Miles Ward is the CTO of SADA, An Insight company.
The buzz around AI agents is undeniable. Everywhere you look, there’s a new headline, a new product announcement or another breathless prediction about the future of artificial intelligence. Google, for its part, has been active in introducing the broader “agent space,” providing explanations of the foundational concepts and outlining potential applications. But what truly excites me is moving beyond awareness and demonstrating real-world value.
Beyond ‘Agent Assist’: Defining True AI Agents
Understanding the distinction between “agent assist” and a true AI agent is crucial. “Agent assist” typically involves AI providing information or suggestions to a human user, much like a sophisticated search engine. Think of a chatbot that helps a customer service representative find an answer. While valuable, the human remains responsible for action.
A true AI agent synthesizes requests, accesses information and takes action for the user, often through programmed and LLM-delivered behaviors. It’s not just about text output; it’s about the system performing tasks, reporting completion and continuously learning. This shift from passive information retrieval to active execution is where the transformative business value lies.
Five Ways AI Agents Add Enterprise Value
Based on our work with leading organizations, we’re seeing AI agents provide significant, measurable benefits across these five key categories.
1. Reimagining Software Development
We’re moving beyond simple code completion to a world of accelerated creation and automation, fundamentally changing the building and managing of software. Some enterprises are now experimenting with AI development tools that can generate entire sample applications from a single prompt in seconds.
On a more granular level, organizations are applying AI-driven command-line tools to automate routine but time-consuming tasks such as dependency checks and template deployment.
Teams are also using intelligent coding assistants that suggest functions, tests and refactoring choices directly within their development environments. These applications can save time and money, freeing developers for high-value innovation.
2. Transforming Customer Interaction And Sales Outreach
This is where agents can create an immediately better customer experience. For example, we’re taking real-time sequence data from customer web visits, like someone trying to renew a subscription online.
If a customer runs into trouble and contacts support, an integrated LLM can now summarize their entire journey through the site, giving staff an up-to-the-second view of where the customer got stuck. Instead of generic questions, support agents can open with specifics like, “Hi, it looks like you were trying to renew your subscription online. I can help you with that.”
3. Delivering A Radically Simpler Approach To Application Integration
One of the most persistent—and expensive—challenges in any enterprise is getting disparate systems to talk to each other. An integration project to connect a web app to an ERP system can take months, if you’re lucky.
Agents can now act as a powerful “proxy for integration.” Agents can do the complex data plumbing between systems, handling the nuance of different protocols and data formats automatically. An agent can take data from a customer interaction and automatically create corresponding records in back-office systems, accomplishing in minutes what might have previously taken weeks.
4. Serving As Unbiased Business Advisors
Executives often pay handsome fees for external consultants who, despite their expertise, have their own motives. We worked with a large financial group that wanted to use an agent as a truly objective “second opinion.” They tasked it with generating new approaches to business improvement, analyzing data without preconceptions and offering fresh perspectives on strategic challenges.
Because the agent is inherently yours and working on your behalf, it removes the ulterior motive that can accompany traditional consulting. We even see leaders asking an agent to generate new questions on a monthly basis that they should be asking their teams to spur innovation.
5. Enhancing Discovery, Navigation And Information Synthesis
Enterprise data is fragmented. A single piece of information can live in dashboards, spreadsheets, internal portals and legacy SharePoint sites. The cost of consolidation is often high, but an agent can be pointed at all the structured and unstructured sources and provide a unified search and synthesis interface.
An HR department, for example, can stop spending all of its time explaining HR policies by pointing an agent at the documentation and letting it answer employee questions directly. This is especially powerful in complex domains like security, where agents are being built to help teams identify attack patterns in real time.
The Road Ahead: Overcoming Implementation Challenges
Foundational challenges exist. Senior IT leaders sometimes assume these tools are only cloud-based, but lightweight local models can now be installed on individual machines in minutes without requiring cloud data transfer. Tools evolve faster than institutional knowledge, requiring enterprises to bridge this gap. While valuable, deploying AI agents in production requires considerations.
• Cost Models And Scalability: The cost efficiency of user-initiated prompts versus high-volume production agents differs significantly. For an agent handling millions of transactions, fine-tuning for cost efficiency, performance and reliability is paramount, often requiring specialized tools.
• Data Readiness And Infrastructure: The success of AI agents hinges on the accuracy and robustness of underlying data systems and secure infrastructure. Many companies need assistance with AI prerequisites: clean, accessible data, standardized testing and validated authentication/authorization.
• Organizational Mindset: A fundamental shift is required for many organizations to view themselves, even outside of traditional IT departments, as “development teams” capable of building and managing these agents. Leaders must be prepared for radically disparate levels of familiarity and capabilities with creative, powerful tools of this type and work to coach every role, no matter how far from “tech” they seem, to capture the value being created via AI.
The era of AI agents is not a distant future; it is here, delivering tangible business value across diverse industries today. Enterprises can now go beyond the hype and truly unlock AI’s transformative power. It’s all about focusing on practical applications, developing domain expertise and tackling implementation challenges head-on.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?