Chapter 9: Human-Centric AI

Building Superhuman Employees, Not Super AI

Building on our exploration of how to prevent and address lazy AI usage, we now turn to a more fundamental question: how can organizations ensure that AI truly enhances human capabilities rather than just automating tasks? While Chapter 8 focused on avoiding superficial AI implementations, this chapter explores how to create a human-centric approach to AI that empowers employees to achieve superhuman results through strategic collaboration with AI tools.

In the quest to integrate artificial intelligence (AI) into enterprise operations, a critical misstep organizations often make is prioritizing the development of "super AI" systems over empowering their workforce to become "superhuman." The real power of AI lies not in replacing human ingenuity but in amplifying it—enhancing employees' abilities to think creatively, solve problems efficiently, and drive innovation with AI as their partner. In fact, 83% of companies say that employees demonstrating AI skills will have more job security than those who don't [1]. This reinforces the idea that AI should be viewed as an enabler of human potential rather than a substitute for it. The AI Operations framework provides the necessary foundation to enable this transformation.

The Philosophy Behind Superhuman Employees

At its core, the concept of superhuman employees revolves around augmentation, which can include automation. It's about creating a symbiotic relationship between human intelligence and AI tools, where the latter acts as an enabler rather than a replacement. This philosophy aligns with the ethos of AI Operations (AI Ops): embedding AI into workflows to elevate human capabilities rather than sidelining them.

Key principles of this philosophy include:

• Empowerment through Augmentation: AI should automate repetitive and low-value tasks, freeing employees to focus on strategic, creative, and high-value activities.
• Human-Centric Design: AI tools must be intuitive, accessible, and aligned with the natural workflows of employees.
• Collaboration, Not Substitution: The goal is to foster a collaborative partnership where humans and AI solve problems together, leveraging their unique strengths.

AI Operations serves as the guiding framework to implement these principles. By ensuring that AI tools are integrated thoughtfully and strategically, organizations can focus on enhancing human potential rather than creating technological replacements.

What Does a Superhuman Employee Look Like?

If you were to ask a random person what they thought it would take to be really good at AI, they might describe someone highly technical. This couldn't be further from the truth. Across organizations, superhuman AI-empowered employees emerge from all departments. AI Operations enables this by equipping employees with the mindset, skills, and tools to succeed through structured support and a robust infrastructure. It provides the necessary frameworks for training, experimentation, and cross-functional collaboration, ensuring employees can fully leverage AI in their roles:

• Think Critically and Creatively: Use AI-generated insights as a starting point for innovative problem-solving.
• Adapt Quickly: Embrace new tools and workflows with minimal disruption.
• Collaborate Effectively: Partner with AI systems and cross-functional teams to achieve common goals.
• Drive Innovation: Identify novel applications of AI to enhance workflows and outcomes.

Examples of superhuman employees in action include:

• A Marketing Specialist: Using generative AI to craft personalized campaigns, analyze performance data, and iterate quickly based on feedback.
• A Customer Support Representative: Leveraging AI-powered chat tools to provide faster, more accurate responses while focusing on complex, empathy-driven interactions.
• An Operations Manager: Utilizing predictive analytics to anticipate bottlenecks and optimize supply chain efficiency.
• A Salesperson: Saving hours of prospect research to deliver messaging that truly resonates.
• A Sales Engineer: Using AI to create custom demo environments in minutes instead of days.

AI Operations is the enabler that creates the environment for these employees to thrive.

The Building Blocks of Superhuman Employees

Creating superhuman employees requires fostering an environment rooted in AI Operations, which encourages exploration, education, and incentives for AI adoption. AI Operations acts as the foundation for this environment by promoting a human-centered approach to AI integration. Here's how organizations can build that foundation:

1. Encouraging Exploration and Experimentation Many organizations, especially schools, take a restrictive approach to new technologies out of fear of misuse. This is the exact opposite of what should be done. Instead of blocking AI tools, companies should create a culture that encourages safe experimentation. AI Operations provides the structure and guardrails to ensure this experimentation remains productive and ethical. These guardrails might include clear policies for responsible AI use, tools to monitor outcomes for unintended consequences, and training sessions to guide employees in exploring AI tools effectively. This framework ensures employees can experiment with confidence while aligning their work with organizational goals.

