What Didn’t Happen with Generative AI in 2025 and What May Happen in 2026
In 2025, generative AI was expected to revolutionize industries, but several anticipated trends did not materialize as expected. This analysis explores the key developments that fell short and outlines potential advancements for 2026.
Generative AI Trends That Did Not Come to Fruition in 2025
Fully Autonomous Agents in Mass Production: The year 2025 was projected to see widespread implementation of agents capable of performing tasks autonomously. However, nearly two-thirds of companies remained stuck at the pilot project phase. Reports indicated that only 39 percent of businesses observed any significant financial impact on EBIT. Wharton noted that while 82 percent of leaders utilized generative AI weekly, the focus was on enhancing productivity rather than deploying autonomous agents.
End of Hallucinations and Perfect Reasoning: Despite advancements, issues with accuracy and reasoning persisted. Misinformation continued to plague even the most advanced systems, prompting warnings from organizations like OECD.AI regarding operational risks. Stanford’s AI Index 2025 confirmed that challenges in security and reasoning remained, hindering critical applications.
Regulation Fully Enforced Across the Ecosystem: The European AI Act began its gradual implementation in 2025, with bans and training commencing in February and governance starting in August. Many companies were still in preparation mode rather than full compliance, indicating that the complete impact of the regulations will not be felt until 2027.
Cost and Hardware Without Barriers: Investment in generative AI soared, with $644 billion spent in 2025, predominantly on hardware rather than software. This shift underscored the necessity for AI infrastructure over software-driven solutions, as indicated by IDC’s projection of £69.1 billion in generative AI investments.
Uniform Adoption and Double-Digit Productivity for All: Adoption rates increased but remained uneven. The St. Louis Fed reported an overall adoption rate of 54.6 percent in the U.S., with only 5.7 percent of working hours involving generative AI. Benefits were modest, with Stanford’s AI Index showing savings of less than 10 percent and revenue increases below 5 percent.
Expectations for 2026
Looking ahead, 2026 is poised to be a pivotal year for generative AI developments.
Compliance with and Implementation of the AI Act (EU)
With the full enforcement of the AI Act starting in August 2026, companies will need to ensure compliance in areas such as risk management, data governance, transparency, and cybersecurity. This will necessitate the activation of conformity assessments and post-launch monitoring within generative AI processes.
From Pilots to Measured Value and Disciplined Scaling
Data from 2025 suggests that 2026 will be critical for establishing benchmarks and measuring ROI. Companies that redesign their processes and set clear growth objectives will likely see improved outcomes.
‘Agentic’ Architectures with Governance and Security by Design
According to PwC, the transition from demo agents to practical tools will emphasize controlled autonomy and multimodal capabilities. The focus will shift to proactive problem resolution and optimal deployment in sectors like telecommunications.
Infrastructure: NPUs, GPUs, Unified Storage and Data
The gap between expectations and reality in 2025 will drive investments in scalable storage and integrated data architectures. IDC predicts a surge in high-performance infrastructure to support analytics and generative AI.
Market and Skills: High Adoption, but with Critical Skills
While adoption will be widespread, differential results will occur where there is adequate AI training and risk policies. Spending will continue to grow, and measuring ROI will become standard.
Conclusion
The experiences of 2025 have highlighted that generative AI did not fulfill all its promises, akin to other developing technologies. However, it has emerged as a strategic tool for enhancing productivity and efficiency. As we move into 2026, the AI Act will be a significant turning point, demanding transparency and real governance. Companies must transition from scattered pilots to scaled projects with measurable ROI and clear objectives. The coming year promises smarter agents and secure architectures, but success will hinge on the development of AI literacy and specialized roles.
In summary, 2026 will not be characterized by empty promises but by strategic actions paving the way for responsible and effective AI.
