The New Enterprise Frontier: AI Reasoning and Agentic AI

While we sit in an enterprise culture enraptured by AI, it is hard not to think about what’s next. With some leaders comparing the early dawn of AI to the birth of the internet, there is significant hope that AI will continue to grow and benefit business and society through future innovations.

Even at this early stage in the technology’s development, among companies that have adopted AI/machine learning technologies, Forrester found that 74% have reported a positive impact.

This is all, of course, tempered by the fact that growing pains will continue, as will regulatory concerns. As seen recently in California after the veto of the AI safety bill, the core issue is not AI models themselves, but rather the potential impact on innovation they could cause. Shifting the focus away from the technology itself, and instead toward the safe and ethical use of it, provides a better mindset for embracing best practices.

As much as generative AI (GenAI) has been the buzz in the business world, some organizations are still struggling to see real value in their investments. The emerging field of agentic AI goes beyond GenAI’s traditional system of request and response. Its promise lies in the ability for “agents” to accomplish real work by reasoning through a user’s query, autonomously developing and executing a set of tasks while intuitively calling on all the necessary tools to do so. Let’s delve deeper into the future of AI, including the data, that will drive the performance of agentic AI in the enterprise.

FIRST THINGS FIRST: ALL FORMS OF AI MUST HAVE A STRONG FOUNDATION

Where and when to implement any type of AI comes down to the following: 1) a thorough review and prioritization of business use cases and 2) an exceptional data foundation.

There are compelling reasons to use AI in many areas of business, from business intelligence (BI) and fraud management to customer relationship management (CRM) and content production.

What organizations can do today to prepare for an AI future that is yet to be written is to put a hyperfocus on data integrity. It’s virtually a riskless investment: Regardless of the future form AI takes, it will rely heavily on the data on which it sits. When establishing a reliable data foundation, there are six core qualities. Data needs to be diverse, timely, accurate, secure, discoverable, and consumable. The steps an organization needs to take for each of these components vary depending on where they are on their data journey; however, this is a good short-list reference on what is required of data to feed reliable AI.

Along with a solid data foundation, an organization that successfully implements AI programs is one that also puts an emphasis on strong governance and fueling a culture of innovation. From a change management perspective, neither one of these is easy. However, it is the best way to move AI initiatives forward, grow new competencies, and ensure safety for all throughout it.

MOVING PAST CURRENT MINDSETS: AI CAN BE MORE THAN A TOOL IN THE ENTERPRISE

The idea that AI can be more than a tool in the enterprise, as the next-gen thinking of agentic AI lays out, indicates the future is unfolding before us. It is an innovative new way to leverage large language models, pulling them out of the strict request-and-response role that currently defines GenAI and making them more operational. Forrester reported that AI agents are now leveraging advanced language models to perform complex tasks, make decisions, and interact autonomously on behalf of enterprises or individuals. Where it gets really exciting is the possibility of multiple agents working together to pursue more value-rich outcomes for an organization—an illustrative digital factory of the future.

Implementing and scaling agentic AI in the enterprise won’t happen overnight, which is similar to what some organizations have endured in their pursuit of GenAI. However, Forrester’s Top 10 Emerging Technologies for 2024 reports that agentic AI is the most exciting development reflected on its list because it promises more sophisticated, and less brittle, automation capabilities. It is also a major factor in the evolution and emergence of other important technologies.

This underscores the importance of being proactive in creating a foundation ready to handle all forms of AI, some of which are yet to be created.

EMBRACING WHAT’S NEXT

There is a future beyond the hype of GenAI for those that embrace it (and even those who choose not to). The organizations that equip themselves to harness all forms of AI—through a solid data foundation, strong governance, and a culture of innovation—will be those that thrive well into the future.