic AI prioritisation among software executives

Across Intuit’s brands—from TurboTax and QuickBooks to Mailchimp and Credit Karma—GenOS helps create consistent, trusted experiences and ensure robustness, scalability and extensibility across use cases. While long-standing ML-based improvements to Odoo may already feel “old,” they’re far from outdated. Many of these ML-based models have reached a stage of maturity where they consistently deliver value in forecasting, classification and anomaly detection. Organizations that pair agentic AI with the organizational capacity to absorb and act on its insight won’t just operate faster—they’ll operate smarter.

About 93 per cent of organisations are already developing or planning to develop custom AI agents, according to a report by OutSystems, an AI-powered low-code development platform. There is also an increasing trend in agentic AI prioritisation among software executives. Together, these takeaways paint a clear picture of an enterprise AI landscape that is maturing rapidly, moving from broad experimentation to focused, value-driven execution. The conversations at Transform 2025 showed that companies are deploying AI agents today, even if they’ve had to learn tough lessons on the way.

In our work across various manufacturers, we’ve seen projects where AI-powered scheduling, inventory forecasting and advanced automation led to measurable efficiency gains—often in the range of 20% to 30%—while also unlocking new revenue opportunities. These improvements typically required less investment than conventional digital transformation programs and proved easier to scale thanks to agentic AI’s adaptability to existing business rules. With the Atos Polaris AI platform, we are taking the automation of automation to the next level, shifting the paradigm. With the use of fully autonomous agents for software engineering and business processes, agentic AI is indeed positioning itself as a powerful lever for business success. We are particularly proud to make the Atos Polaris AI platform available worldwide and thus help businesses enter the era of agentic AI.