HBR Guide to Generative AI for Managers

1. Generative AI: From Tools to Collaborative Partners

With the advent of generative AI models, managers can talk with machines in natural language, asking them to collaborate on tasks and engage in conversations.

Evolution of machines. Historically, machines served as tools, automating tasks and streamlining processes, but creativity and strategic thinking remained human domains. The introduction of AI virtual assistants marked a transitional phase, allowing simple natural language interactions, though often feeling robotic and limited. This era set the stage for a more profound shift.

The game-changer. OpenAI's ChatGPT, launched in November 2022, revolutionized human-AI interaction by offering a truly conversational interface. This made AI accessible to everyone, regardless of coding skills, enabling fluid, human-like dialogues. Its rapid adoption underscored a fundamental change: machines were no longer just enablers but potential partners.

New paradigm. Generative AI ushers in an era where machines become collaborators, capable of understanding and generating diverse content (text, images, audio, code). This symbiotic relationship means AI can now assist managers across a wide spectrum of tasks, from routine operations to complex problem-solving, fundamentally transforming how work is done.

2. Mastering Gen AI: The Co-Pilot and Co-Thinker Modes

Co-Thinking represents a process done together, as the “co” implies, where human and AI intertwine.

Co-Pilot for execution. In Co-Pilot mode, generative AI acts as an efficient assistant, handling administrative, communication, and operational tasks. Managers provide clear prompts, and AI executes, drafting emails, summarizing documents, or creating slides. The manager's role is to provide initial direction, then review and validate the AI's output, ensuring accuracy and quality.

• Prompting is key: Be precise, contextual, specify format, give examples, set boundaries, and don't hesitate to ask AI for help in crafting prompts.
• Not autopilot: Always verify AI-generated content to avoid fabrications or hallucinations.

Co-Thinker for strategy. In Co-Thinker mode, AI becomes a thought partner, engaging in deep, reflective dialogue to aid strategic thinking and problem-solving. This involves a back-and-forth exchange where both human and AI contribute ideas, challenge assumptions, and build upon each other's inputs.

• Preparation is crucial: Assign AI a specific role (e.g., mentor, devil's advocate), define the setting (one-to-one, one-to-many), outline the dialogue flow, and then create a structured prompt.
• Focus on reflection: Unlike Co-Pilot's speed, Co-Thinker emphasizes thoughtful conversation, encouraging pauses and deeper analysis.

Blended interaction. These two modes are not mutually exclusive; they can be used sequentially. For instance, a manager might use AI as a Co-Thinker to brainstorm a strategy, then switch to Co-Pilot to draft a memo summarizing the discussion. This dynamic interplay optimizes both efficiency and strategic depth.

3. Cultivating the Essential Gen AI Mindset

Your mindset lies at the center of every transformation and influences how you perceive, embrace, and adapt to change.

Conversational approach. Generative AI's ability to engage in natural language conversations demands a shift in mindset: treat it as a knowledgeable partner, not just a tool. This means providing clear instructions, asking follow-up questions, sharing context, and even challenging its responses, just as you would with a human collaborator.

• Be respectful and flexible: Use polite language, adapt your tone, and be patient with responses.
• Be clear and focused: Formulate full sentences and stick to the topic for productive dialogue.
• Be proactive: Ask AI for help when stuck or to improve your prompts.

Experimental and adaptive. Gen AI evolves at a remarkable pace, necessitating a continuous learning mindset. Managers must stay curious, experiment with new models and features, and understand the technology's expanding capabilities and limitations. This hands-on immersion is vital for personal relevance and for fostering an exploratory culture within teams.

• Test and share regularly: Encourage team experimentation and knowledge sharing.
• Embrace versatility: Try multiple AI models to find the best fit for different tasks.

Responsible and vigilant. Unlike error-free tools, gen AI can "hallucinate" or fabricate information, requiring a fundamentally different approach. Managers must be vigilant, develop robust guardrails, and understand ethical, legal, security, and regulatory risks. This responsibility extends to setting an example and educating teams on responsible AI use, ensuring human judgment always augments, never replaces, AI.

4. Enhancing Personal Productivity with Gen AI

By freeing up time from these labor-intensive tasks, you can concentrate efforts on more fulfilling work, improving your motivation, and productivity.

Streamlining email management. Email, while essential, can be a productivity drain. Gen AI integrated with email platforms (e.g., Google Gemini in Gmail, Microsoft Copilot in Outlook) can summarize long threads, extract key information, and draft messages in various tones and styles. This frees managers from sifting through communications, allowing focus on higher-value tasks.

• Drafting assistance: Improve clarity, conciseness, and tone; detect biases; ensure logical flow.
• Information extraction: Summarize threads, identify key points, and link to original emails.

