Unlocking Adoption: The AI Integration Framework

Of all the frameworks I’ve developed for working with #GenAI, this one provides the greatest unlock. It cuts through ambiguity, contextualizes AI, and replaces fear of replacement with intentional design for AI integration. Though I’ve presented on and discussed this framework numerous times - in keynotes, workshops, and even casual conversations over coffee or beer - this is my first attempt to write the AI Integration Framework up. I’m going to keep it fairly crisp here (as crisp as I am able), as there are speaking engagements, workshops, tools, and services to really bring the frame into your own work, your team’s efforts, or your organization’s AI journey.

AI Integration Framework:

• Type 1 Work - Human Exclusive Tasks: Work only I can do, requiring uniquely human skills and judgment. This is, and will continue to be, my work.
• Type 2 Work - AI Automation Potential: this is the work that the robot could do for me, at some point. This is "For Me" work.
• Type 3 Work - AI Collaboration Opportunities: this is the work I can do with AI, at higher quality, in less time, with less mental strain, and with more enjoyment. This is "With Me" work.

The most critical mindset shift in the AI space is moving from “What will AI do for me?” to “What will I do with AI?” Instead of chasing external ‘use cases,’ we should focus on our work—our tasks—and identify those ripe for AI augmentation. That's what the AI Integration Framework does.

The AI Integration Framework begins with you, your job, and the bundle of tasks that make up “your work.” This is a critical starting point for two reasons – 1) they are yours, and 2) you know them, so you can evaluate the quality of an AI output helping with them! And since you are now the leading the R&D effort on how to bring AI into your work, that knowledge is critical.

Unlike traditional software purchases, where R&D is outsourced to the vendor, generative AI requires organizations and employees to internalize the R&D process. For example, we outsourced customer record R&D when we subscribed to Salesforce; we outsourced collaboration tool R&D when we subscribed to Microsoft Teams. Generative AI is different – in essence organizations and employees must internalize the R&D around this new type of software, because it is the workers who will ultimate be able to spot where to bring it to life in their own work.

Now, begin by examining your own work – what you do on a day-to-day, week-to-week basis – with an eye toward what work you will always have to be doing (your human exclusive tasks) and what you can do at higher quality, in less time, with less mental strain, and more enjoyment (your AI collaboration opportunities).

Type 1) Human Exclusive Tasks: My Work

Work I still need to do myself (the people side of work) – This category identifies tasks that are best suited for humans due to the complexity of human interaction, emotional intelligence, ethical considerations, or intricate decision-making. This kind of work will always be done by people.

1. Work that demands physical presence - such as in-person team leadership, where body language and onsite decision-making play critical roles.
2. Work that requires human empathy - like counseling or patient care, where understanding and responding to human emotions are paramount.
3. Work that involves ethical judgment - such as making decisions on employee disputes or handling sensitive customer issues.
4. Work that requires cultural insights - like community outreach programs, where understanding local norms and values is essential.
5. Work that involves real-time improvisation - such as live event coordination, where instant decisions based on current happenings are required.
6. Work that requires a high degree of trust and confidentiality - such as legal consultations or personal financial planning.
7. Work that depends on creating or interpreting complex legal strategies - where nuanced understanding and human intuition guide decision-making.

Questions to ask yourself for your work:

• Which tasks require uniquely human skills, such as empathy, ethical judgment, or creativity?
• Where does your physical presence or ability to connect with others in person make a critical difference?
• What decisions or activities in your work demand trust, confidentiality, or cultural awareness?

Type 2) AI Automation Potential: For Me Work

Work AI can do completely for me or on my behalf – Tasks AI can fully automate, minimizing human intervention. These include repetitive or predictable work that improves efficiency and reduces human labor needs. While automation is enticing, I encourage people not to dwell here because the real magic lies in collaboration - explored in the next section.

1. Work that involves routine data processing - such as entering transaction data into business systems.
2. Work that requires monitoring technical systems or environments - like IT network monitoring for anomalies or security breaches.
3. Work that consists of answering standard FAQ-type customer queries - where responses are predefined and consistency is key.
4. Work that involves basic accounting tasks - such as reconciling bank statements and processing payroll.
5. Work that includes compiling and formatting periodic reports - such as weekly sales or performance reports.
6. Work that entails managing simple digital content updates - like updating website times or locations based on a schedule.
7. Work that requires sorting and categorizing information - such as organizing digital files or classifying simple data sets.

Questions to ask yourself for your work:

• Which repetitive or routine tasks could be automated to free up your time for more impactful work?
• Are there data-heavy processes, like reports or updates, that could be managed more efficiently by AI?
• What standard, predictable interactions - such as FAQs or simple requests - could AI handle on your behalf?

Type 3) AI Collaboration Opportunities: With Me Work

Work I can do with AI to improve productivity and outputs – Collaborative tasks where AI enhances human productivity and creativity, making processes more efficient and insightful without replacing the human touch. This is where the magic is! This is where effectively integrating AI means we work at higher quality, in less time, with less mental strain, and with more enjoyment. And sometime we do work we couldn’t have ever done without AI assistance. AI’s evolving capabilities, and the access you have in your work, determine the types of tasks and work where you can collaborate with an AI counterpart.

