Without clear controls and ongoing evaluation, AI agents can quickly introduce compliance, brand, and operational risks. Effective management of AI agents in B2B go-to-market (GTM) contexts requires a structured approach that treats agents as autonomous actors with defined roles, responsibilities, and governance to ensure operational success, compliance, and value creation. In this report, we introduce the Forrester B2B AI Agent Lifecycle Framework to help GTM leaders operationalize successful agent management from experimentation to production to decommissioning based on outputs or evolving business priorities.

AI has evolved from discrete features and tools to a core force reshaping how B2B organizations engage customers, qualify demand, and create value throughout the customer lifecycle. Companies must align technology investments with human capabilities and reskilling to maximize AI’s business impact and address the challenges and opportunities presented by generative and agentic AI. The Forrester Human-AI Calibration Model provides guidance for a human-first, AI-native strategy that harmonizes agency, adaptability, and authenticity.

As AI search disrupts how buyers discover, evaluate, and engage with brands, marketing leaders must evolve their strategies beyond traditional search engine optimization (SEO). Answer engine optimization (AEO), also known as generative engine optimization (GEO) or AI search optimization (AISO), is now vital to ensure your brand is visible, credible, and influential in AI-generated answers. This assessment helps you benchmark and improve your organization’s ability to compete in this new era of AI search.

Delivering AI capabilities that consistently generate business value requires more than technology. It requires strategic alignment, organizational readiness, and the operational discipline to scale responsibly. Use this assessment to drive strategic discussions and evaluate the current state of AI proficiency within your B2B go-to-market (GTM) teams across three core dimensions and nine categories. Your results will map to one of six profiles, each reflecting a distinct pattern of strengths, opportunities, and priorities, and include a customized set of recommended actions to help you move forward with clarity and intention.

Join Forrester and your peers to learn how companies are deploying AI agents across go-to-market processes. In this session, we'll discuss how go-to-market teams are participating in developing an agent strategy, the current state of agent adoption and top use cases, and challenges go-to-market functions are facing in onboarding and training AI agents. This conversation will be hosted by Jessie Johnson and Katie Linford and will include open discussion with participants, so please bring your questions and experiences to share with the group. Questions for discussion:Which AI agent use cases have successfully made it into pilot or production inside your organization? Build vs. buy — Are the most successful AI agent deployments coming from internal development or from vendor capabilities? What are the top internal challenges, and how have your peers had success in tackling them? How has the work changed with AI agent augmentation? Peer discussions are available exclusively to Forrester Decisions VIP Leader and Leader license holders for their own participation.

AI has long been embedded in the B2B tech stack and go-to-market workflows. The sudden ubiquity of generative AI and, now, the promise of agentic AI have catalyzed rapid, intensive change — and driven the need for a harmonious human-AI coexistence.

AI agents have the potential to reshape B2B marketing through accelerated decision-making, real-time orchestration of complex workflows, and personalized engagement at scale. Although adoption intent is high, success hinges on the alignment of AI agents to strategic initiatives and upfront planning. It requires defining AI agent goals and responsibilities, data sources, interoperability requirements, and ongoing training while building trust through transparency, education, and reskilling. This report outlines key considerations for deploying AI agents intentionally and effectively to drive innovation, scale, and measurable business impact across B2B marketing functions.

Digital content will continue to be shaped by enterprises both investing in and looking to gain practical business value from genAI solutions. Here’s how we foresee digital content evolving.

Goal-oriented, self-improving AI agents purpose-built for B2B buying and selling will soon impact every interaction during the purchasing journey and postsale experience. AI agents for B2B marketing and sales broadly align to seven archetypes, each tailored to specific business contexts, audience needs, interaction scenarios, and training data and tooling requirements. This report describes the AI agent archetypes augmenting B2B marketing and sales teams now and in the future and includes considerations for leveraging and coordinating those agents for go-to-market (GTM) use cases.

A consistent and thoughtful approach to AI agent creation, customization, and instruction is required to translate business logic into agent outcomes. B2B organizations need a scalable way to activate, instruct, ground, and ensure continuous learning and optimization of AI agents as they continue to proliferate. In this report, we describe how to use the B2B AI-Agent-On-A-Page Template For Go-To-Market Teams to guide the planning and activation of AI agents across go-to-market (GTM) functions, roles, and use cases.