2. Providing AI Education Stipends Rather than bringing in corporate trainers—who often have a limited grasp of AI's rapidly evolving landscape—organizations should empower employees to pursue self-directed learning. AI Operations can establish guidelines for learning while offering AI education stipends that allow employees to choose online courses, certifications, or workshops that align with their interests and roles. This approach ensures learning remains relevant and engaging while fostering a sense of ownership over skill development.

3. Incentivizing AI Adoption Encouraging employees to embrace AI tools requires motivation beyond mandatory training. Organizations can achieve this by:

   • Hosting AI Contests and Hackathons: Create a sense of urgency and excitement by offering prizes for innovative AI applications.
   • Recognizing and Rewarding Innovation: Celebrate employees who successfully integrate AI into their workflows, demonstrating tangible improvements.
   • Providing Career Growth Opportunities: Employees who excel in AI adoption should be given opportunities for career advancement or specialized roles within AI Ops teams.

4. Investing in AI Leadership If an organization can afford it, hiring or designating an AI Ops leader can significantly impact AI adoption. This role is responsible for guiding employees, identifying high-impact AI use cases, and fostering a company-wide culture of AI exploration. Having a dedicated leader ensures that AI initiatives remain focused, strategic, and integrated into the company's long-term vision.

The Role of AI Operations in Addressing Employee Fears and Uncertainty

A well-structured AI Operations approach does more than enable AI-powered employees—it reassures them. Employees are far more likely to adopt AI when they see it as a company-wide initiative designed to enhance their work rather than a clandestine project that threatens job security. This is especially important as 45% of workers globally are worried about AI replacing them at work, with 30% of U.S. workers specifically concerned that their jobs could be eliminated [1]. Without clear messaging, these fears can lead to resistance, slowing AI adoption and limiting its effectiveness.

By establishing AI Operations as a dedicated function that spans departments, organizations send a clear message: AI is here to assist, not replace. Instead of employees worrying about a small group of engineers automating their roles behind closed doors, they should see AI Ops as a transparent, empowering framework that exists to make them more valuable in their work. In fact, by 2030, about 14% of the global workforce (~375 million workers) may need to change occupations or acquire new skills due to AI and automation's impact [3]. This highlights the importance of upskilling initiatives and AI literacy programs to ease concerns and prepare employees for evolving roles.

How AI Ops Drives Buy-In

1. Clear Communication – Regular updates on AI initiatives ensure employees understand how AI is being used and why. Transparency about AI's purpose, limitations, and benefits reduces fear and fosters trust. Given that 79% of corporate leaders feel their company needs to adopt AI to stay competitive, yet 60% fear their leadership lacks a clear AI implementation plan [4], organizations must prioritize structured AI strategies to instill confidence among employees.

2. Involvement in AI Strategy – Employees should be engaged in discussions on how AI can improve their workflows. This fosters a sense of ownership and encourages innovation. Employees who feel involved are more likely to advocate for AI adoption rather than resist it.

3. Skill Development – Structured programs and resources help employees see AI as a tool for personal and professional growth rather than a threat. 68% of business leaders say they struggle to attract sufficient AI-skilled talent [5], reinforcing the importance of upskilling existing employees. Companies that invest in AI training not only alleviate these talent shortages but also empower their workforce to use AI effectively.

When AI Operations is implemented as a cross-functional effort that puts people first, organizations create a culture where employees feel confident, empowered, and motivated to integrate AI into their daily work. Rather than fearing change, they become champions of it.

Conclusion

Creating the right AI Operations strategy is the foundation for developing superhuman AI-powered employees. By fostering an environment that encourages exploration, education, and incentives, AI Ops enables employees to embrace AI as a tool that enhances their capabilities rather than threatens their roles. A well-structured AI Ops strategy reassures employees by demonstrating that AI is being integrated to support them, not replace them. When employees see AI Operations as a company-wide initiative designed to improve their work rather than as a project run by a select few, they are far more likely to engage with and champion AI adoption. This approach ensures that AI adoption is both impactful and sustainable, positioning organizations to unlock innovation, productivity, and resilience in an AI-driven world.

