2026 is the year organizations will accelerate their move from AI experimentation to incorporation into key processes, products and decision frameworks. Senior leaders, board members and their advisors are leaning into organization design in order to discern what their organizations will look like as the future unfolds integrating generative AI, agentic AI, robotics and other technologies. This redesign thinking must precede the redesign work. It means understanding the direction of travel—for their firms and their industries—their goals and objectives, the speed of change and what it means for their organization to compete and be resilient.
Designing well for the future puts key discussions first. What are the organization’s actual objectives, values and priorities? Beyond the slogans or values statements that have been printed and memorized, how does the organization make decisions when tensions arise between stakeholders or key interests? How does it allocate rewards, costs and risks? How does it resolve tensions, whom does it tend to favor and which tensions get resolved first?
The answers to these questions will illuminate what your organization really values as you reinvent for its next generation of innovation and execution. These questions will determine what behaviors you enable, what risks you accept and, ultimately, what type of organization you evolve into as AI becomes more embedded in your operations. It will also lay the foundation for a decision framework that advances the key change areas below:
DECISION RIGHTS AND ACCOUNTABILITY
AI doesn’t sit in one place anymore. The further along the adoption curve an organization moves, the more dispersed the knowledge, use and application. Leaders need to map how decisions can be made—and by whom within the organization, as different types of deployments of AI will have different risks. In particular, agentic AI has some very specific requirements that need to be determined up front as part of the design phase: Which decisions will be left to agents to make autonomously? What are the triggers for human-in-the-loop? Who is accountable when an AI agent makes a consequential decision? This will require rethinking approval matrices, escalation paths and liability frameworks. This is work that most organizations haven’t contemplated in quite some time.
SIMULTANEOUS OPERATING MODELS
Sequential workflows tend to collapse as gen AI and agentic AI are adopted. When AI can draft, review and refine work simultaneously for multiple stakeholder groups, classic stage-gate, stakeholder processes just become bottlenecks. Processes that were designed around human limitations (like finishing one task before starting another) versus actual business requirements need close reexamination. This will reveal opportunities to redesign workflows rather than just accelerate existing, ill-fitting ones.
SKILL REQUIREMENTS AND NEW ROLES
The talent question isn’t just “hire more data scientists” anymore. Organizations need people who can bridge technical and domain expertise, who can understand both business context and AI capabilities well enough to design guardrails, interventions and to keep innovation on track. The challenge is to create roles that work for your organization as the operating model shifts. The new skills that are needed will be less sequential and task-oriented and more strategic, design-driven and provide real-time governance oversight. It means roles that lessen bottlenecks, can make values-driven decisions that understand the risks and opportunities for all stakeholders, as well as individuals who can lead exception protocols in the face of extreme time pressures. These new skills likely require retraining of current senior employees as well as the hiring of new ones. And these new skills will require new performance metrics and incentives.
THE PREPAREDNESS ADVANTAGE
Most organizations are familiar with the concept of preparedness as a regulatory compliance feature; however the concept will have profoundly new meaning when economic, political and social changes put additional pressure on their infrastructure, workforce, processes and markets as 2026 unfolds. Preparedness for and resilience in the face of traditional PESTLE (political, economic, social, technical, legal, environmental) elements will be a strategic necessity as norms continue to shift and business models change.
These are discussions that can start now, even while the technologies race ahead and your AI experiments emerge into operations.
