Despite all the investments that businesses have made in AI, most organizations are nowhere close to AI maturity. Just 1% of business leaders say their companies have fully integrated AI into workflows and used AI to drive substantial business outcomes, according to McKinsey industry research. Part of the challenge is that AI itself is experimental and continuously evolving.
But most businesses also struggle to implement and sustain the organizational change necessary to support AI maturity. This perpetual shortcoming is expected to increasingly stand in the way of achieving AI maturity.
The latest generation of AI—known as agentic AI—refers to AI that generates original content by identifying patterns in existing data. Unlike more established forms of AI, agentic AI doesn’t require constant human input. Agentic AI can think, learn, and act on its own. Unfortunately, it is agentic AI’s powerful capabilities that present barriers to AI maturity for most businesses—especially for businesses that don’t come prepared.
Businesses need to make strategically important changes and updates to how they think and operate if they truly want to take advantage of agentic AI.
Let’s explore four key organizational changes that every business should be making when investing in agentic AI:
Prioritize vertical use cases for agentic AI
Traditionally, businesses tend to implement AI horizontally across the organization—meaning a finite set of AI features and functionalities are adapted for different uses across the organization. While horizontal integration of AI has been successful at enhancing individual productivity (such as streamlining and automating time-consuming tasks), horizontal integration typically only targets individual steps of workflows—not business processes as a whole. As a result, businesses often struggle to drive bottom-line value from horizontal AI integration.
Read More: 5 Reasons Organizations Are Replacing GenAI With Agentic AI
By contrast, vertical AI integration is much more likely to unlock AI’s value—particularly when it comes to agentic AI. Vertical AI integration refers to holistically integrating AI into overarching business functions, such as marketing or sales or IT or HR. Agentic AI in particular is highly effective at integrating and synthesizing disparate processes, technologies, and people. In fact, it is precisely this capability of agentic AI—which is unique to agentic AI—that enables the technology to consistently drive bottom-line value from vertical AI integration.
Unify siloed AI initiatives and teams
Because of the fast and uneven pace at which AI advances have been unfolding, businesses have struggled to engage in any meaningful strategic planning around AI. Teams tend to operate in silos, and to pursue AI initiatives independently from one another and from central decision-making centers. As a result, businesses commonly struggle with poor AI integration, fragmented data pipelines, and misalignment of strategy and goals for AI.
While these challenges have long been barriers to the success of all AI investments, these issues will be particularly problematic as organizations begin investing in agentic AI. Agentic AI works most effectively when it’s not being encumbered by siloing and fragmentation—but rather has free reign to look holistically at entire workflows and business ecosystems.
Establish governance for AI agents
Until the advent of agentic AI, AI lacked many of the hallmark features of human intelligence. The difference with older forms of AI, including generative AI, is that they operate largely reactively, in response to human prompts and human guidance. Moreover, older AI technologies are generally unable to retain memory of their past interactions. Consequently, they cannot fully absorb and contextualize information they’ve been exposed to across multiple sessions and queries.
Read More: Understanding AI Agents Beyond The Hype
Agentic AI is the complete opposite. Agentic AI relies on the use of support agents, which are deployed specifically to absorb, synthesize, contextualize, and learn over time with virtually no human guidance or prompting. Against the backdrop of this fundamentally different operating environment, businesses need strong governance policies and practices to manage the potential risks associated with deploying AI support agents. Human teams should not be discussing if, when, or how to deploy AI agents until they’ve established robust governance for these agents.
Lay the groundwork for both custom and off-the-shelf AI agents
Agentic AI is still so new that most businesses are still figuring out what are appropriate vs. inappropriate use cases for AI support agents. Among the key questions that businesses are asking is whether they should invest in only custom-built AI agents, which provide maximum control, or be open to off-the-shelf AI agents, which saves time and money.
The general answer is that businesses should be laying the groundwork to integrate both types of AI agents, and to enable these agents to freely interact with one another. Known as the agentic AI mesh, this novel AI operating environment gives organizations the flexibility they need to take full advantage of their AI agents. Moreover, the flexibility to choose custom vs. off-the-shelf AI agents engenders trust in AI, both among teams that are preparing AI agents for deployment and among teams that are the intended end users of these tools. Flexibility also lowers barriers for AI agents themselves to operate freely within the business’s ecosystem.
Final thoughts
Organizational change rarely comes easy, and the changes that are needed to support agentic AI are no exception. But achieving these changes is essential for unlocking agentic AI’s full potential. The key organizational changes that every business should prioritize implementing include prioritizing vertical AI integration instead of horizontal integration, unifying siloed AI initiatives and teams, establishing governance for agentic AI support agents, and paving the way for the organization to implement both custom and off-the-shelf AI agents.
To learn more about planning for and managing the organizational changes that should accompany agentic AI integration, please reach out to the agentic AI experts at Fullcast. We’d be happy to help you assess where you’re at, develop plans for implementing necessary organizational change, and then implement and sustain these changes to benefit fully from agentic AI.