Optimizing time management. Managers face heavy workloads, interruptions, and constant responsibilities. Gen AI, integrated with collaboration apps, can significantly enhance time efficiency. It provides overviews of schedules, prioritizes tasks, and prepares for appointments by retrieving relevant information.

• Schedule management: Get detailed lists of upcoming endeavors, categorize activities, and rank tasks by urgency.
• Meeting preparation: List action items, explain roles, and generate talking points from documents.
• Meeting participation: Attend meetings on your behalf, transcribe, and summarize key points and action items.

Efficient summarization. Managers are inundated with information from various sources. Gen AI excels at summarizing and interpreting diverse inputs, from long documents to presentations. It can distill insights, create bulleted lists, executive summaries, or even compare multiple texts, saving valuable time and ensuring critical information is not missed.

• Customizable output: Summaries can be tailored in style and format (tables, lists, memos).
• Advanced techniques: Use "Chain of Density" for increasingly detailed yet concise summaries of complex documents.
• Crucial oversight: Always verify AI-generated summaries for accuracy, tone, and factual correctness, as AI can fabricate information.

5. Driving Personal Growth and Persuasive Communication

To be a good manager, you need to understand what you’re doing well and where you’re falling short.

Self-reflection for leadership. Generative AI, acting as a Co-Thinker, can guide managers in a structured practice of self-reflection on their values, behaviors, and leadership styles. It can draw on established theories (e.g., Daniel Goleman's leadership styles), ask probing questions, and offer insights, fostering introspection and continuous improvement.

• Personalized guidance: AI can act as a neutral observer or expert coach, providing a safe space for candid self-assessment.
• Beyond human coaches: While not a replacement, AI can complement human coaching, especially when resources are limited, offering accessible, anytime support.

Soliciting and acting on feedback. Effective managers actively seek and process feedback for growth, despite common reluctance from others to provide it. Gen AI can help managers hone this skill by suggesting approaches to solicit candid input, process it without defensiveness, and translate it into actionable steps for personal and professional development.

• Methodological support: AI can guide discussions on improving feedback collection from direct reports.
• Emotional intelligence: AI can help managers prepare for and manage emotional reactions to negative feedback.

Persuasive communication. Gen AI as a Co-Thinker can transform speech and job interview preparation. For speeches, it aids in defining storytelling, sharpening messages, preempting objections, and refining delivery aspects like tone and gestures. For interviews, it acts as a sparring partner, simulating scenarios and anticipating questions, accelerating professional growth.

• Speech preparation: Frame the story, suggest data/quotes/metaphors, develop wording, and recommend nonverbal components.
• Interview rehearsal: Extract insights from job descriptions, match experience, draft/review résumés, and simulate mock interviews with feedback.

6. Streamlining Team Operations and Fostering Creativity

Most companies would not be successful without the creativity of their people.

Efficient meeting management. Meetings are crucial but often inefficient. Gen AI, integrated with collaboration apps, can streamline the entire meeting lifecycle. Before, it helps plan agendas and prepare pre-reading. During, it takes notes, transcribes, and offers real-time insights. After, it summarizes discussions, tracks action items, and debriefs, freeing up team members for more meaningful engagement.

• Pre-meeting: Draft agendas, summarize documents for pre-reading, suggest questions.
• During meeting: Take notes, track speakers, offer lateral thinking ideas, highlight disagreements.
• Post-meeting: Prepare summaries, track progress, recommend topics for next meetings.

Goal setting and articulation. Helping teams set ambitious yet achievable goals is vital. Gen AI, familiar with frameworks like OKR, SMART, and FAST, can guide managers in defining, structuring, and articulating goals effectively. It clarifies alignment with company objectives, details tasks, and identifies appropriate metrics for progress measurement.

• Framework guidance: Explain goal-setting techniques and guide their application.
• Clarity and alignment: Rephrase goals for clarity and ensure direct support of company strategy.
• Metric identification: Suggest relevant qualitative and quantitative metrics, and even formulas.

Team creativity support. Creative teams are essential for innovation. Gen AI as a Co-Pilot can augment the creative process by generating a wide array of ideas, providing fresh perspectives, and assisting in team composition. It helps managers assemble the right mix of skills and foster an environment where creative minds can thrive.

• Team composition: Identify multidisciplinary roles, articulate necessary skills, and check for diversity.
• Idea generation: Expand brainstorming scope, provide divergent perspectives, cluster ideas, refine concepts, and assess ideas against criteria.
• Visualization: Use text-to-image capabilities to make concepts tangible and concrete.

