University of Kwazulu-Natal

Ai At Scale How 2025 Set The Stage For Agent Driven Enterprise

Bonisiwe Shabane
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ai at scale how 2025 set the stage for agent driven enterprise

NEW YORK, NY – Jan. 15, 2026 – Insights from the KPMG Q4 AI Pulse Survey reveal business leader priorities that will drive agents into the enterprise in 2026, led by continued investment in the technology and critical foundations,... As AI cements itself as a recession-proof investment, business leaders are demonstrating unwavering commitment: 67% say they will maintain spending even if a recession occurs in the next 12 months, with a projected $124... Expectations on ROI continue to hover at similar figures quarter-over-quarter, with 59% expecting to see measurable ROI within that same timeframe. “AI isn’t just an investment, it’s becoming the backbone of enterprise strategy,” said Steve Chase, Vice Chair of AI and Digital Innovation at KPMG LLP. “What the numbers don’t show is the growing divide: while some organizations stall after early deployments, the leaders are scaling fast and pulling ahead.

For those treating AI as a true disruptor, this isn’t about catching the next wave; it’s about agents fundamentally changing how value is created and sustained across the enterprise.” 2026: The Year Agents Move to Professionalized, Orchestrated Systems While the survey found a reported decline in agent deployment at 26% (down from 42% in Q3), that number is more than double the 11% reported in Q1 and does not reflect the reality... In our client work and at KPMG, we see the opposite trend: leaders have moved beyond initial deployments and are professionalizing and preparing to scale agent systems – readying data, investing in infrastructure, and... AI transformation only succeeds beyond the pilot phase Image: Unsplash/Jo Lin The true winners of the AI era will be businesses that master both innovation and operations.

As firms and organizations across sectors dive headfirst into their transformation journeys, a significant gap persists between artificial intelligence (AI) incubation and adoption in production. To come out ahead, leaders will need to bridge this divide, translating AI's immense capabilities into real world benefits for employees, customers and society. At Rakuten, we've formalized our approach to AI transformation through what we call "AI-nization." AI-nization is about more than implementing AI tools or automating tasks; it's a fundamental cultural and operational shift, systematically embedding... To guide this AI transformation and ensure our AI initiatives are intelligent, efficient, ethical and productive, we developed a framework of “Eight Drivers of AI-nization.” These drivers provide a structured, actionable roadmap that I... This report is a collaborative effort by Alexander Sukharevsky, Dave Kerr, Klemens Hjartar, Lari Hämäläinen, Stéphane Bout, and Vito Di Leo, with Guillaume Dagorret, representing views from QuantumBlack, AI by McKinsey and McKinsey Technology. We’re at a moment when gen AI has entered every boardroom, but for many enterprises, it still lingers at the edges of actual impact.

Many CEOs have greenlit experiments, spun up copilots, and created promising prototypes, but only a handful have seen the needle move on revenue or impact. This report gets to the heart of that paradox: broad adoption with limited return. The current diagnosis is this: Today, AI is bolted on. But to deliver real impact, it must be integrated into core processes, becoming a catalyst for business transformation rather than a sidecar tool. Most deployments today use AI in a shallow way—as an assistant that sits alongside existing workflows and processes—rather than as a deeply integrated, engaged, and powerful agent of transformation. Agentic AI is the catalyst that can make this transition possible, but doing so requires a strategy and a plan to successfully power that transformation.

Agents are not simply magical plug-n-play pieces. They must work across systems, reason through ambiguity, and interact with people—not just as tools, but as collaborators. That means CEOs must ask different questions: not “How do we add AI?” but “How do we want decisions to be made, work to flow, and humans to engage in an environment where software... Redefining how decisions are made, how work is done, and how humans engage with technology requires alignment across goals, tools, and people. That alignment can only happen when openness, transparency, and control are central to your technology and implementation—when builders have an open, extensible, and observable infrastructure and users can easily craft and use agents with... That alignment creates the trust and effectiveness that is the currency of scalable transformation that delivers results rather than regrets.

Deloitte Insights and our research centers deliver proprietary research designed to help organizations turn their aspirations into action. For personalized content and settings, go to your My Deloitte Dashboard Stay informed on the issues impacting your business with Deloitte's live webcast series. Gain valuable insights and practical knowledge from our specialists while earning CPE credits. Stay informed with content built for today’s business leaders. From data visualizations to expert commentary, our video content delivers concise, actionable information to help you lead with clarity in a complex world.

