The Rise of Agents

Thank you for reading! Please see “Why 5W?”  for context, methodology and disclaimers.

Agent Overview

The rise of AI-powered agents powered by large language models (LLMs) and generative AI offers transformative potential for a wide range of stakeholders. Businesses, end-users and developers all stand to benefit. For businesses, these agents represent an opportunity to deliver exceptional customer experiences, automate repetitive tasks and deepen engagement. For end-users, they promise unprecedented convenience, enabling them to accomplish complex tasks with simple, conversational inputs. Developers, meanwhile, can leverage this technology to create highly specialized solutions tailored to niche markets or use cases.

Imagine you’re planning a trip. Today, you would navigate separately to an airline site, a hotel booking portal, and a car rental service .. all with separate logins. Or, you can work through an aggregator .. while convenient, potentially introduces other challenges (surcharges, cancellation options, etc.) with the booking.

Tomorrow, an AI-powered agent will streamline this activity, offering a unified interface where you simply describe your needs: “I want to travel from Atlanta to Seattle on February 12th, departing before noon. Please find flights, book a rental car for my arrival, and reserve a room at the Westin in Downtown Seattle for two nights, returning to Atlanta the afternoon of February 14th.” The agent can ask you to clarify preferences (learning along the way) and respond with options based on your plain-language prompt. Further, the Agent will create stickiness for the website, suggesting account and profile creation and storing preferences and payment options from the interaction.

Extend this example to multiple B2C and internal use cases (examples below), all of which eliminate complexity and streamline processes.

AI-powered agents act as intermediaries between users and complex systems, translating natural language inputs into actionable requests. Underpinned by LLMs and generative AI, these agents:

• Understand Context: By analyzing the user’s input, they determine intent and parse details into actionable components.
• Coordinate Across Systems: They interact with multiple APIs or backend systems to gather and process information, presenting options to users or completing tasks autonomously.
• Learn and Personalize: Over time, agents improve by learning user preferences, optimizing recommendations, and tailoring responses.

In the travel booking example, the agent queries airline, hotel, and rental car systems, consolidating data to present options in a coherent format. It eliminates the friction of juggling multiple platforms, freeing up the user’s time and attention.

Business Benefits

AI-powered agents provide businesses with several key advantages:

• Enhanced Efficiency: Automate repetitive and time-consuming tasks, freeing employees to focus on higher-value activities.
• Cost Savings: Reduce operational costs by handling tasks traditionally managed by humans.
• Personalized User Experiences: Tailor interactions to individual preferences, increasing customer satisfaction and loyalty.
• Availability: Operate around the clock, ensuring continuous availability and support.
• Improved Decision-Making: Leverage real-time data and insights to provide accurate and timely responses.

The agent will increase user loyalty, making it the go-to method for completing tasks.

Agent Capabilities

An effective AI-powered agent should be able to execute tasks such as:

• Understanding Complex Requests: Parse and respond to multi-step queries, like planning a trip or managing logistics.
• Providing Contextual Responses: Leverage user history and preferences to deliver personalized solutions.
• Integrating with Systems: Seamlessly connect with various tools, platforms, and APIs to complete tasks.
• Learning and Adapting: Improve over time by analyzing past interactions and feedback.
• Ensuring Data Security: Handle sensitive information responsibly and securely.

Note that the agent does not need to be built to execute these capabilities by itself .. the first integration with the agent will be with underlying LLMs and back-end systems through the use of Application Programming Interfaces (APIs), automation and Web Services.

Agent Use Cases

Use cases for agents are everywhere. Beyond the travel booking sample, the capabilities of engaging through plain-language requests and backend integrations can enable myriad use cases such as:

• Customer Support: Automate responses to FAQs or escalate complex issues to human agents.
• E-Commerce Assistance: Help users find products, compare prices and complete purchases.
• Healthcare Scheduling: Manage appointments, send reminders and answer patient queries.
• HR Onboarding: Guide new employees through onboarding processes, from document submission to training schedules.
• Recruiting: Guide candidates to roles that match their skills and job preferences.

Use your imagination .. what kinds of processes did you execute today? Which processes repeat themselves, only with different data? Which ones lend themselves to agent automation?

Agent Providers

Agent enablement platforms are already here, requiring only integration and agent training. Several companies provide platforms enable businesses to create and deploy AI-powered agents. If a business doesn’t have the skills to do the integration, each of these companies has a robust partner ecosystem to perform these services:

• The OpenAI Platform provides foundational LLMs that power intelligent conversational agents.
• The Google AI Studio offers tools like Dialogflow to create conversational experiences.
• Microsoft Azure AI enables agent development through Azure AI Services.
• IBM Watsonx Assistant for enterprise-grade virtual assistants.
• Salesforce AI that empowers customer service teams with AI-driven interactions.
• ServiceNow offers NowAssist to amplify productivity within an organization.
• Nvidia offers Visual AI Agents for real-time query of video streams

Many, many more partners out there that can enable virtually any use case you can imagine. Please reach out to me if I may assist in platform and partner selection.

Agent Audiences at Target Companies

Some audiences you can consider when you approach companies about deploying AI-powered agents. Note there are many diverse stakeholders within these organizations, including:

• Customer Service Teams will benefit from agents that automate support tasks and enhance customer interactions.
• Sales Departments use agents to qualify leads and handle routine inquiries.
• Operations Managers leverage agents to streamline workflows and improve efficiency.
• IT Departments deploy agents to assist with system queries and troubleshooting as part of their ticketing system.
• Marketing Teams utilize agents to gather customer insights and personalize campaigns.

AI-powered sales agents are my favorite at the moment as a means to extend my Technical Sales Strategy engagements.

An agent seller needs the ability to recognize, expand and document end-customer use cases / need states that enable them to secure a solid prospect. An agent sale will cross multiple audiences, engaging Sales, Marketing, IT, Operations, Developers and Executive audiences.

Conclusion

An agent campaign is a storytelling campaign. It may will likely not begin with a prospect with an enhancement story already in mind. Target audiences need to be guided to consider extensions to their current processes with an agent front-end to facilitate better end-user experiences. Agents are a paradigm shift .. engagements will involve several technical and business audiences, as well as reaching from operations and technical audiences all the way to the executive suite of an organization. Product Owners and Developers will present as useful influencers, but the ultimate decisions must be enabled across the organization.