AI-Enabled Organizational Design

Emerging Departments: How AI is Transforming Organizations Transformation in light of AI isn't just about digital change—it's strategic, cultural, and organizational. Early results of organizational optimization with AI reveal that traditional structures are evolving into new, combined departments that break down silos and enhance collaboration. Here are some emerging trends: 1. Human Experience Department (Led by the CXO) Combines marketing, HR, and customer service to create a unified experience approach. Focuses on customer and employee experience as a seamless continuum. Example: Airbnb and Starbucks blending internal and external engagement for holistic experience design. 2. The Intelligence Function (Led by Chief Data & Intelligence Officer (CDIO)) Merges IT, data analytics, and AI strategy into a unified intelligence function. Enhances decision-making with data-driven insights and technology integration. Example: Microsoft and Amazon use intelligence functions to support strategy and innovation. 3. Integrated Growth Department (Led by the CGO) Combines Marketing, Sales, and Customer Success to create cohesive client journeys. Prioritizes growth by aligning customer interactions across all touchpoints. Example: HubSpot and Salesforce driving client experience continuity. 4. Strategic Innovation & Transformation Office (Led by Chief Strategy Officer or Chief Transformation Officer) Combines strategy, innovation, and transformation initiatives for continuous evolution. Fosters agility by integrating foresight and innovation into long-term strategy. Example: Tesla blending innovation with strategic growth planning. 5. Technology and Digital Transformation Department (Led by the Chief Technology & Transformation Officer) Integrates IT, digital transformation, and cybersecurity under one strategic role. Embeds technology into workflows while ensuring security and compliance. Example: Cisco and IBM streamlining their digital transformation efforts. 6. Resilience and Continuity Department (Led by the Chief Risk Officer) Oversees Risk Management, Business Continuity, and Strategic Foresight. Ensures organizational resilience in an increasingly FLUX world. Example: JP Morgan building resilience to mitigate risks and ensure continuity. 7. Ethics and Responsible AI Office (Led by the CEAO) Ensures ethical AI use and compliance with regulatory standards. Maintains trust and integrity as AI becomes central to business strategy. Example: Microsoft and IBM proactively building ethics frameworks for responsible AI. In sum, AI is driving fundamental shifts in how we structure our organizations. To thrive, leaders must think beyond digital transformation and focus on strategic, cultural, and organizational evolution. The companies that succeed will be those that break down silos, integrate their functions, and embrace transformation as a continuous journey.

Org Charts of the Future Don’t Look Like Org Charts at All. Once upon a time, functions sat neatly in their boxes. HR owned people. IT-owned systems. BUT .. here's what may happen in 2 years. Companies like Moderna are already experimenting with the next move, rolling HR + IT into a single role “Chief People & Digital” groups. Why? Because they are hedging that talent strategy is inseparable from tech fluency. And that’s just the beginning. So, here’s my Future Roles Forecast once AI is materially embedded into the operating model: BUSINESS 💥 AI Monetization Strategist – designs usage tiers, pricing models, API monetization. 💥 Head of AI Partnerships – builds trust-based ecosystems with providers, infrastructure, and academia. TECHNICAL 💥 Prompt Engineer – closes the gap between human intent and model execution. 💥 Synthetic Data Architect – builds edge-case datasets for safe, scalable validation. 💥 RLHF Lead – runs human feedback pipelines to keep AI aligned and safe. OPERATIONS 💥 Model Governance Officer – enforces policies around black-box decisions. 💥 AI Cost Controller – audits GPU spend, runtime economics, dollar-per-output. TALENT 💥 AI Workforce Planner – forecasts job impact, redeploys people, sustains morale. 💥 AI-Diversity Advocate – ensures underrepresented voices shape both data and design. Also, Cross-functional hot zones will emerge: 💡 Product ↔ Engineering (build vs. viable) 💡 Ops ↔ Tech (deployment vs. scalability) 💡 Talent ↔ Business (hiring vs. GTM) Recommendations: - Start with overlap. Early AI teams wear multiple hats. Split later, when load—not ambition—demands it. - Recruit “interface thinkers.” The ones who thrive at boundaries—product ↔ tech, ethics ↔ infra, adoption ↔ change. I think the new org chart isn’t lines and boxes—it’s interfaces and leverage.

