Our 2026 Forecasts
Six members of our board wrote 2026: artificial intelligence moving from experimental ground to the center of corporate identity, the ownerless zones inside decision architecture, the discipline of governance, and the future of the apprenticeship track.
Barış Karakullukçu
2026 will be the year artificial intelligence stops being an experimental space and settles into the center of corporate identity. 88 percent of organizations use AI today, yet only 6 percent produce scalable, tangible commercial value; the reason has less to do with technology than with the absence of a strategic business model and disciplined execution. Successful organizations do not bolt AI onto existing structures. They redesign workflows from an AI-first standpoint and put data quality and process architecture ahead of hardware spending. Whether that transformation succeeds depends on the CEO and the board owning AI as a direct P&L responsibility, and on measuring its effects on productivity, speed and cost through outcome-oriented dashboards.
The dimension that matters as much as performance is trust and governance. Unless bias management, explainability and human oversight are designed in from the start, autonomous AI systems cannot produce durable value; this is not an IT topic but a question of corporate risk and leadership. Open and honest communication with employees will be equally decisive. The organizations that stand out will be those that clarify the role of AI, treat reskilling as a strategic investment, and tell the story of the transformation through people. Türkiye can become a regional example through human-centered AI leadership, but only by positioning AI as a new management culture rather than a tool, and by asking boards for accountability for outcomes rather than merely for approval.
Ergi Şener
Over recent years artificial intelligence has evolved from analytical systems that predict, to creative models that generate, and on to structures that increasingly shape decision processes and in some domains act autonomously. As we approach 2026, the success of AI will be measured less by performance metrics than by the decision territory it has been given. The real danger lies not in the shortcomings of AI but in its quietly becoming the norm in areas where human intervention and responsibility were never clearly defined. What I expect from 2026 is that AI is treated not as a solution applicable to every problem but as a strategic infrastructure layer placed deliberately inside an organization’s decision architecture. What I hope is that this positioning happens through moral judgment, accountability and a sense of responsibility for decisions, rather than through reflexes of speed and scale.
Artificial intelligence is becoming a partner that rewrites not only how organizations work but how they think. Less hype and fewer promises; more thought and more responsibility. The real value of AI will emerge not from replacing people but from raising the quality of human thinking. That requires more than choosing the right technology: it means redefining the division of labor between human and machine, and running a deliberate change effort that reaches from the idea of leadership to corporate culture. So I believe the healthiest progress will come from organizations able to hold engineering skill and ethical instinct, entrepreneurial speed and academic discipline, vision and the courage to set limits, all at once. 2026 will define not the future of artificial intelligence but the competence of human intelligence within that future.
Cihan Sarı
2026 will be the year the AI ecosystem puts efficiency and security ahead of sheer size, with a radical shift from vast general-purpose large language models to Small Language Models that organizations run behind their own castle walls. Looking at model governance processes, I see clearly that organizations will stop sending their data to external APIs and start building specialized models that run on-premise, cost less, and know the corporate memory completely. Beyond the advantages in data privacy and processing speed, this shift means organizations declaring their own AI sovereignty.
But that technological localization will demand a serious governance discipline alongside it. Developing or training a model is no longer enough; establishing model risk management processes across the whole span from initiation to decommissioning, and auditing them with the same rigor, will be the most critical success metric of 2026. Managing hallucination risk in these on-premise small language models, running bias tests and maintaining version control will become more valuable than the code itself. The winners in 2026 will therefore not be those holding the best AI model, but those who build their models on a transparent, auditable and sustainable governance frame.
Sarp Kaya
2025 was the year artificial intelligence first produced a major break in business. But the break did not come, as often assumed, from corporate innovation; it came from individual use outrunning corporate deployment. Individual AI use spreading quickly among employees and managers triggered a fear of missing out among business leaders. That led many organizations to invest in haste and on weak strategic foundations. In the end only 5 percent of AI investments delivered a meaningful return. The message is clear: AI is not an end but a means. Real transformation begins by investing in people, in leaders and employees, before technology.
As agentic AI spreads in 2026, AI investment will move from pilot to business outcome; productivity will materialize not through automation alone but by redesigning the decision loop end to end. Organizations will therefore have to manage not the number of models but the impact of the portfolio: revenue growth, cost reduction, lower risk losses, better customer experience and compliance. What separates the leaders will not be technology but measurement discipline, governance across responsibility, oversight and explainability, and leadership able to answer consistently which decisions stay with people and which are handed to machines.
In Türkiye the critical risk is less about access than about the limited supply of leaders and operating models able to manage the transformation. Small and medium-sized businesses in particular lagging the West on AI integration raises the expectation that 2026 will bring concrete state-backed steps aimed at them. Globally we are entering a period in which AI accelerates scientific discovery, makes personalized services mass-market, democratizes access further, and becomes a powerful instrument of politics and communication; that loads organizations with responsibility not only for performance but for trust, ethics and social impact. 2026 will be the threshold year that clearly separates those still saying “we did AI” from those able to say “we redesigned the work with AI”.
Cantekin Ertekin
The RACI matrices of most organizations are still current and tidy today. But they no longer reflect corporate reality. Business units, technology, risk and legal are clearly defined in the table; meanwhile artificial intelligence, which actually influences the direction of decisions, sits outside the organizational design. That points less to an oversight than to a structural gap in how organizations architect their decisions.
AI is usually positioned as supportive, yet in practice it shapes the outcome of the decision. The business side owns the output, the technology function considers delivery complete, and risk joins the process afterwards. The result is a decision with no clear owner.
Entering 2026, organizations should start with a single basic question: what effect is artificial intelligence having on the decisions being made, and on whose behalf is that effect working? Until that is answered plainly, even the best-drawn organization charts stay superficial. Unless organizations redesign moments of decision rather than jobs, what keeps growing will not be role gaps but ownerless decisions.
Sevda Özsönmez
In 2026 the focus in business is less the speed of technology than where people stand inside that speed. As the pace rises, uncertainty does not shrink but deepens; decisions are taken in less time while their effects spread over longer horizons. The real test for organizations is therefore not how fast they move but what ground they move on. Structures that can build context, simplify complexity and set direction deliberately rather than hastily hold the quiet but lasting advantage of this period.
Seen from the perspective of the YZTD HR Committee, 2026 makes it necessary to rethink the relationship between people and technology. As artificial intelligence and automation transform work, ideas like meaning, responsibility and ethics become more visible. The role of HR here is not only to build systems but to offer a frame that protects and deepens the place of the person inside the organization. Value creation is shaped more by awareness than speed, more by intent than scale, and more by the judgment people carry than by the tools they use.