Looking to stay on top of the latest news and trends? With MyDeloitte you'll never miss out on the information you need to lead. Simply link your email or social profile and select the newsletters and alerts that matter most to you. Capturing the full potential of agents will require modernizing enterprise architecture. By Pascal Gautheron, Chris Bell, and Stephen Hardy This article is part of Bain’s Technology Report 2025

Agentic AI isn’t just another wave of automation; it’s a structural shift in enterprise technology, one with the potential to completely redefine how work gets done. Previous waves of automation tackled parts of processes, leaving exceptions where humans had to step in. AI agents can reason, collaborate, and coordinate actions, allowing them to accomplish complex, multistep, nondeterministic processes that have so far depended on humans. It’s easy to see the transformative potential of this, from improved operational efficiency and customer experience to sharper decision making and beyond. Forward-looking leaders aren’t asking if agentic AI will reshape their business but how to prepare their organizations to deploy it safely and effectively. "2025 will be the year of the AI agent." Wait — didn’t we already say that in 2023?

Back then, I talked about chaining AI models in my podcast. The excitement around AI was huge, and by 2024, many companies rushed to try generative AI, with some even using chained models. But many of these projects failed to scale. Why? Because they were test projects that were not integrated into the system infrastructure or were missing guardrails and quality controls. This will change in 2025, but the product challenges will remain the same.

To see what AI agents can do in 2025, let’s consider a simple example: an email-answering tool. Imagine a system that drafts replies to emails automatically. This example shows the opportunities and challenges businesses face with AI agents. The simplest way to build an email-answering tool is with a GPT wrapper. I saw many of these in 2024. These are basic setups where you connect AI to a small interface.

For our use case, this means getting a ChatGPT API key, writing some code to take an email as input, adding a prompt telling the AI what to do, and displaying the response in... Even in this simple example, several key challenges emerge for enterprise AI today: Large language models are excellent at tasks like summarization or acting as interfaces, but alone they are not enough. As I emphasize in my eCornell certificate program, each of these challenges can be addressed. Let’s improve our tool by building AI agents within a workflow. AI models can be connected or "chained" to build workflows where the output of one model becomes the input for the next.

Think of tools like Zapier or IFTTT, but powered by AI. Instead of fixed steps, the process is dynamic and adapts to each situation. These workflows don’t always rely on generative AI like ChatGPT. In fact, they often don’t—generative AI can be too slow and expensive. Stay ahead with BCG insights on artificial intelligence Manage Subscriptions AI is transforming the way work gets done, but it hasn’t fundamentally altered the way most companies operate—yet.

We are entering the era of AI agents. While previous waves of AI focused either on logic and optimization or creativity and synthesis—the “left brain” and “right brain” of predictive AI and generative AI, respectively—the next wave will involve agentic systems that... (See the sidebar “The Frontal Cortex of AI.”) Early adopters are already showing what this looks like in practice: Results like these are spurring rapid investment across industries. In a recent BCG study with MIT Sloan Management Review, 35% of organizations said they are already using agentic AI, and another 44% said they plan to do so soon.

That same research found that three-quarters of extensive adopters believe AI is now enabling new sources of value and competitive advantage. “AI isn’t just an investment, it’s becoming the backbone of enterprise strategy,” said Steve Chase, Vice Chair of AI and Digital Innovation at KPMG LLP. “What the numbers don’t show is the growing divide: while some organizations stall after early deployments, the leaders are scaling fast and pulling ahead. For those treating AI as a true disruptor, this isn’t about catching the next wave; it’s about agents fundamentally changing how value is created and sustained across the enterprise.” https://lnkd.in/eXP7tq-e Agentic AI isn’t a future experiment anymore. It’s here, its scaling, and it’s rewriting enterprise playbooks.AI agents are embedded in enterprise workflows from customer support and cybersecurity to software engineering.

Recent surveys show 50%+ of enterprises have already deployed agents, and 62% expect >100% ROI in the next two years. The opportunity is clear. But there’s a paradox: while agentic AI promises autonomy and efficiency, adopting it without guardrails risks fragmented adoption, compliance gaps, or brittle architectures. Those that prepare systematically can unlock compounding gains in efficiency, resilience, and competitive advantage. As enterprises move toward the agent-driven future, this blog provides a pragmatic 2025 checklist for leaders to evaluate readiness, guide adoption, and build the right governance for scaling Agentic AI. The implication is clear: fragmented pilots won’t cut it.

The winners will be enterprises that treat agents as systems, not just tools – with integration, scalability, and governance as the new battlegrounds.

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