Building an Army of Interns (thought exercise)

Imagine if every employee in your organization could mentally approach their work as if they had an unlimited number of interns to assist with their daily tasks. What would you have them do? How would they enhance your work? This is the mindset shift that AI Operations (AI Ops) enables—empowering employees to think of AI not as a replacement for workers, but as a limitless resource to augment their productivity and creativity. Credit for this idea goes to Bryon Jacob, the CTO and Co-Founder of data.world, who has encouraged and helped me at every step of my personal AI journey.

Step 1: Rethinking Work – The Intern Exercise

If you've ever hired an intern, you know how this goes. You're happy to have the help, but you need to break tasks down into parts and processes to ensure they can effectively contribute. When done right, this creates a mutually beneficial relationship. However, not every employee gets to go through this exercise, as companies can't afford to hire an unlimited number of interns for everyone. But what if they could?

Better yet, have employees imagine they could and encourage them to go through this exercise. This is a great first step in helping people rethink how they work and how AI can assist them. It also helps them to:

• Develop a delegation-first mindset, focusing on the most valuable aspects of their work.
• Consider scaling administrative and analytical tasks.
• Introduce them to Systems Thinking.

These are all valuable skills, regardless of AI, and a great on-ramp to thinking about how AI can work for them.

Step 2: Building Your "Intern" Team

Take the list of "intern" tasks and start thinking about how AI tools might help. Many of these tasks can be accomplished through simple chat interfaces like Chat-GPT or Claude, along with a personal library of custom prompts. Taking it a step further, employees could create custom GPTs in Chat-GPT to streamline their workflows. Tools like Relevance AI and Make.com allow users to integrate existing tools and AI to accomplish tasks efficiently.

Below is a sample list of tasks that AI "interns" might handle:

1. Administrative Support

   • Automating meeting notes and summaries.
   • Managing scheduling and reminders.
   • Drafting standard emails and documents.

2. Data Analysis and Research

   • Aggregating and summarizing market trends.
   • Identifying patterns in financial reports or operational metrics.
   • Extracting key insights from large datasets.

3. Content Generation and Curation

   • Creating blog posts, social media content, and marketing copy.
   • Generating product descriptions and FAQs.
   • Summarizing lengthy reports or articles.

4. Customer Support Assistance

   • Drafting personalized responses based on prior interactions.
   • Automating FAQs and basic troubleshooting.
   • Routing complex inquiries to human agents with contextual summaries.

5. Coding and Software Development

   • Generating boilerplate code.
   • Writing and testing scripts for automation.
   • Assisting in debugging and documentation.

Having a dedicated AI Operations team can greatly enhance this process. The AI landscape evolves at a rapid pace, and having knowledgeable professionals who stay on top of emerging tools and trends can provide invaluable guidance as employees build out their AI intern teams. An AI Operations leader would understand which tools align with the company's infrastructure, which solutions to buy versus build, and how to integrate AI effectively. Expecting a manager—who is already focused on their daily workload—to keep up with the AI landscape and effectively guide employees through this process is unrealistic. AI Operations is key to ensuring AI implementation is efficient and well-integrated, helping employees and managers alike navigate the evolving landscape of AI tools effectively.

Conclusion

A simple exercise and shift in thinking can help employees overcome barriers to AI adoption. Thinking about AI in terms of "interns" not only makes AI more approachable but also encourages the development of valuable skills, such as delegation and systems thinking. By engaging with AI tools, employees refine their ability to break down tasks into structured processes, communicate expectations clearly, and iterate on results—just as they would when managing a real team of interns. More importantly, it empowers employees and gives them autonomy. Many employees leave these discussions feeling excited about their work again, eager to experiment and innovate with AI at their side.