1. Work that benefits from quick information retrieval and analysis – like legal or medical research, where AI can provide fast access to vast amounts of data.
2. Work that involves creative design iterations – such as architectural design, where AI can suggest variations quickly based on set parameters.
3. Work that requires scheduling and logistical planning – where AI tools help optimize appointments and manage workflows efficiently.
4. Work that includes drafting and editing large documents – such as business reports or academic papers, where AI can assist in initial drafts and grammar checks.
5. Work that involves regular follow-up and reminders – like client management, where AI can automate contact schedules and maintain records.
6. Work that needs data visualization for better decision-making – such as financial analysis, where AI can create comprehensive charts and forecasts.
7. Work that can be enhanced by predictive analytics – like sales forecasting, where AI models predict trends and consumer behavior.

Questions to ask yourself for your own work:

• What tasks could benefit from AI tools to help you work faster, more accurately, or with greater creativity?
• Are there areas where AI could assist with brainstorming, analysis, or creating better visualizations?
• How could AI support your planning, drafting, or organizing to reduce mental strain and increase productivity?

Value of the AI Integration Framework

I’ve walked people through the AI Integration Framework a number of times, for all sorts of jobs in all sorts of industries with people who were AI savants to those who had never put in a single prompt. It has resonated time and time again. Here are the reasons I think that is:

It shifts control - you decide how to work with AI, rather than waiting for it to act on you.

It sets the stage for collaboration – clearly defining what you’ll do together creates the collaborative partnership that drive real output from GenAI.

It keeps a human in the loop by design – by defining the loops ourselves, we ensure we are part of the loop for the collaborative work

It reduces fear – instead of worrying about being replaced by AI, you bring AI into the work where it can be most helpful

It promotes adoption – AI adoption is what will fill the gap between nearly unlimited potential and the real value organizations ultimately receive

Conclusion

The AI Integration Framework is not just a tool; it facilitates the mindset shift that empowers individuals, teams, and organizations to approach generative AI with intention and confidence. By focusing on the tasks that define your work - what only you can do, what AI can do for you, and where you can collaborate with AI - you take charge of how AI integrates into your daily activities.

This framework helps demystify AI, transforming it from a source of uncertainty to an opportunity for enhanced productivity, creativity, and enjoyment. It provides a practical approach to navigating the AI era, one task at a time.

In the appendices, you’ll find examples of how the AI Integration Framework can be applied to different roles: Change Management Practitioner, People Team Leader, and CEO. These real-world examples illustrate how the framework can help imagine the possible within the context of your work. Whether you're just beginning your AI journey or looking to deepen your integration, this framework provides a strong foundation for success.

Appendix Example 1: AI Integration Analysis for Change Management Practitioners

Change Management Practitioners focus on guiding individuals and organizations through transitions, ensuring that changes are implemented smoothly and achieve desired outcomes. Their responsibilities include planning change strategies, managing resistance, communicating effectively, and fostering engagement among stakeholders. AI offers significant opportunities to enhance these processes while leaving uniquely human aspects intact.

Human Exclusive Tasks for Change Practitioners

Building Trust and Empathy with Stakeholders: Requires emotional intelligence to connect authentically with individuals affected by change. This involves active listening, empathy, and tailored communication that AI cannot replicate.

Resolving Resistance to Change: Negotiating and addressing stakeholder concerns involves understanding underlying fears and motivations, often needing real-time improvisation and cultural sensitivity.

Facilitating High-Stakes Meetings: Managing strategy discussions for organizational change requires nuanced judgment, leadership, and the ability to read group dynamics.

Cultural Alignment and Adaptation: Steering cultural shifts necessitates deep understanding of organizational values and human contexts to ensure alignment with the change vision.

AI Automation Potential for Change Practitioners

Routine Reporting: Automated systems can generate regular reports on the status of change initiatives, offering real-time data on progress and outcomes.

Survey Administration: AI can handle the deployment and collection of surveys to gather feedback, enabling quick adjustments to change plans.

Scheduling and Notifications: AI systems can automate scheduling for training sessions, reminders for stakeholders, and other routine tasks to streamline operations.

AI Collaboration Opportunities for Change Practitioners

Analyzing Change Readiness: AI tools can process surveys and engagement metrics to assess how prepared employees are for upcoming changes, saving time and revealing actionable insights.

Drafting Change Communication Plans: AI can generate templates for stakeholder emails, newsletters, or presentations, which can be refined by the practitioner to suit specific contexts.

Monitoring Feedback and Sentiment: AI can track employee sentiment through feedback tools and identify patterns of resistance or support, allowing for targeted interventions.

Optimizing Resource Allocation: Predictive analytics can recommend efficient distribution of resources across change initiatives, ensuring that critical areas are prioritized.

Designing Training Content: AI can assist in developing customized training modules, providing a foundation that practitioners can adapt to organizational needs.

Change Management Practitioners benefit from AI in enhancing efficiency and insight into data-heavy tasks while retaining the irreplaceable human qualities needed for empathy, leadership, and cultural understanding. By integrating AI effectively, practitioners can focus more on high-impact, people-centered responsibilities that drive successful transitions.

