Explore how to leverage AI agents for genuine business transformation
AI agentic systems are evolving faster than any technology in recent memory. Mastering them requires robust data infrastructure, clear ROI metrics, security and trust, and a forward-looking operating model. Organizations that start now will be best positioned to leverage AI agents for genuine business transformation.
While AI agents do boost productivity, they are increasingly viewed as catalysts for tangible ROI and market disruption. AI agents can help you deliver value.
At a recent Wall Street Journal CIO Network Summit,1 67 percent of attendees indicated they’re actively piloting or deploying AI agents. In a poll conducted at roughly the same time by Salesforce, 93 percent of enterprise IT leaders said they have implemented or plan to implement AI agents in the next two years.2 This remarkable rise underscores how AI has shifted from a speculative technology to near-mainstream in under two years.
AI agents are often described as a paradigm shift in AI. They move AI from passive information retrieval to proactive execution and decisionmaking. They possess higher levels of autonomy and intelligence, enabling them to adapt and optimize their actions in response to changes in their environment.3 AI agentic systems are evolving rapidly, moving from simple “taskers” designed to automate single functions to “orchestrators” where multiple AI agents interact to achieve complex tasks at scale. They can operate across different domains—for example, in healthcare they reduce administrative overhead, while in financial services they help optimize complex trading strategies—demonstrating true cross-industry applicability.
We would argue, however, that the paradigm shift lies not just in AI, but in IT as whole. AI agents are forcing IT to reinvent itself. We would even go so far as to say AI could fundamentally challenge of the software-as-a-service (SaaS) model.
Consider the impact of such a shift on your IT organization and your business as a whole. Over the last two decades or so, your IT organization’s operating model—its technologies, processes, people, performance measures, and security and governance models—has likely been built and optimized around SaaS, and business strategies and business models have been built upon those capabilities. AI agents are now threatening to undermine that foundation entirely.
History offers many lessons, and the disruptive effects of cloud based technologies hint at the potential impact of AI agents. Many of the world’s most valuable companies today either were transformed by the cloud model or were forward-thinking and agile enough to pivot to it, often with radical shifts to their business models and the underlying IT operating models required to enable them—Microsoft, Oracle, and Apple come to mind. And of course, there are many well-known companies that failed to adapt, clinging onto their existing business models until the bitter end.
For most, adapting to the world of AI agentic systems will be an evolutionary process. Inertia is a powerful force, and turning the enterprise ship can take time. Just understanding the full transformative potential of something as disruptive as AI agents can be challenging without a clear roadmap examples.
Today, with AI agents, many still appear to be in the “lift-and-shift” phase, where the only question being asked is, “how can I take advantage of this technology to improve what I do but without fundamentally changing what I do?” In fact, recent surveys show that while more than 80 percent of enterprises have piloted AI to boost productivity, fewer than 30 percent report having reengineered processes or business models around AI. Many organizations have limited their use of AI to private large language models (LLMs) or embedded AI features within major platforms. AI agentic systems have yet to be widely embraced as an enabler of business transformation or a catalyst for entirely new business models that can redefine product or service offerings, disrupt markets, and solve sectorwide challenges.
But pressure is mounting to change that. 75 percent of attendees polled at the recent Wall Street Journal CIO Summit said they believe AI is currently driving a small amount of value for their investments, but not enough.4 CIOs are hearing from their boards and CEOs, “We need transformative value, not just incremental efficiency gains.” AI agents are the answer.
For most, adapting to the world of AI agentic systems will be an evolutionary process. Inertia is a powerful force, and turning the enterprise ship can take time.
PHASE 1: Measure your AI readiness First, measure your AI readiness. Conduct both an outside-in (i.e., market research) and insideout (i.e., data collection) analysis on AI-relevant domains, including strategies, data and technologies, trust and governance, workforce skills, project management, and value tracking. Identify gaps and develop a plan to address them. For instance, form a cross-functional committee—IT, Legal, Compliance, and HR—to evaluate your data posture, AI maturity, and organizational readiness for agentic solutions.
PHASE 2: Conduct a comprehensive opportunity assessment Next, conduct a comprehensive opportunity assessment. Outline use cases for AI, and prioritize those use cases based on risk, value, and complexity. The goal is to have a prioritized roadmap for use-case implementation complete with ROI metrics. Consider starting with “low-hanging fruit”—e.g., chat-based employee support or automated financial reconciliation—then expand to more disruptive, crossfunctional initiatives once initial successes are proven.
PHASE 3: Implement an AI operating model designed for value, scalability, and sustainability Finally, implement an AI operating model designed for value, scalability, and sustainability—the foundation you’ll need to integrate AI agents, foster innovation, and develop a competitive edge:
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Just as the cloud forced IT to transform from an organization designed to maintain on-premise servers, AI agents are now challenging existing models and forcing another reinvention. This disruption is accelerating far faster than previous technology shifts, making it critical to initiate your transformation immediately.
In the next 12 to 18 months, we’ll see AI agentic systems expand into multimodal capabilities (e.g., combining text, images, and speech). Moreover, we can expect a continued evolution of regulatory frameworks. By preparing now—aligning IT strategy, data governance, security, and talent—you’ll be ready to capitalize on upcoming breakthroughs rather than scramble to catch up.
For a deeper dive into AI readiness, ask us about our “AI Agent Roadmap Toolkit,” which provides a step-by-step guide—from data strategy to ethical AI governance—to help you jumpstart adoption.
1 Belle Lin, “AI Agents Are Everywhere…and Nowhere,” The Wall Street Journal, February 12, 2025.
2 “Integration Key as 93% of IT Leaders Turn to AI Agents Amid Soaring Resource Demands – New Research,” Salesforce, January 29, 2025.
3 AgentLayer, “The Rise of AI Agents and the Evolution of Innovation in AgentLayer,” Medium, March 3, 2024
4 Belle Lin, “AI Agents Are Everywhere…and Nowhere,” The Wall Street Journal, February 12, 2025.