7. Leading Teams with Purpose and Resolving Complex Problems

Establishing a clear and compelling purpose is vital for bringing a group together as a true team.

Crafting team purpose. Instilling a shared, compelling purpose is crucial for team cohesion and motivation. Gen AI, acting as a leadership coach, can guide structured reflection to unveil the deeper meaning of a team's work. It helps link team activities to the company's overarching purpose, fostering clarity and driving action.

• Structured reflection: Facilitate discussion on strategic aspiration, value creation, and collective impact.
• Purpose articulation: Suggest concise, inspiring statements that resonate with team members.

Designing high-quality work. Managers must define roles that are engaging, varied, and allow for growth, balancing autonomy, workload, mastery, collaboration, and engagement. Gen AI as a Co-Thinker can help reflect on these dimensions, suggesting good practices and identifying warning signs of issues like burnout or disengagement.

• Work design principles: Discuss factors like autonomy, workload, mastery, collaboration, and engagement.
• Actionable steps: Recommend concrete actions to implement design principles and avoid pitfalls.

Facilitating conflict resolution. Conflict is inevitable in diverse teams but can be toxic if mismanaged. Gen AI can act as a specialized coach to help managers understand conflict sources, explore resolution options, and prepare for critical conversations. It aids in identifying root causes, suggesting mediation approaches, and providing sample language to rebuild team cohesion.

• Conflict analysis: Probe deeper into causes, including overlooked psychological or organizational mechanisms.
• Mediation strategies: Suggest appropriate approaches (e.g., empathetic listening, depersonalization) and provide sample language.
• Psychological safety: Reinforce practices that promote open communication and trust, essential for productive conflict resolution.

8. Leveraging Gen AI for Data-Driven Business Insights

Managers can ask gen AI questions and receive elaborate information presented in natural language in a way that is both intuitive and efficient, with the possibility of asking follow-up questions and diving deeper into topics.

Transforming information search. Generative AI revolutionizes information retrieval by allowing managers to ask complex questions in natural language, receiving summarized findings with cited sources, rather than just links. This applies to web knowledge, internal company databases, and even expert knowledge shared in team chats, significantly speeding up research.

• Web search: Scan the web, extract key findings, and cite sources directly.
• Company knowledge: Search internal databases, summarize key points, and uncover connections across documents.
• Expert knowledge: Cluster and summarize information from community chats, identify trending questions, and map active contributors.

Enhancing data analysis and visualization. Managers need data-driven decisions without getting bogged down by technical complexities. Gen AI acts as a data science-savvy Co-Pilot, capable of reading, cleaning, and analyzing large datasets. It can identify trends, segment data, perform calculations, and translate insights into compelling visuals.

• Data preparation: Describe content, identify missing values, and clean datasets for analysis.
• Insight extraction: Perform structured analyses (ranking, sorting, filtering, calculations, trend/pattern recognition, pivots, sensitivity analysis).
• Visual communication: Suggest appropriate chart types, design features, and craft textual descriptions to make data storytelling more engaging.
• Crucial verification: Always double-check AI-generated output for accuracy, as errors can occur.

9. Developing Robust Business Cases and Strategic Decisions

Your strategy should explain how your business will outperform competitors and secure its position.

Stakeholder perspectives. Building a persuasive business case requires understanding diverse stakeholder views. Gen AI excels at emulating different stakeholders (shareholders, customers, employees, regulators), helping managers gain a comprehensive understanding of their needs, pain points, and potential concerns, ensuring a more informed and inclusive approach to complex issues.

• Uncovering overlooked perspectives: Suggest additional critical stakeholders and their specific needs.
• Risk identification: Highlight red flags and propose mitigation actions from various viewpoints.

Evaluating trade-offs. Business decisions often involve difficult choices where win-win solutions are not possible. Gen AI as a Co-Thinker helps managers ponder various criteria, evaluate pros and cons of alternatives, and identify potential trade-offs (e.g., short-term vs. long-term, quality vs. speed). It also aids in articulating the rationale for decisions to stakeholders.

• Structured evaluation: Analyze advantages and disadvantages, integrate overlooked factors.
• Clear communication: Break down rationale into understandable points and formulate responses to likely questions.

Risk identification and mitigation. In a volatile, uncertain, complex, and ambiguous (VUCA) environment, proactive risk management is crucial. Gen AI can help map and evaluate risks, simulate scenarios, and de-risk projects by challenging critical assumptions. It guides managers in identifying vulnerabilities and developing robust mitigation strategies.

• Risk mapping: Consider a long list of risks, simulate variations, and visualize assessments in a risk matrix.
• De-risking projects: Challenge and refine critical assumptions, suggest hidden ones, and provide validation approaches.
• Scenario planning: Run multiple "What if" scenarios to stress-test assumptions and prepare for contingencies.

