Nov 3, 2026 · 2 min read
Leaving too much of the thinking to AI can erode judgment, problem framing, and creativity within organizations. The research examines the warning signs and how work can be organized to preserve these skills.
Bora Kaykayoğlu · Nov 3, 2026
Oct 10, 2026 · 2 min read
An AI-Native company redesigns its business processes, decision-making practices, and team capabilities with AI. The work runs from understanding team capabilities to achieving measurable results on a real business problem.
Bora Kaykayoğlu · Oct 10, 2026
Sep 12, 2026 · 2 min read
AI's contribution to work depends on the problem it is used for and how its output is evaluated. Developing human capabilities alongside technology matters if that contribution is to become part of everyday work.
Bora Kaykayoğlu · Sep 12, 2026
Aug 27, 2026 · 1 min read
In an AI-Native organization, teams define problems, question AI outputs, and explain their decisions. How tools fit into the work is considered alongside the team's thinking skills and responsibilities.
Bora Kaykayoğlu · Aug 27, 2026
Aug 24, 2026 · 2 min read
As Rıfat Özcan’s guest on Axis Network, Y. Bora Kaykayoğlu described how an AI-Native professional works. The conversation covered human capabilities, problem-solving methods, and the impact of AI agents on the business world.
Bora Kaykayoğlu · Aug 24, 2026
Aug 19, 2026 · 1 min read
An AI-Native family business brings together the family’s accumulated knowledge, the next generation’s perspective, and professional management capabilities around a shared business need. AI is used to evaluate information and develop new options.
Bora Kaykayoğlu · Aug 19, 2026
Aug 13, 2026 · 1 min read
An AI-Native university considers teaching, research, and administrative operations alongside human capabilities. Verification and responsibility for decisions matter as much as where AI is used.
Bora Kaykayoğlu · Aug 13, 2026
Aug 8, 2026 · 2 min read
An AI-Native team is defined by how it redesigns work around outcomes, rather than the tools it uses. I explore the thinking strengths a team brings, how tasks are divided across its workflow, and how to track development through real cases.
Bora Kaykayoğlu · Aug 8, 2026
Aug 3, 2026 · 2 min read
As 2027 approaches, professionals need to understand their expertise, frame problems clearly, and maintain quality when working with AI. AI-Native work considers how tasks, responsibility for decisions, and learning fit together.
Bora Kaykayoğlu · Aug 3, 2026
Aug 1, 2026 · 2 min read
As access to information and first drafts becomes easier, understanding problems, distinguishing causes, and making decisions become more important. Organizations using AI also need to consider the risk of these capabilities eroding.
Bora Kaykayoğlu · Aug 1, 2026
Jul 7, 2026 · 1 min read
AI-Native professionals work with an understanding of their own expertise and limits. They use AI for research and generating options while taking responsibility for evaluation, context, and the final decision.
Bora Kaykayoğlu · Jul 7, 2026
Jun 3, 2026 · 1 min read
AI-Native work in engineering extends from understanding requirements to comparing alternative architectures and verification. The options AI generates are assessed through engineering judgment.
Bora Kaykayoğlu · Jun 3, 2026
May 3, 2026 · 1 min read
In the new AI-Native sprint series, teams work on real organizational cases. Starting with a strategic need, they reframe the problem, examine the human capabilities it requires, and test how people and AI will work together.
Bora Kaykayoğlu · May 3, 2026