As 2026 approaches, artificial intelligence (AI) continues to evolve at remarkable speed, embedding itself deeper into working life. Organisations now face new challenges and opportunities in how they apply, govern and benefit from AI.
Here Dr Gordon Fletcher, Associate Dean Research and Innovation, and Dr Maria Kutar, Director of Undergraduate Business, explore how AI will shape workplaces, and the wider social and economic landscape, in 2026.
Bridging the hype-reality gap
Over the past year, AI has shifted from a headline-grabbing novelty to a core expectation. Yet while its capabilities are expanding rapidly, meaningful adoption often lags behind. Many high-profile examples look seamless, but they rely on significant behind-the-scenes work to function effectively.
In 2026, attention will increasingly turn to practical realities. Organisations will confront the limits of their data, workforce capability and governance structures, while assessing the real costs and benefits of implementation. The conversation is moving from “what AI could do” to “what AI can actually deliver.” Bridging this hype-reality divide will become one of the defining themes of the year ahead.
Agents: partial automation, human oversight required
One of the most notable shifts in 2026 will be the evolution of AI agents: systems that can plan, act and complete multi-step tasks with minimal prompting. These agents can automate significant parts of roles, yet the remaining tasks – validation, refinement, ethical judgement and contextual understanding – will remain firmly in human hands.
Partial automation brings inherent risks. AI agents can produce missteps, inconsistent reasoning or other unreliable outputs, meaning they must be closely supervised. Clear accountability structures and audit trails are essential as well as processes that include human oversight and intervention by design, to build and maintain trust in AI-driven processes.
To address these risks, workforce capability becomes critical. Organisations will need employees to understand how to work alongside AI, assess its outputs and identify potential errors or shortcomings. Upskilling and reskilling will be central to ensuring AI complements human expertise rather than replacing it. AI literacy will expand beyond technical teams, with leaders, managers and frontline staff needing to understand AI’s limitations and risks, from data biases to regulatory compliance. These organisations that invest in workforce capability alongside technology are most likely to see the most meaningful gains.
At NERIC (Northern Engineering and Robotics Innovation Centre), businesses are already exploring agent-driven automation in robotics, manufacturing and industrial processes, demonstrating safe and effective approaches to innovation using AI.
Infrastructure, governance and ethical oversight
AI will become increasingly integrated into everyday tools, workflows and devices in 2026. Employees may use AI features without even realising it, from productivity platforms to communications tools, as the technology works in the background to support decision-making and streamline routine tasks.
But this convenience hides complexity. Organisations must invest in the infrastructure and governance that make AI reliable, transparent and auditable. This includes preparing high-quality data, integrating systems, and developing frameworks for responsible and ethical use. True transformation will rely less on flashy new models and more on the careful engineering and oversight that underpins dependable AI.
The social and economic context of AI adoption
Beyond the workplace, AI adoption in 2026 will be closely intertwined with wider economic and societal pressures. Growing volumes of AI-generated content and automated communications are already reshaping public expectations, trust and critical engagement. Tools that reveal the source of content are becoming increasingly important, forcing organisations and individuals to be more discerning and helping counter misinformation.
For small and medium-sized enterprises (SMEs) in particular, the challenge is becoming clearer and more urgent. AI should not be viewed simply as a route to short-term efficiency gains that risk triggering a downward spiral of job losses and reduced capability. Instead, the real opportunity lies in identifying how AI can act as a pathway to greater productivity, innovation and sustainable growth. In this context, AI is not just a technical tool, but a strategic influence on organisational behaviour, decision-making and the wider business ecosystem.