10. Leading Organizational Change with Generative AI

Change is difficult, both for employees and for the managers who must lead by example.

Defining transformation strategy. Successful change initiatives require clarity on the reasons for change, a sense of urgency, a clear vision, and a defined approach. Gen AI, acting as a change management expert, can guide managers in articulating the "why" of change, identifying evidence for urgency, assessing stakeholders, and drafting a compelling vision and strategy.

• Strategic clarity: Articulate the need for change and define success metrics.
• Stakeholder assessment: Identify critical stakeholders and strategies to bring them on board.
• Vision crafting: Draft inspiring vision statements and main pillars of the transformation strategy.

Overcoming resistance. A primary obstacle to change is human resistance, often leading to high failure rates in transformation efforts. Gen AI as a Co-Thinker helps managers examine the reasons for resistance within their team, anticipate potential objections, and identify effective ways to overcome them. It provides methodological guidance and suggests practical mitigation tactics.

• Anticipate resistance: List typical sources of resistance and underlying psychological mechanisms.
• Reduce resistance: Guide through methodological questions to find effective solutions and share successful change management tactics.

Promoting a mindset shift. True change requires winning hearts and minds and fostering a new mindset. Gen AI can actively involve teams in experiences that immerse them in the rationale and benefits of the desired mindset. It facilitates structured dialogues where team members evaluate their mindset maturity, reflect on improvement areas, and receive tailored suggestions for translating new mindsets into daily habits.

• Structured dialogue: Guide team members in self-evaluation of mindset maturity.
• Actionable practices: Suggest good practices, tips, and routines for applying the new mindset in daily work.
• Continuous learning: Encourage follow-up sessions to discuss progress and challenges in implementation.

11. Beyond Tasks: Redesigning Workflows for a HumanAIzed Future

Redesigning processes in the age of generative AI requires a shift away from a pure technology-driven principle of offloading to machines those activities that humans previously performed.

Four-step transformation journey. Integrating generative AI at scale requires a structured approach beyond individual task enhancement. This journey involves disciplined experimentation, building new human-AI collaboration skills, redesigning workflows to foster synergy, and establishing collective responsibility for ethical use.

Experimentation in both modes. Managers should engage teams in structured experiments across both Co-Pilot and Co-Thinker modes, starting with non-critical workflows. Co-Pilot is ideal for large-scale productivity boosts (e.g., data analysis, slide drafting), while Co-Thinker suits specialized, complex problem-solving requiring deep dialogue and co-creation.

• Impact and feasibility: Prioritize tasks based on business impact, functional fit, learning potential, compliance, access, risks, and limitations.
• Structured measurement: Define KPIs (productivity, quality, engagement, sentiment), use control groups, time-box tasks, and conduct retrospective analyses.

Redesigning workflows. The true impact of Gen AI extends to transforming entire workflows, shifting from simply offloading tasks to designing for dynamic human-AI collaboration. This means establishing clear guidelines on when AI seeks human input and vice versa, and how they communicate, ensuring humans remain in the driver's seat for critical decisions.

• Collaborative design: Focus on synergy, where AI provides analytical capabilities and breadth, and humans offer context, critical thinking, and emotional intelligence.
• Organizational adjustment: Be prepared for potential adjustments to team and organizational structures as workflows evolve.

12. Embracing Collective Responsibility in the AI Era

Ultimately, human assessment is required to verify the quality of the output generated by LLMs.

Infallibility is a myth. Unlike traditional tools, generative AI is not infallible; its statistical foundation means it can produce inaccuracies, errors, or "hallucinations." This inherent fallibility necessitates human oversight and critical judgment to verify the quality and reliability of AI-generated output.

Mitigating the "trust trap." The tendency for individuals to over-rely on AI systems, known as the "trust trap," poses a significant risk. Companies must adopt a balanced approach: establishing ethical frameworks and guidelines at the organizational level, while equipping individuals with critical thinking skills to anticipate risks and spot anomalies.

• Individual judgment: Exercise judgment before (setting goals), during (asking pertinent questions, providing context), and after (interpreting recommendations) AI interactions.
• Collective judgment: Foster collaborative practices like peer review and seeking validation from expert colleagues to ensure shared responsibility and robust outcomes.

HumanAIzed future. The goal is to move towards "humanAIzed" organizations where humans and intelligent machines fuse on a large scale, with workflows designed for integrated collaboration. This future demands continuous preparation, experimentation, and a commitment to fostering positive human relationships within teams, ensuring AI augments, rather than diminishes, human connection and collective creativity.

Last updated: August 17, 2025