Appendix Example 2: AI Integration Analysis for Team Leaders

A People Team Leader oversees employee well-being, drives team productivity, and ensures alignment with organizational goals. Their role emphasizes fostering engagement, managing relationships, resolving conflicts, and supporting professional development. AI can assist in streamlining administrative processes and enhancing decision-making while leaving human-centered tasks untouched.

Human Exclusive Tasks for Team Leaders

Building Team Trust and Morale: Requires emotional intelligence to inspire confidence, resolve interpersonal issues, and sustain morale, particularly during challenging times.

Conducting Sensitive Conversations: Discussions about performance issues, career growth, or personal challenges demand empathy, discretion, and nuanced understanding that AI cannot provide.

Navigating Ethical Decisions: Making decisions involving sensitive employee matters requires judgment, cultural insight, and adherence to ethical considerations, which rely on a human touch.

Shaping Organizational Culture: Leading initiatives to instill core values and foster inclusivity involves real-time engagement and understanding of team dynamics and organizational nuances.

AI Automation Potential for Team Leaders

Scheduling and Reminders: AI can manage team calendars, schedule meetings, and send automatic reminders for deadlines or events.

Routine Reporting: Automated systems can generate reports on team performance, diversity metrics, or training completions, reducing manual effort.

Onboarding Processes: AI can handle routine aspects of onboarding, such as document collection, benefits enrollment, and compliance training scheduling.

AI Collaboration Opportunities for Team Leaders

Analyzing Employee Engagement Data: AI can process engagement surveys, attendance records, and feedback to provide actionable insights, helping leaders identify trends and areas of concern.

Drafting Policies and Communication: AI tools can create first drafts for HR policies or team communication, saving time and allowing leaders to focus on tailoring content for their audience.

Optimizing Workload Distribution: AI can recommend workload adjustments based on team members’ capacities and past performance, aiding in fair and effective resource allocation.

Monitoring Performance Metrics: AI dashboards can track productivity and highlight patterns, enabling leaders to proactively address underperformance or reward achievements.

Personalizing Employee Development Plans: AI can analyze career progression data and suggest tailored development plans, which leaders can refine to align with organizational goals.

People Team Leaders thrive on building relationships, guiding their teams, and aligning people strategies with organizational objectives. AI enhances efficiency by automating repetitive tasks and offering data-driven insights, enabling leaders to focus on fostering connections and driving impactful change.

Appendix Example 3: AI Integration Analysis for Chief Executive Officers

A Chief Executive Officer (CEO) is responsible for strategic decision-making, company vision, and overall leadership. This role requires a balance of high-level strategic thinking, stakeholder management, and decision-making. AI can enhance a CEO's effectiveness by automating routine tasks, providing actionable insights, and supporting complex decision processes while leaving critical human-led leadership tasks intact.

Human Exclusive Tasks for CEOs

Setting and Communicating Vision: Crafting and articulating the company's vision demands deep understanding of market trends, organizational goals, and cultural dynamics—tasks that rely on human insight and inspiration.

Building High-Stakes Relationships: Engaging with investors, partners, and key stakeholders requires trust-building, emotional intelligence, and negotiation skills that AI cannot replicate.

Navigating Ethical Dilemmas: Decisions involving corporate responsibility, ethical trade-offs, or major organizational changes require human judgment, empathy, and alignment with personal and organizational values.

Leading Organizational Culture: Steering the company culture to align with its vision involves direct interaction with employees, fostering inclusivity, and promoting shared values.

AI Automation Potential for CEOs

Routine Reporting and Analytics: AI can generate regular reports summarizing key metrics such as revenue growth, operational efficiency, or market share, saving time for strategic analysis.

Calendar and Meeting Management: Automated scheduling tools can handle meeting arrangements, reminders, and travel logistics, ensuring the CEO's schedule runs smoothly.

Stakeholder Updates: AI can send automated, personalized updates to investors, board members, and other stakeholders regarding company performance and news.

AI Collaboration Opportunities for CEOs

Data-Driven Strategic Planning: AI tools can analyze market data, financial trends, and competitive landscapes, providing actionable insights that CEOs can use to shape strategic decisions.

Enhancing Decision-Making Processes: Predictive analytics can help CEOs anticipate market trends, identify risks, and evaluate the potential outcomes of various strategies.

Personalizing Communication: AI can generate initial drafts of speeches, memos, or press releases, allowing CEOs to focus on personalizing these communications to align with their style and goals.

Monitoring Key Metrics: AI dashboards can provide real-time updates on financial performance, employee engagement, or customer sentiment, enabling CEOs to stay informed and act swiftly.

Optimizing Resource Allocation: AI can suggest resource distribution strategies based on organizational needs and goals, improving efficiency in implementing new initiatives.

As the visionary leader of an organization, the CEO is central to strategic decisions, stakeholder relationships, and cultural leadership. AI complements this role by providing data-driven insights, automating routine tasks, and enhancing communication processes, allowing the CEO to dedicate more time to guiding the organization toward its goals.

###

Reach out to learn more about bring the AI Integration Framework into your AI journey.