2025 marks the close of AI’s first great wave: the rollout era of large language models like OpenAI’s GPT-5, Google’s Gemini, and Microsoft’s Copilot. Nearly every large enterprise has implemented GenAI in some variation, yet few have seen transformative business results. An MIT report found that 95% of companies gained no meaningful return from broad, carte blanche deployments. Productivity is up, but measurable ROI remains elusive.
Many of the sweeping, “all-knowing” AI projects that once promised to transform entire organizations are now slowing down, as companies recognize that smaller, operational automation efforts deliver far more consistent value. The next few quarters will reveal clear winners and losers as inflated valuations and unsustainable AI initiatives start to correct.
The rise of agentic AI offers enterprises a second chance to apply the hard-earned lessons of GenAI before diving headfirst into the next wave of transformation. Even with 69% of Middle East businesses planning to increase AI investment, success this time will require more than enthusiasm. It will demand a disciplined strategy: anchoring deployments in real business problems, integrating AI with automation and analytics, and enforcing practical governance.
Organizations will enter a critical reevaluation period, taking a hard look at their current AI initiatives and charting a more mature course forward. In 2026, more firms will reassess internal AI teams that have struggled to scale or show measurable impact, deepen vendor partnerships to rebuild and standardize capabilities, and shift from experimentation to integration, embedding AI where it truly enhances workflows rather than chasing hype.
Agentic AI, undefined yet
Agentic AI is expected to dominate the 2026 hype cycle, but consensus on what it actually is will remain elusive. Despite the lessons of GenAI’s early missteps, many organizations will repeat them by rushing into new technologies without clear objectives or governance guardrails. Agentic AI’s most powerful impact often happens behind the scenes—boosting efficiency, precision, and resilience across key economic sectors. Real progress will depend on pairing technical capability with business understanding, bridging IT’s infrastructure role with the expertise of people who know how their company actually operates. The belief that a single autonomous system can manage entire business operations is fading; the next generation of AI agents will augment people, not replace them.
Competing definitions of “agentic AI” will proliferate, many of them oversimplified or technically inaccurate, as vendors race to rebrand existing products to fit the trend. Amid the noise, a handful of standout projects will demonstrate the real promise of AI systems with genuine decision-making independence.
The enterprises that approach this next shift holistically by embedding governance at the core will manage the right balance between speed and safety, ensuring innovation happens responsibly.
The rise of specialized AI teams
In 2026, organizations will double down on specialized AI teams. Drawing from the hard lessons of generative AI, enterprises will shift away from broad, unfocused deployments toward smaller mission-driven teams tasked with focusing on targeted, high-value use cases, such as emerging variations like agentic AI and composite AI.
These cross-functional groups, where business experts, data specialists, and IT engineers work together, will replace the purely IT-led AI model, ensuring real operational understanding drives development and adoption. As every function begins to interact with AI tools, a baseline fluency in applying and interrogating AI will become a core competency, even for non-technical teams. In fact, Alteryx research highlights that globally, 94% of data analysts agree that their role has impacted strategic decision-making in the past year. These teams will develop applications that not only impress the industry but also redefine practical innovation, demonstrating that meaningful impact stems from problem-driven AI design rather than a generalized rollout. Programs such as the 1 Million AI Talents initiative in the UAE are working on building the skills base to support that vision.
The road ahead
As the first AI revolution winds down, a new era defined by agentic AI is taking shape. The race to refine foundation models, scale infrastructure, and deliver practical, decision-driven systems marks a pivotal turning point for global enterprises. In growth markets like the UAE, where AI is projected to add over $100 billion to GDP by 2030, success will hinge on disciplined execution, meaningful use cases, and specialized teams that turn automation into lasting economic and competitive advantage.
