Create an Onboarding Plan for AI AgentsSKIP TO CONTENTHarvard Business Review LogoHarvard Business Review LogoGenerative AI|Create an Onboarding Plan for AI AgentsSubscribeSign InLatestMagazineTopicsPodcastsStoreReading ListsData & VisualsCase SelectionsHBR ExecutiveSearch hbr.orgSubscribeLatestPodcastsThe MagazineStoreWebinarsNewslettersAll TopicsReading ListsData & VisualsCase SelectionsHBR ExecutiveMy LibraryAccount SettingsSign InExplore HBRLatestThe MagazinePodcastsStoreWebinarsNewslettersPopular TopicsManaging YourselfLeadershipStrategyManaging TeamsGenderInnovationWork-life BalanceAll TopicsFor SubscribersReading ListsData & VisualsCase SelectionsHBR ExecutiveSubscribeMy AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesSign InHarvard Business Review LogoGenerative AICreate an Onboarding Plan for AI Agents by Joseph FullerMarch 25, 2026J Studios/Getty ImagesPostPostShareSavePrintSummary.   Leer en españolLer em portuguêsPostPostShareSavePrintMost executives believe that the big challenge in adopting agentic AI is figuring out how to adapt to a new and important technology. But in fact it’s primarily about managing work.Joseph Fuller is a professor of management practice and a faculty cochair of the Project on Managing the Future of Work at Harvard Business School.PostPostShareSavePrintRead more on Generative AI or related topics Leading teams, Teams, Human resource management, Employee engagement, Talent management, Organizational development, Organizational change, Organizational restructuring, Organizational transformation, Cross-functional management, Managerial behavior, AI and machine learning and AlgorithmsPartner CenterStart my subscription!Explore HBRThe LatestAll TopicsMagazine ArchiveReading ListsCase SelectionsHBR ExecutivePodcastsWebinarsData & VisualsMy LibraryNewslettersHBR PressHBR StoreArticle ReprintsBooksCasesCollectionsMagazine IssuesHBR Guide SeriesHBR 20-Minute ManagersHBR Emotional Intelligence SeriesHBR Must ReadsToolsAbout HBRContact UsAdvertise with UsInformation for Booksellers/RetailersMastheadGlobal EditionsMedia InquiriesGuidelines for AuthorsHBR Analytic ServicesCopyright PermissionsAccessibilityDigital AccessibilityManage My AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesHelp CenterContact Customer ServiceExplore HBRThe LatestAll TopicsMagazine ArchiveReading ListsCase SelectionsHBR ExecutivePodcastsWebinarsData & VisualsMy LibraryNewslettersHBR PressHBR StoreArticle ReprintsBooksCasesCollectionsMagazine IssuesHBR Guide SeriesHBR 20-Minute ManagersHBR Emotional Intelligence SeriesHBR Must ReadsToolsAbout HBRContact UsAdvertise with UsInformation for Booksellers/RetailersMastheadGlobal EditionsMedia InquiriesGuidelines for AuthorsHBR Analytic ServicesCopyright PermissionsAccessibilityDigital AccessibilityManage My AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesHelp CenterContact Customer ServiceFollow HBRFacebookX Corp.LinkedInInstagramYour NewsreaderHarvard Business Review LogoAbout UsCareersPrivacy PolicyCookie PolicyCopyright InformationTrademark PolicyTerms of UseHarvard Business Publishing:Higher EducationCorporate LearningHarvard Business ReviewHarvard Business SchoolCopyright ©2026 Harvard Business School Publishing. All rights reserved. Harvard Business Publishing is an affiliate of Harvard Business School.

The core challenge in the widespread adoption of agentic AI, according to Joseph Fuller, isn’t primarily a technological adjustment but rather a shift in how organizations manage their work processes and human resources. Fuller, a professor of management practice and a faculty cochair of the Project on Managing the Future of Work at Harvard Business School, posits that executives often misdiagnose the issue by focusing on adapting to a new technology itself, neglecting the fundamental managerial implications. The article emphasizes that the true hurdle lies in effectively integrating AI agents into existing workflows and teams, requiring a deliberate and structured approach to ensure success.

The proposed onboarding plan centers around this managerial focus, suggesting a phased implementation strategy rather than a rapid, disruptive rollout. The initial phase involves defining clear objectives for agentic AI – what specific tasks will these agents perform, and what outcomes are expected. This requires detailed assessment of current workflows to identify areas where AI can augment, not replace, human capabilities. It’s crucial to establish metrics for success, ensuring alignment between AI goals and overall business strategy, and to communicate these objectives transparently to all stakeholders.

Subsequently, the plan advocates for structured training and skill development. Employees will need to learn how to interact with and manage these AI agents effectively. This extends beyond basic operation to include understanding the agent’s limitations, recognizing potential biases in its outputs, and exercising critical judgment when applying its recommendations. The training should emphasize collaboration between humans and AI, fostering a symbiotic relationship where each leverages their respective strengths. A key element is upskilling, equipping teams with the abilities to oversee, refine, and improve the AI’s performance over time, moving beyond pure operational tasks.

A critical component of the onboarding process, highlighted by Fuller, is establishing clear governance and accountability structures. Defining roles and responsibilities for managing AI agents – who is responsible for monitoring their performance, addressing issues, and ensuring ethical use – is paramount. This includes establishing processes for handling disagreements between human judgment and AI recommendations and creating mechanisms for audit and oversight to prevent unintended consequences. Furthermore, the plan stresses importance on continuously monitoring the impact of the AI agents on the workforce, paying attention to changes in job roles, skill requirements, and team dynamics.

The article implicitly suggests a longer-term iterative model of onboarded change. The implementation is described as a series of phases, beginning with small-scale pilot projects to test the concept and refine the approach. As learnings from these pilots are gathered, the strategy can be scaled up while continually adapting to ensure the agents remain aligned with evolving business needs. This phase-wise integration minimizes disruption, reduces risk, and allows for a more controlled, data-driven optimization of AI deployment.

Ultimately, Fuller’s perspective underscores a shift in thinking – moving beyond viewing agentic AI as a technological marvel and instead recognizing it as a significant operational challenge that demands careful planning, skilled management, and a commitment to continuous improvement. It’s a process of managing the human-computer relationship within an organization, not just integrating a new tool.