Real-World Examples of Human-AI Collaboration

The rapid evolution of AI has led to the development of tools that significantly enhance human capabilities. When deployed within a structured AI Operations framework, these tools enable employees to become 'superhuman'—leveraging AI to amplify their intelligence, efficiency, and decision-making abilities. Many of these tools emerge from organizations in the early stages of AI Operations, often without perfectly structured data as explored in Chapter 1. This aligns with the concepts in Chapter 3, which highlight how organizations can overcome cultural and operational barriers to AI adoption. Yet, they still unlock tremendous value, demonstrating that AI adoption does not require perfection. This section explores real-world examples of human-AI collaboration, illustrating what is possible with the right mindset and infrastructure. And this is only the tip of the iceberg.

AI-Powered Sales and Business Development

Sales and business development require extensive research, personalized communication, and strategic engagement. AI significantly enhances these efforts by automating routine tasks, providing deep insights, and optimizing interactions.

• Prospect Researcher: Enter a LinkedIn profile to get a personality profile and tailored outreach messages.
• Account Researcher: AI scrapes the internet and internal databases to craft a custom sales pitch based on a company's latest initiatives.
• Cold Call Role Play: Engage in AI-driven role-playing to simulate challenging sales conversations and receive real-time feedback.
• Discovery Call Role Play: AI-powered simulations help sales teams practice extracting key information from hard-to-crack prospects.

AI in Content Creation and Marketing

AI has become an essential tool in marketing, helping professionals create compelling, on-brand content quickly and efficiently.

• Email Campaign Writer: Craft multiple emails quickly with a consistent message and clear CTAs.
• Chat with Podcast Transcripts: Quickly search for nuanced topics buried in podcast transcripts to surface valuable insights.
• Respond to LinkedIn Messages and Emails: Generate context-aware responses for professional outreach and engagement.

AI for Research and Knowledge Management

Organizations are using AI to enhance knowledge discovery and streamline documentation workflows:

• RFI Writer: Drag and drop an RFI to get structured guidance and real writing assistance.
• Docs Bot: Chat with AI trained on internal documentation to find information quickly.
• Meeting Notes Summarization: AI-generated summaries turn meeting transcripts into action items and key takeaways.

AI in Learning and Employee Development

Companies are using AI to personalize training programs and provide employees with real-time learning resources, reinforcing the AI literacy initiatives discussed in Chapter 4:

• Learning Plan Generator: Take a quiz to receive a customized learning plan with suggested resources.
• AI-Powered Mentorship: Match employees with mentors and provide continuous career development insights.

AI in Engineering and Product Development

AI is transforming engineering and product teams by automating repetitive tasks and enhancing decision-making:

• Bug Ticket Generator: AI suggests bug reports based on observed software behavior.
• Code Review Summarizer: AI scans pull requests and summarizes key changes and potential issues.
• Feature Prioritization: AI analyzes feedback and trends to help product managers determine what to build next.

AI in Legal and Compliance

Legal teams are leveraging AI to streamline workflows and ensure compliance:

• Contract Clause Checker: AI highlights missing or risky clauses in legal documents.
• Legal Research Assistant: Quickly summarize case law and regulatory updates.
• Automated Policy Updates: AI helps keep policies and internal guidelines aligned with new legal requirements.

AI in Accounting and Finance

AI is enhancing accuracy, efficiency, and decision-making in finance and accounting:

• Invoice Categorization: AI sorts and categorizes invoices automatically to speed up reconciliation.
• Fraud Anomaly Detector: AI scans transactions for unusual patterns that may indicate fraud.
• Expense Report Generator: AI drafts expense reports based on submitted receipts and corporate policies.

The Future of Human-AI Collaboration

These examples illustrate just a glimpse of what is possible when organizations commit to AI Operations. By fostering a structured AI framework, even those in the early stages can create tools that amplify human potential, improve efficiency, and streamline decision-making. AI is not just a support tool—it is a force multiplier that, when deployed correctly, enables employees to operate at an entirely new level, fulfilling the vision of superhuman employees introduced earlier. As organizations refine their AI strategies, they will continue unlocking new, transformative capabilities that redefine what is possible in every industry.

References

1. AIPRM / ResumeBuilder Survey - "AI Replacing Jobs Statistics" (2023)
2. McKinsey Global Institute - "Companies Using AI" (2021)
3. Microsoft Work Trend Index - "AI in Workplace Statistics" (2023)
4. AI Talent Shortage Report - "AI in Workplace Statistics" (2024)