Everyone’s racing to adopt AI. But most are missing the real unlock. According to a new research study, AI tools like ChatGPT are everywhere—but they’re not moving the needle on productivity, wages, or work hours. Why? Because AI isn’t a tech problem. It’s an organizational design problem. You don’t get ROI from AI by handing out logins. You get it by redesigning workflows, roles, and management systems to make the most of human+machine collaboration. The data is clear: Without clear organizational structure and support, average productivity gains from AI are just 2.8%. But, with training and leadership buy-in? Creativity, task expansion, and satisfaction rise 10–40%. The future of work isn’t about who uses AI—it’s about who redesigns their organization to unlock its power. Tools don’t transform companies. Structures, systems, and talent strategies do. Source: NBER Working Paper No. 33777, “Large Language Models, Small Labor Market Effects” by Anders Humlum & Emilie Vestergaard (May 2025). #FutureOfWork #AI #OrganizationalDesign #FreelanceTalent #UpworkResearch #ProductivityParadox #Leadership #HumanInTheLoop

Last month, during a strategy meeting with our client in Denver, their VP of Operations shared something that caught my attention. They'd restructured their entire project management layer, reducing 12 middle management roles to 4, with AI handling most of the coordination work that used to require human oversight. "It's more efficient," he said, "but we're still figuring out the human side of things." This conversation reflects a broader trend I'm seeing across Western enterprises. Gartner predicts that through 2026, 20% of organizations will use AI to flatten their organizational structure, eliminating more than half of current middle management positions. Meanwhile, US employers are advertising 42% fewer middle management positions at the end of 2024 than they did in the spring of 2022. I'm observing how organizations are rethinking traditional hierarchy. AI is now handling what middle managers used to own: status reports, performance dashboards, project coordination, and even basic decision making all done faster, cheaper, and without burnout. The technology is impressive. Microsoft now uses AI for up to 30% of its code development while simultaneously cutting over 40% of their recent engineering layoffs targeting software engineers. Microsoft's latest Copilot upgrade now gives AI the ability to use any software like a human would, not just via APIs, effectively automating many supervisory tasks. However, according to the World Economic Forum's 2025 Future of Jobs report, 41% of employers worldwide intend to reduce their workforce in the next five years due to AI automation, which raises important questions about organizational culture and employee development. The challenge isn't just technological it's human. Companies are discovering that while AI excels at coordination and reporting, the mentoring, relationship building, and cultural aspects of management require a different approach. To my fellow CTOs: we're not just redesigning org charts, we're reshaping how people work together. To emerging professionals: focus on skills that complement AI rather than compete with it. The future organization will be leaner, but success will still depend on human judgment and leadership.

AI is ushering in the next organizational paradigm—and it’s one that will bring together humans, AI agents, and machines into the workplace of the future. Early adopters of the agentic organization are already exploring what’s possible, transforming their operating models and embracing an AI-first approach to unlock significant value.   Our new article maps the contours of the agentic organization, sharing lessons from pioneering companies and guiding leaders on where to take action now: https://mck.co/4nBe554   Building an agentic organization requires a holistic reimagining of the enterprise across five pillars—business model; operating model; governance; workforce, people, and culture; and technology and data—and three radical shifts to make a step change in how to transform for the agentic era.   While the agentic organization paradigm will continue to evolve, today’s leaders can’t wait for perfect clarity. It’s time to think boldly, move fast, and dive deep—or risk being left behind.   #OrganizeToValue #Transformation #AgenticAI

AI isn’t just a tool—it’s a new node in the organizational network. AI is evolving from an assistant to an active team member—completing tasks, making decisions, and even collaborating like a real colleague. But what does this mean for the way we work? Using Organizational Network Analysis (ONA), we can explore how AI agents will reshape workplace dynamics: - Breaking down silos by sharing knowledge across teams - Speeding up decision-making by synthesizing insights and aligning stakeholders - Expanding the company’s network as AI agents take on specialized roles, forming entirely new connections Understanding these shifts will be critical for leaders looking to harness AI’s full potential. Check out my latest blog post to see how ONA can help organizations adapt and take advantage of coming agentic age.