2026 will not be another year of explosive optimism for artificial intelligence (AI), but the Research Institute of the German bankDeutsche Bank andanalysts Adrian Cox and Stefan Abrudan estimate that "the honeymoon is over and the most difficult year for AI is beginning."
According to the Deutsche Bank Research Institute duo, it will be the most demanding phase to date: a year of maturation, conflict, and critical trials, as three major forces converge and redefine expectations around AI. The technology is "here to stay," but the environment is clearly becoming tougher.
Demystification: when expectations meet reality
The first and perhaps most decisive point for 2026 is thedemystification of genetic AI. Despite rapid improvements in models, particularly in areas such as coding, the transition from pilot projects to productive application reveals the limits of the technology. Issues of accuracy, reliability in unpredictable conditions, and, above all, cost in relation to human labor are now coming to the fore.
For many companies, AI does not yet resemble a technological revolution of the "tractor instead of horse" type, but rather a "more comfortable saddle." Its value is real, but it requires guidance, interpretation, and high-quality data. Most companies do not yet have the infrastructure, system interconnectivity, or internal controls required for widespread use, let alone in sensitive areas such as finance or healthcare.
The gap between technological innovation and actual corporate adoption remains wide, making 2026 a year of revised expectations for management and investors.
Deregulation and congestion: AI in the infrastructure storm
The second point concerns thestructural deregulation between demand and capabilities. Demand for computing power, data, and AI applications continues to grow at an exponential rate, but infrastructure supply faces serious constraints. The AI supply chain is one of the most complex in the history of technology, and a single "bottleneck," from high-bandwidth memory to energy sufficiency, can delay entire projects.
The cost of energy and water for data centers, as well as the limitations of electrical networks, are particularly important. At the same time, the geopolitical dimension is intensifying: export restrictions, rare earths, and the implementation of the EU AI Act from August 2026 add new levels of uncertainty.
At the same time, 2026 is expected to bea year of crisis for independentAIcompanies. Investments continue at impressive levels, but investors will begin to demand sustainable business models. The rising cost of computing power and the pressure for profitability make the environment particularly challenging, especially for those without proprietary infrastructure.
Mistrust: social, political, and institutional tension
The third point is theexplosive rise in distrust surroundingAI. In 2026, legal disputes over intellectual property rights, privacy, and the protection of vulnerable groups are expected to intensify, while incidents of misuse or misapplication of AI will heighten public concern.
The debate on employment is becoming more intense, with the first signs of changes in the labor market—especially for young workers—fueling political controversy. At the same time, AI is taking ona cleargeopolitical dimension, as competition between the US and China over technological standards and open source ecosystems becomes a strategic issue of global significance.